define convergence thesis

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The Convergence Thesis Explained

Table of Contents

The origins of the convergence thesis, key elements of the convergence thesis, the implications of convergence.

• Criticisms of the Convergence Thesis

The convergence thesis is an essential concept in sociology that deals with the idea that industrialized societies, regardless of their initial ideological or political differences, will increasingly resemble each other over time. This concept gained prominence during the mid-20th century, as scholars attempted to understand the consequences of modernization and economic development in both capitalist and socialist societies. The idea suggests that as nations industrialize, they tend to adopt similar technological, organizational, and social structures, leading to a convergence in their economic and societal outcomes. While it has its supporters and detractors, the convergence thesis remains a key concept for understanding global patterns of development.

The convergence thesis emerged in the post-World War II period, during a time when many scholars sought to understand the rapid changes taking place in industrial societies. The Cold War and the ideological competition between capitalism and socialism spurred debates about which system would prove more successful in the long run. Early proponents of the convergence thesis, such as Clark Kerr and his colleagues, believed that both capitalist and socialist systems would become more similar due to the pressures of industrialization. They argued that industrial societies, whether in the United States, the Soviet Union, or elsewhere, would experience common trends such as technological advancement, bureaucratization, and urbanization.

The thesis was also influenced by modernization theory, which posited that as societies modernized, they would follow a similar trajectory of development. Modernization was seen as a process through which traditional, agrarian societies transitioned to industrialized, urban ones, with corresponding changes in culture , politics, and social structure. The convergence thesis expanded upon this by suggesting that not only would societies modernize, but that they would increasingly resemble each other in the process, regardless of their ideological origins.

At its core, the convergence thesis posits that industrialization is a universal process that leads to the development of similar social, economic, and political institutions across different societies. Some of the key elements associated with this process include:

1. Technological Advancement

One of the driving forces behind convergence is technological advancement. As societies industrialize, they rely increasingly on complex machinery, automation, and digital technology to drive their economies. This reliance on technology requires a highly skilled labor force, efficient organizational structures, and sophisticated systems of management. As a result, countries with very different political systems must adopt similar technologies and organizational practices to remain competitive in the global economy. This technological standardization leads to a convergence in both the structure of workplaces and the nature of employment .

2. Bureaucratization

Another central aspect of the convergence thesis is the idea of bureaucratization. Industrial societies require complex systems of administration and management to coordinate large-scale production, distribution, and public services. Regardless of whether a society is capitalist or socialist, it requires a bureaucracy to manage its economy, enforce regulations, and oversee public services. This bureaucratization of society is seen as a necessary response to the complexities of industrial life, and it contributes to the convergence of different political and economic systems.

3. Urbanization

The process of industrialization also leads to rapid urbanization, as people move from rural areas to cities in search of employment. Urbanization brings with it similar patterns of social life, including the development of large, densely populated cities with similar infrastructures, such as transportation systems, housing developments, and public services. Urbanization also leads to the emergence of similar social issues, such as income inequality , housing shortages, and environmental degradation, which must be addressed by governments and societies in similar ways, regardless of their ideological orientation.

4. Education and Professionalization

As industrial societies develop, there is an increasing demand for skilled labor, which in turn leads to the expansion of educational systems. Education becomes a key institution for producing the professionals needed to manage and operate complex industrial economies. Schools and universities become more standardized across societies, offering similar curricula in fields such as engineering, medicine, and business administration. This process of education and professionalization further contributes to the convergence of societies, as people across different countries acquire similar skills and knowledge, leading to a more globally homogeneous workforce.

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What Is Convergence Theory?

How Industrialization Affects Developing Nations

Danny Lehman/Getty Images 

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Convergence theory presumes that as nations move from the early stages of industrialization toward becoming fully industrialized , they begin to resemble other industrialized societies in terms of societal norms and technology.

The characteristics of these nations effectively converge. Ultimately, this could lead to a unified global culture if nothing impeded the process.

Convergence theory has its roots in the functionalist perspective of economics which assumes that societies have certain requirements that must be met if they are to survive and operate effectively. 

Convergence theory became popular in the 1960s when it was formulated by the University of California, Berkeley Professor of Economics Clark Kerr.

Some theorists have since expounded upon Kerr's original premise. They say industrialized nations may become more alike in some ways than in others.

Convergence theory is not an across-the-board transformation. Although technologies may be shared , it's not as likely that more fundamental aspects of life such as religion and politics would necessarily converge—though they may. 

Convergence vs. Divergence

Convergence theory is also sometimes referred to as the "catch-up effect."

When technology is introduced to nations still in the early stages of industrialization, money from other nations may pour in to develop and take advantage of this opportunity. These nations may become more accessible and susceptible to international markets. This allows them to "catch up" with more advanced nations.

If capital is not invested in these countries, however, and if international markets do not take notice or find that opportunity is viable there, no catch-up can occur. The country is then said to have diverged rather than converged.

Unstable nations are more likely to diverge because they are unable to converge due to political or social-structural factors, such as lack of educational or job-training resources. Convergence theory, therefore, would not apply to them. 

Convergence theory also allows that the economies of developing nations will grow more rapidly than those of industrialized countries under these circumstances. Therefore, all should reach an equal footing eventually.

Some examples of convergence theory include Russia and Vietnam, formerly purely communist countries that have eased away from strict communist doctrines as the economies in other countries, such as the United States, have burgeoned.

State-controlled socialism is less the norm in these countries now than is market socialism, which allows for economic fluctuations and, in some cases, private businesses as well. Russia and Vietnam have both experienced economic growth as their socialistic rules and politics have changed and relaxed to some degree.

Former World War II Axis nations including Italy, Germany, and Japan rebuilt their economic bases into economies not dissimilar to those that existed among the Allied Powers of the United States, the Soviet Union, and Great Britain.

More recently, in the mid-20th century, some East Asian countries converged with other more developed nations. Singapore , South Korea, and Taiwan are now all considered to be developed, industrialized nations.

Sociological Critiques

Convergence theory is an economic theory that presupposes that the concept of development is

• a universally good thing
• defined by economic growth.

It frames convergence with supposedly "developed" nations as a goal of so-called "undeveloped" or "developing" nations, and in doing so, fails to account for the numerous negative outcomes that often follow this economically-focused model of development.

Many sociologists, postcolonial scholars, and environmental scientists have observed that this type of development often only further enriches the already wealthy, and/or creates or expands a middle class while exacerbating the poverty and poor quality of life experienced by the majority of the nation in question.

Additionally, it is a form of development that typically relies on the over-use of natural resources, displaces subsistence and small-scale agriculture, and causes widespread pollution and damage to the natural habitat.

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What is convergence theory in sociology?

This theory is one of social change that has been given by economic professor Clark Kerr in a book by him and his colleagues called ’Industrialism and Industrial Man’ in the 1960s. The convergence theory is the one which postulates that all the societies as they move from the early industrial development to complete industrialization tend to move towards a condition of similarity in terms of the general societal and technological norms. This is to say that as the societies move towards development they look become alike will similar structures, which means that the differences among the societies will reduce as they are ultimately on the same path of development. This would thus lead to a single global culture.

This theory given by Clark Kerr is what is known as the ‘logic of industrialization’ which he has also mentioned in his writing, this logic is the thesis of the theory and states that industrialization everywhere has similar consequences whether the society is a capitalist one or a communist one.

This convergence may reflect in the form of what can be called the ‘catch up effect’. This ‘catch up’ refers to the process of opening up the economy of a country to the foreign economy allowing the inflow of capital, this investment helps the economy to maintain pace with the more advanced societies, this process usually takes place when the society is introduced to the industrialization process. However, there might be cases when the reverse may happen i.e. the economy may diverge instead of converging. Such divergence takes place in the case of economies in which the foreign capital is not invested, this may be due to the political and social factors such as lack of education or job training, etc. often these nations are the ones that are unstable.

It is believed that the third world nations are supposed to get out of their conditions of poverty through the process of convergence as they take up the form of western industrial societies.

The convergence theory is often related to the study of modernization, it is believed that the path of development is the one that has been taken by the western industrial societies, which will be undertaken by every society in order to reach complete development and modernization. Thus there is a foxed pattern of development which will be followed. There is thus a convergence if the ideas attitudes and beliefs, thus the overall way of thinking and doing things.

Thus we see that while the convergence theory has made many countries into market economies such as the ones found in the western societies, as it has in Russia and Vietnam which were communist countries earlier and are now market economies.

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Do the Right Thing: Understanding the Interest-Convergence Thesis

Northwestern University Law Review Colloquy , Vol. 106, No. 248, 2012

13 Pages Posted: 26 Feb 2015

Stephen Matthew Feldman

University of Wyoming - College of Law

Date Written: February 24, 2012

Professor Derrick Bell was one of the most influential constitutional scholars of the last fifty years. His insights spurred civil rights scholars as well as thinkers in other fields. One of his most important legacies is the interest-convergence thesis, which asserts that, historically, African Americans gained social justice primarily when their interests converged with the interests of the white majority. In a recently published article, Rethinking the Interest-Convergence Thesis, Professor Justin Driver calls this legacy into question. This Essay defends the interest-convergence thesis from Driver’s attack. It argues that the analytical flaws he identifies only exist by dint of his fundamental misreading of the interest-convergence thesis.

Keywords: critical race theory, social justice, interest-convergence, Derrick Bell

Suggested Citation: Suggested Citation

Stephen Matthew Feldman (Contact Author)

University of wyoming - college of law ( email ).

P.O. Box 3035 Laramie, WY 82071 United States

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Convergence Theory: 10 Examples and Definition

Viktoriya Sus (MA)

Viktoriya Sus is an academic writer specializing mainly in economics and business from Ukraine. She holds a Master’s degree in International Business from Lviv National University and has more than 6 years of experience writing for different clients. Viktoriya is passionate about researching the latest trends in economics and business. However, she also loves to explore different topics such as psychology, philosophy, and more.

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Convergence theory predicts that cultures worldwide will gradually grow increasingly similar due to globalization. 

According to this theory, the further nations progress along their industrialization journey towards becoming fully industrialized powers, they will increasingly emulate other developed countries in terms of technology and cultural norms , leading to one transnational culture .

So, as countries become increasingly linked and globalized, they will tend to imitate each other’s governmental systems (such as democracy rather than communism), economic models (capitalism, socialism, or a blend of both), and collective values.

Such a convergence process is believed to lead to a more homogenous world where nations and societies are increasingly similar. 

Definition of the Convergence Theory

The convergence theory states that as the world continues to develop, expansion in technology and globalization will cause cultures around the globe to increasingly become more similar in a process called cultural convergence (Hess, 2016). 

Over time, such a convergence of diverse social groups could lead to a unified global society with greater uniformity amongst its members.

According to Wilensky (2002),

“…convergence theory is the idea that as rich countries got richer, they developed similar economic, political, and social structures and to some extent common values and beliefs” (p. 3).

Bryant and Peck (2007) state that “the industrialization process is so strong it substantially transforms any society that is industrializing” (p. 189).

In other words, globalization and increased economic integration are believed to lead to a more homogenous world where different nations and societies become increasingly similar regarding their economic, political, and cultural practices. 

Convergence theory provides a helpful lens for studying sociological topics such as socioeconomic development, modernization, and globalization. 

Overall, convergence theory is a helpful tool for understanding the effects that increased global interconnectedness can have on societies and cultures worldwide.  

10 Examples of Convergence Theory

• The spread of the English language : As countries become more intertwined, English has risen to the top as a global language of commerce, education, and communication. For example, in numerous nations worldwide, it is now employed as an aviation lingua franca, while many international businesses also rely on it when corresponding. In essence, English is the bridge that brings people from around the globe together.
• The rise of high-tech industries : As the world progresses and countries become more interconnected, they often follow similar industrial trends. For instance, biotechnology and information technology are two sectors in which many nations invest heavily; The United States and China both devote considerable resources to cyberspace security research.
• The increase of democracy : For a long time, democracy was considered a concept exclusive to the Western world and was only prevalent in European and American countries. Nonetheless, it has spread to many other nations in recent decades, indicating a trend toward the convergence of political systems toward democracy.
• The spread of consumer culture : The expansion of consumer culture has been accelerated by globalization, leading to an almost worldwide standardization in the types of products consumed. Today, many people worldwide go to McDonald’s, shop at Walmart, and wear clothing made by Nike.
• Religious convergence : As interfaith dialogue and progressive religious movements gain traction, we have begun to see a convergence of beliefs and spiritual practices across cultures. This shift towards accepting different faiths can lead to greater understanding among people from various backgrounds, fostering an environment where diversity is respected and celebrated.
• Social convergence : As countries become more interconnected, they adopt similar social norms and values. It is evident in attitudes toward gender, marriage, and sexuality. So, in some respects, societies are becoming more alike.
• The rise of the middle class : Countries worldwide are increasingly experiencing growth in their middle classes, leading to a convergence of lifestyles and behaviors. 
• The spread of mass media : As nations become more interrelated, they often adopt comparable preferences regarding the media they consume. It can result in a more integrated global culture and a greater mutual understanding of diverse cultures.
• The spread of education : Globalization has seen an increased spread of education across the world. Now, many countries are adopting the UK and US systems of education and teaching methods, leading to greater convergence in educational practices.
• The prevalence of global health : The increased spread of medical knowledge and the emergence of international health programs has led to a more unified approach to health care across nations. For example, more countries are adopting the World Health Organization’s guidelines and standards for health. 

Origins and History of Convergence Theory

In the mid-1960s, American sociologist Clark Kerr introduced a groundbreaking concept – the theory of convergence. It asserted that societies around the globe were continuously becoming more and more alike despite diverse cultural backgrounds (Brubaker, 2022) .

Kerr believed that this process was being driven by changes in technology, communication, and transportation that allowed for increased international trade and collaboration.

He argued that homogenizing cultures would create a utopian world without conflicts and disparities (Brubaker, 2022). 

Kerr’s ideas were developed further by other sociologists in the late 20th century. These theorists argued that convergence was more than just a simple process and could have a tangible impact on how societies interact. 

The technological version of Galbraith’s “convergence” has also gained wide popularity. He linked the future of the industrial system with the convergence of two systems – capitalist and socialist (Mishra, 1976).

Galbraith explained the inevitability of “convergence” because the large scale of production, characteristic of developed capitalist and socialist countries, requires an approximately similar planning and organization system.

One of the options for convergence was proposed by the outstanding Dutch mathematician and economist Tinbergen, who put forward the theory of “optimal order” (Don, 2019).

According to Tinbergen, as a result of the synthesis of both systems – some elements of “capitalist efficiency” and “socialist equality” – an “optimal system” is formed, the main principles of which are the peaceful coexistence and business cooperation of states (Don, 2019).

Today, convergence theory is used to understand the effects of globalization and how it impacts different societies. It also explains why specific trends, such as consumer culture and democracy, have become more prevalent in recent years. 

Overall, convergence theory has become essential for understanding the forces shaping our world today.

Convergence Theory vs. Divergence Theory

Convergence theory seeks to explain how societies become more alike, while divergence theory accounts for the ways in which they grow increasingly distinct.

Convergence theory suggests that countries adopt similar social norms and values as they become more interconnected (Hess, 2016).

On the other hand, divergence theory claims that as societies move further from each other geographically and culturally, they become increasingly dissimilar (Brubaker, 2022).

So, while some countries embrace same-sex marriage as an accepted form of union, other nations condemn it entirely. Divergence theorists explain this difference due to two societies growing apart and developing distinct values.

Ultimately, divergence and convergence theories explain how societies change over time. While the former focuses on differences between cultures, the latter focuses on similarities that might arise from increased global connections. 

Importance of Convergence Theory

Convergence is not just one of the hobbies or inventions but a requirement of the time associated with the search for socio-economic alternatives.

In particular, the 2020 economic crunch made it clear that the world could not adequately respond under the existing socio-economic model since its structure is based on methodological individualism.

Thus, the idea of the adherents of convergence was confirmed that the market form of economy applies only to a part of socio-economic relations and, in many cases, turns out to be harmful and powerless.

Furthermore, convergence theory also has implications for social cohesion and stability in any community.

As societies become more similar, there may be less social tension and conflict as people share similar values, beliefs, and practices, promoting social harmony and reducing the risk of civil unrest.

Notably, convergence theory can encourage international cooperation and collaboration. It suggests that countries can learn from each other’s experiences and adopt best practices to promote growth and development. 

Critique of Convergence Theory

As convergence theory has become highly regarded in many fields, it is still subject to criticism since ignores cultural and historical differences, overlooks power and inequality, and oversimplifies complexity .

1. It Ignores Cultural and Historical Differences

Convergence theory assumes that all societies will converge towards similar values, beliefs, and practices as they become more modern or more connected to the global economy. 

However, this assumption ignores that different societies have unique cultural and historical backgrounds that shape their development differently (Hay & Couldry, 2011).

For example, the modernization process in Japan has been very different from that in India or Brazil.

2. It Overlooks the role of Power and Inequality

Convergence theory often overlooks the role of power and inequality in shaping social change .

Furthermore, it disregards the fact that many societies may move in different directions, with some populations more likely to experience advantages from convergence than others.

3. It Oversimplifies Complexity

Convergence theory tends to oversimplify the complex social, economic, and political processes that shape social change.

This idea presumes that all societies will progress towards the same goal, regardless of any distinctions in economic standings or governmental systems.

In reality, many factors influence the development of societies, making it difficult to predict which direction a community will take accurately (Form, 1979).

So, while convergence theory may help understand broad trends, it cannot account for the unique characteristics of different societies or the subtle interactions between various factors. 

Convergence theory predicts that as the world becomes increasingly globalized, cultures worldwide will gradually grow more similar.

This theory argues that technological, economic, and political developments lead to a convergence of social structures and cultural norms. 

The convergence process could lead to a unified global society with greater uniformity among its members, thus providing a helpful lens for studying topics such as socioeconomic development, modernization, and globalization.

Its origins are traced back to the mid-1960s when Clark Kerr states that societies around the globe were continuously becoming more and more alike due to technological, communication, and transportation advancements.

Today, convergence theory is a valuable tool for understanding the effects of increased global interconnectedness on societies and cultures worldwide.

Brubaker, D. (2022).  Psychosocial political dysfunction of the republican party. New York: Archway Publishing.

Bryant, C. D., & Peck, D. L. (2007).  21st century sociology: A reference handbook. Thousand Oaks Sage Publications.

Don, F. J. H. (2019). The influence of Jan Tinbergen on Dutch economic policy.  De Economist, 167 (3), 259–282. https://doi.org/10.1007/s10645-019-09333- 1

Form, W. (1979). Comparative industrial sociology and the convergence hypothesis.  Annual Review of Sociology, 5 , 1–25. https://www.jstor.org/stable/2945945

Hay, J., & Couldry, N. (2011). Rethinking convergence/culture.  Cultural Studies, 25 (4-5), 473–486. https://doi.org/10.1080/09502386.2011.600527

Hess, P. N. (2016).  Economic growth and sustainable development . London: Abingdon.

Mishra, R. (1976). Convergence theory and social change: The development of welfare in Britain and the Soviet Union.  Comparative Studies in Society and History, 18 (1), 28–56. https://www.jstor.org/stable/178161

Wilensky, H. L. (2002).  Rich democracies. Univesity of California Press.

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Derrick Bell’s Interest Convergence and the Permanence of Racism: A Reflection on Resistance

• Alexis Hoag

Nothing about this moment — COVID-19’s disproportionate impact on Black people, Trump’s explicit anti-Black racism , or the mass demonstrations following lethal police use of force against Black people — would have surprised Professor Derrick Bell.  These fault lines are not new; rather, these events merely expose longstanding structural damage to the nation’s foundation.  A central theme of Bell’s scholarship is the permanence and cyclical predictability of racism.  He urged us to accept “the reality that we live in a society in which racism has been internalized and institutionalized,” a society that produced “a culture from whose inception racial discrimination has been a regulating force for maintaining stability and growth.”  Bell would have also foreseen Trump’s presidency as the likely follow-up to eight years of the nation’s first Black President.  Any amount of racial advancement, Bell argued , signified “temporary ‘peaks of progress,’ short-lived victories that slide into irrelevance as racial patterns adapt in ways that maintain white dominance.”  In this reflection, I revisit Bell’s arguments, including his interest convergence theory ,  to provide clarity on the current moment and to reflect on the way his scholarship has impacted my work as a civil rights lawyer, scholar, and teacher.  

I first encountered Professor Bell in 2005, as a student at New York University School of Law. By then, he had maintained a visiting professorship for nearly two decades in an arrangement made with his former student, NYU Law Dean and later University President, John Sexton .  Bell’s legendary status as the father of Critical Race Theory and as a champion of faculty diversity was firmly ensconced.  At the time, I was active in a student group demanding more faculty of color, and our group asked Bell for advice.  Soft-spoken and impeccably dressed, he was surprisingly accessible.  Bell was intimately aware of our concerns, having experienced them in nearly every professional space he had entered.  His advice was gentle and encouraging, but decisive.  With his support, we regularly staged silent protests before faculty meetings, lining the hallway armed with posters, as our professors walked past to vote on candidates.  Bell likely sensed that staging the protests would be more beneficial for our development as social justice lawyers than for hiring more people of color for the faculty.  

To the casual observer, Bell’s warmth, wit, and gentle demeanor belied his radical beliefs and scholarship.  But what made his writings, actions, and teaching so effective was that Bell embodied all these qualities.  As his student and teaching assistant in Constitutional Law, it was hard for me to reconcile what I perceived as pessimism and cynicism in his writings with the affable and charming professor presiding over the classroom.  At first read, the ending of Space Traders made me shudder, but I could not deny the allegory’s accuracy in depicting the plight of Black people at the hands of white people in power; given the opportunity to access wealth, unlimited energy, and technological advances in exchange for Black people, white America made the trade.  It is one of Bell’s many works to which I often turn, as I did last year when I transitioned to teaching law .  And I frequently recommend it to my students.

Only after I started practicing did I cease seeing Bell as a pessimist and recognize him for what he was: a realist .  Working on capital cases as an appellate defender in Tennessee, no federal judge wanted to acknowledge the gross racial disparities in death sentencing in a state where Black men convicted in a single county made up the largest subgroup on death row.  The draconian rules of procedural default prevented these same clients from securing relief on otherwise meritorious claims of racial discrimination in jury selection.  Later, as a lawyer at the NAACP Legal Defense and Educational Fund, Inc. ( LDF ), I inherited one of the Mississippi school desegregation cases that Bell filed with his colleagues Mel Leventhal and Marian Wright Edelman .  Despite five decades of federal court monitoring, the public school district was still failing to adhere to the law established in Brown v. Board of Education .  My colleagues and I reengaged members of the original plaintiff class, now grandparents of children enrolled in the same district.  The district no longer operated a dual school system separated by race; instead, it operated a single, virtually all-Black, under-resourced school system that funneled children into the criminal legal system.  In civil rights and the criminal legal system, I was fighting the same fight as my forebearers with similarly racist results.

So, as Bell posed , “Now what?”

For the answer, I turn to Bell’s theory of interest convergence: that the rights of Black people only advance when they converge with the interests of white people.  Twenty-five years after the U.S. Supreme Court’s ruling in Brown v. Board of Education , Bell argued that the holding  “cannot be understood without some consideration of the decision’s value to whites, not simply those concerned about the immorality of racial inequality, but also those whites in policymaking positions able to see the economic and political advances at home and abroad that would follow abandonment of segregation.”  How else, Bell argued , could one account for the country’s “sudden shift . . . away from . . . separate but equal . . . towards a commitment to desegregation?”  Then, the world was in the midst of the Cold War, and the nation’s hypocrisy in its treatment of Black people at home was not lost on our adversaries abroad.

It is through this lens that I view the actions that have transpired since George Floyd’s murder: the rapid passage of law enforcement reforms (that had previously stalled), swift actions and statements from corporations decrying anti-Black racism (from corporations that had previously denied it), and the sudden cross-racial embrace of “Black Lives Matter” (by white people who had previously resisted it).  To be clear, my argument here largely applies to the sharp increase in (public) racial consciousness among white people.  What has changed is not the legal, or even social status of Black people, but rather the social (media) acceptability of anti-Black racism.  Said another way, it is now popular and financially advantageous to be anti-racist.

The popularity and profitability of anti-racism is nowhere more evident than on social media.  With many Americans either out of work or working from home, we are all glued to pocket-sized screens.  The hyper focus online created a higher stakes platform for the performance of protesting anti-Black racism.  Social media enables users to measure the popularity and reach of each post.  Yes, millions marched against anti-Black racism in cities and small towns across the nation, but these demonstrations were largely captured and shared via social media.  Appearing at a Black Lives Matter demonstration showed solidarity, but appearing and then posting a photograph of it had measurable social currency.  Consumer-driven corporations were all quick to showcase their anti-racist positions.  Never mind that some of these corporations had engaged, or continue to engage, in anti-Black practices .  Although retail spending decreased during the pandemic, companies could not possibly lose more money speaking out against racism, but they could by remaining silent, or worse, condoning racism .

I argue that a major motivating factor for many white peoples’ actions and corporations’ pronouncements against racism was not to advance Black equality.  Rather, it was the realization that the nation cannot maintain its economic, political, and social superiority over the rest of the world while remaining silent about anti-Black racism in America.  Racism is a bad look.  Silence in the wake of racist events is even worse.  And just as in the 1950s, the world is watching America. Only now, the world is consuming America’s hypocrisy in real time on social media.  Instead of America decrying human rights abuses across the globe, the globe is protesting human rights abuses in America.  We all witnessed the responses: Democratic members of Congress donned West African kente cloth to announce their police reform bill, later kneeling in long-belated solidarity with Colin Kaepernick.  Broadcast from the Rose Garden, Trump gave lip service to the experiences of Black people at the hands of law enforcement.  Quaker Oats changed the name and image of its Aunt Jemima brand.  NASCAR prohibited confederate flags from its events and properties.  All abrupt, performative displays of wokeness, despite prior unanswered complaints of anti-Black racism.

And lest we forget, just a few years ago many white people responded with distaste and hostility to the expression “Black lives matter” following the murders of Trayvon Martin and Michael Brown.  With earnestness, well-meaning white people asked , “don’t all lives matter”?  Yet, here we are, roughly six years later, witnessing millions of people posting black squares on their Instagram accounts with long captions or simple hashtags denouncing anti-Black racism.  Again, these were largely white people.  I observed many of my Black peers posting variations of: “I’m tired” or nothing at all.  On my bike rides and runs through New York City, whenever I pass wealthy, white enclaves I frequently observe signs in windows or draped flags adorned with the words: “Black Lives Matter” and “White Silence is Violence.”  Where were these signs when New York City police officers fatally shot Amadou Diallo, unarmed and standing in the doorway of his home, 41 times?

Will this moral posturing online translate into substantive changes in the law and in society for Black people?  It was lost on no one that police used excessive force on Black people protesting excessive police force against Black people.  Law enforcement officials murdered Rayshard Brooks on camera weeks after officers murdered George Floyd, his death also captured on camera.  Officials have not yet arrested the officers who murdered Breonna Taylor.  The wave of police reforms is not insignificant, but when we closely examine these measures, they fail to provide paths to redress for Black victims of excessive police force or even address the practices that result in a disproportionate use of force against Black people.  For that, we would need to eradicate the presumption of criminality and dangerousness that society assigns Black people.  But according to Bell, that is unlikely because “white people desperately need[] . . . black people — or most blacks — in a subordinate status in order to sustain . . . the . . . preferential treatment to which every white person is granted…”

Bell warned us that “yearning for racial equality is fantasy.”  There is no vaccine for America’s illness.  Like Bell, I do not believe we can eradicate racism from a nation built and dependent upon it.  The subordination of Black people provides “whites with a comforting sense of their position in society. . . whether or not [white people] want it.”  But this acknowledgment does not mean we should abandon the fight to challenge the racial hierarchy.

To counter the permanence of racism, Professor Bell advocated that our fight against it must be equally persistent.  He implored us to “realize with our slave forbearers that the struggle for freedom is, at bottom, a manifestation of our humanity that survives and grows stronger through resistance to oppression even if that oppression is never overcome.”  Although many of my death-sentenced clients — now represented by successor counsel — still await rulings from federal judges, there was nevertheless something meaningful about the process of post-conviction litigation.  For many of my clients, the work my team and I performed on their behalves enabled them for the first time to feel listened to, heard, and seen.  In investigating and presenting their habeas claims, we told their stories and elevated their humanity.  The collective effort reminded our clients that their lives have value.  Later, while working for LDF, I encountered an older woman in Meridian, Mississippi. She had grandchildren enrolled in the same school district as her children were during the desegregation litigation Bell initiated.  She recalled that the white townspeople threatened to kill her and her children if she got involved in the lawsuit.  This was no idle threat: James Chaney had been teaching her children to read when he was lynched during Freedom Summer.  I asked why she nevertheless agreed to put her name on the lawsuit.  She responded: “At least I’d die fighting with my babies.”  Sometimes, the whole point is to resist. Professor Bell was a brilliant scholar, activist, and civil rights litigator, but he was also an exceptional teacher and mentor.  He gifted me with the knowledge that there is power in amplifying the voices and experiences of those most impacted by racial inequality.  And although I may not see the change for which I advocate, there is value in the struggle against oppression.  I will continue to bear witness, amplify stories of injustice, and encourage my students to do the same.

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• > Journals
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• > Political Convergence: An Empirical Assessment

Article contents

Political convergence: an empirical assessment.

Published online by Cambridge University Press:  13 June 2011

When detente emerged as the focal point of American foreign policy in the early 1970's, the issue of whether or not communist political systems were becoming more like Western democracies over time (i.e., “converging”) was raised. This paper assesses political scientists' efforts to analyze such a hypotheses, particularly the implication that socioeconomic changes called “development” and “modernization” co-vary with fundamental political change. After identifying three components of the convergence hypothesis—pluralism, nationalism, and legitimacy—the author examines published research for empirical evidence regarding these phenomena. He stresses the similarities and differences of political change among communist states. Convergence theory is found to be inadequate in most respects for understanding the relationships between socioeconomic and political changes, although various political trends (such as pluralization) are evident.

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1 Meyer , , “Theories of Convergence,” in Johnson , Chalmers , ed., Change in Communist Systems ( Stanford: Stanford University Press 1970 ), 337 Google Scholar .

2 See, for instance, Jan Tinbergen , “Do Communist and Free Economies Show a Converging Pattern?” in Bornstein , Morris , ed., Comparative Economic Systems ( Homewood, LLL. : Dorsey 1965 ), 455 –64 Google Scholar .

3 Black , , The Dynamics of Modernization ( New York : Harper and Row 1966 ), 49 Google Scholar .

4 Huntington , Samuel P. and Brzezinski , Zbigniew , Political Power: USA/USSR ( New York : Viking Press 1964 ) Google Scholar .

5 Meyer , , “USSR Incorporated,” in Treadgold , Donald W. , ed., The Development of the USSR ( Seattle : University of Washington Press 1964 ) Google Scholar , 21–28; see also Meyer , , The Soviet Political System ( New York : Random House 1965 ) Google Scholar .

6 Brzezinski , , “The Soviet Political System: Transformation or Degeneration,” Problems of Communism (January-February 1966 ) Google Scholar .

7 Brzezinski , , ed, Dilemmas of Change in Soviet Politics ( New York : Columbia University Press 1969 ), 30 – 34 Google Scholar .

8 Fainsod, “Roads to the Future,” ibid. , 134.

9 Mehnert , , “Westerly Winds Over Eastern Europe,” in London , Kurt , ed., Eastern Europe in Transition ( Baltimore : Johns Hopkins University Press 1966 ), 309 –23 Google Scholar .

10 Kassof , , “The Future of Soviet Society,” in Kassof , , ed., Prospects for Soviet Society ( New York : Praeger 1968 ), 504 –5 Google Scholar .

11 Hough , Jerry , “The Soviet System: Petrification of Pluralism,” Problems of Communism XXI (March-April 1972 ) Google Scholar , Matejko , Alexander , Social Change and Stratification in Eastern Tiurope ( New York : Praeger 1974 ) Google Scholar .

12 Daniels , , “Soviet Politics Since Khrushchev,” in Strong , John W. , ed., The Soviet Union Under Brezhnev and Kosygin ( New York : Van Nostrand Reinhold 1971 ), 22 – 23 Google Scholar .

13 Skilling , and Griffiths , , eds., Interest Groups in Soviet Politics ( Princeton : Princeton University Press 1971 ) Google Scholar ; see particularly Skilling's article “Groups in Soviet Politics: Some Hypotheses.” Also interesting is Stewart , Philip D. , “Soviet Interest Groups and the Policy Process,” World Politics , XXII (October 1969 ) Google Scholar .

14 For example, see Kautsky , John H. , Political Change in Underdeveloped Countries ( New York : Wiley 1963 ), 79 – 89 Google Scholar . My article, “The Early Success of Ostpolitik: An Eastern European Perspective,” World Affairs , Vol. 138 (Summer 1975 ), 32 – 50 Google Scholar , discusses increasing contact with Western Europe and the independence from Soviet positions.

15 Gilison , , British and Soviet Politics: A Study of Legitimacy and Convergence ( Baltimore : Johns Hopkins University Press 1972 ) Google Scholar .

16 Ibid. , XII.

17 Ibid. , 37.

18 Ibid. , 93.

19 Ibid. , 105.

20 Ibid. , 169.

21 See for instance, Korbonski , Andrzej , “Liberalization Processes,” in MesaLago , Carmelo and Beck , Carl eds., Comparative Socialist Systems ( Pittsburgh : University of Pittsburgh Center for International Studies 1975 ), 192 – 214 Google Scholar .

22 Ibid. , 196.

23 These data are available in machine-readable form from the Eastern European Elite Archive, University of Pittsburgh, William Jarzabek, archivist.

24 Beck , , “Leadership Attributes in Eastern Europe: The Effect of Country and Time,” in Beck , and others , , Comparative Communist Political Leadership ( New York : McKay 1973 ) 126 –27 Google Scholar

25 Ludz , , The Changing Party Elite in East Germany ( Cambridge : The MIT Press 1972 ), 321 Google Scholar .

26 Nelson, “Background Characteristics of Local Communist Elites,” forthcoming in Polity (1978). My assessment of the Romanian political elite at a local level was based upon numerous interviews with such individuals in four counties (judete).

27 Ludz (fn. 25), 321.

28 Beck (fn. 24), 129.

29 Ibid. , 143.

30 Nelson , , “Socio-economic and Political Change in Communist Europe,” International Studies Quarterly XXI (June 1977 ), 359 –88 CrossRef Google Scholar .

31 These data are available at the Inter-University Consortium for Political and Social Research, Ann Arbor, Michigan. Publications from these data include, among others, Philip Jacob and others, Values and the Active Community ( New York : Free Press 1971 ) Google Scholar , Teune , Henry and Ostrowski , Krystof , “Political Systems as Residual Variables,” Comparative Political Studies , VI (April 1973 ), 3 – 21 CrossRef Google Scholar .

32 See Zaninovich, “Elites and Citizenry in Yugoslav Society: A Study of Value Differentiation,” in Beck (fn. 24), 226–97; Triska and Barbie, “Evaluating Citizen Performance on the Community Level,” paper delivered at the 1975 meeting of the American Political Science Association, San Francisco.

33 Zaninovich (fn. 32), 285.

34 Triska and Barbie (fn. 32), 46.

35 Zaninovich (fn. 32), 285.

36 Lodge , , “Soviet Elite Participatory Attitudes in the Post-Stalin Period,” American Political Science Review , Vol. 62 (September 1968 ), 827 –39 CrossRef Google Scholar ; and “Attitudinal Cleavages Within the Soviet Political Leadership,” in Beck (fn. 24), 202–25.

37 Lodge, “Soviet Elite Participatory Attitudes” (fn. 36), 838.

38 Nelson , , “Sub-National Political Elites in a Communist System,” East European Quarterly X (December 1976 ), 459 –94 Google Scholar .

39 Schwartz , and Keech , , “Group Influence and the Policy Process in the Soviet Union,” American Political Science Review , Vol. 62 (September 1968 ), 840 –51 CrossRef Google Scholar ; and “Public Influence and Educational Policy in the Soviet Union,” in Kanet , Roger E. , ed., The Behavioral Revolution and Communist Studies ( New York : Free Press 1971 ), 151 –86 Google Scholar .

40 Ibid. , 152.

41 Ibid. , 181.

42 Tarkowski , , “A Study of the Decisional Process in Rolnowo Powiat,” Polish Sociological Bulletin , XVI , No. 2 ( 1967 ), 89 – 96 Google Scholar .

43 Ibid. , 93–94.

44 Pirages , , “Socio-economic Development and Political Access in the Communist Party-States,” in Triska , Jan F. , ed., Communist Party-States ( Indianapolis : Bobbs-Merrill 1969 ), 249 –81 Google Scholar .

45 Ibid. , 273.

46 Brzezinski , , The Soviet Bloc: Unity and Conflict ( Cambridge : Harvard University Press 1967 ), IX Google Scholar .

47 Lowenthal , Richard , World Communism: The Disintegration of a Secular Faith ( New York : Oxford University Press 1966 ) Google Scholar .

48 Lendvai , Paul , Eagles in Cobwebs ( New York : Doubleday-Anchor 1969 ), 447 Google Scholar .

49 Kintner , and Klaiber , , Eastern Europe and European Security ( New York : Dunellen 1971 ), 254 Google Scholar .

50 Conformity to Soviet policies was also operationalized through the construction of an index from many component measurements, as described Ibid. , chap. 13.

51 Ibid. , 255.

52 Tucker , , “Measuring Cohesion in the International Communist Movement, 1957–1970,” mimeo ( Indiana University , February 1973 ), 38 Google Scholar .

53 Ibid. , 23, 29.

54 Hopmann, “The Effects of International Conflict and Detente on Cohesion in the Communist System,” in Kanet (fn. 39), 335.

55 Triska and Johnson, “Political Development and Political Change,” in Mesa-Lago and Beck (fn. 21), 267.

56 Ibid. , 282.

57 For a study of the political role played by schools in communist states, see Grant , Nigel , Society, Schools and Progress in Eastern Europe ( New York : Pergamon Press 1969 ) Google Scholar esp. chap. 5. Perhaps the most complete treatment of socialization efforts in the U.S.S.R. is Soviet Political Indoctrination by Hollander , Gayle D. ( New York : Praeger 1972 ) Google Scholar . The best country-specific study of political education is Georgeoff , Peter John , The Social Education of Bulgarian Youth ( Minneapolis : University of Minnesota Press 1968 ) Google Scholar .

58 Zaninovich (fn. 32), 272.

59 Ibid. , 248.

60 Ibid. , 258–67.

61 Cary , , “Political Socialization of Soviet Youth and the Building of Communism,” in Bertsch , Gary K. and Ganschow , Thomas W. , eds., Comparative Communism ( San Francisco : Freeman & Co. 1976 ), 289 –99 Google Scholar .

62 Inkeles , Alex and Bauer , Raymond , The Soviet Citizen ( New York : Atheneum 1968 ) Google Scholar .

63 Ibid. , chap. X.

64 Ulc, Politics in Czechoslovakia ( San Francisco : W. H. Freeman 1974 ) Google Scholar .

65 Ibid. , 9.

66 Ibid. , 19.

67 Ibid. , 23.

68 Nelson (fn. 30).

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• Volume 30, Issue 3
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• DOI: https://doi.org/10.2307/2009873

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Principles of convergence in nature and society and their application: from nanoscale, digits, and logic steps to global progress

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Knowledge, technology, and society as well as natural systems are increasingly coherent and complex, and new systems are continuously formed at their interfaces. Convergence is a problem-solving strategy to holistically understand, create, and transform a system for reaching a common goal, such as advancing an emerging technology in society. The systems may be either in natural, scientific, technological, economic, or societal settings. Convergence offers a unifying strategy applicable to all systems that can be modeled as evolving neural-like networks. The paper presents an overview of the convergence science including underlying theories, principles, and methods and illustrates its implementation in key areas of application. The convergence approach begins with deep integration of previously separated fields, communities, and modes of thinking, to form and improve a new system, from where solutions divergence to previously unattainable applications and outcomes. The worldwide science and technology (S&T) landscape is changing at the beginning of the twenty-first century because of convergence. First, there is the affirmation of three transdisciplinary general-purpose technologies—nanotechnology, digital technology, and artificial intelligence (AI). A second main characteristics is the deep integration of five foundational science and technology fields (NBICA: nanoscale, modern biology, information, cognition, and artificial intelligence) from their basic elements—atoms, genes, bits, neurons, and logic steps and their collective action—to address global challenges and opportunities. The affirmation of nanotechnology at the confluence of disciplines toward systematic control of matter at the nanoscale has been an enabling inspiration and foundation for other S&T fields, emerging industries, and convergence solutions in society. Several future opportunities for implementation of convergence principles are the global S&T system, realizing sustainable society, advancing human capabilities, and conflict resolution.

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Introduction

Defining convergence.

In the early decades of the twenty-first century, with the growth of knowledge societies, progress in emerging technologies, and increased complexity of societal systems, convergence has reached a special significance. It has become a means of harnessing the fundamentally new and rapid scientific and technological advances of our time. Convergence has various meanings in literature as a function of the domains that are subject of integration and how they are brought together. In this paper, convergence refers to a strategy for reaching a shared goal in a system. The principles guiding convergence and their implementation will be outlined.

Progress in science and technology is accelerating, increasingly interdependent and emergent. At the same time, society is becoming more populous and more dynamically networked, with longer-term and more intense interactions. An increasing number of research areas, such as the study of universe, require dealing with a higher level of complexity with limited information. Such systems and topics of study are too complex to be adequately evaluated and managed using single-domain approaches. Problem-solving must go beyond a single application field, discipline, or pathway. A general problem-solving strategy for all these cases is convergence.

Convergence strategy aims to holistically understand and transform a knowledge, technology, or society system for reaching shared goals or align with shared external constrains (Roco 2002 ; Roco and Bainbridge 2003 , 2013 ; NASEM 2014 , 2019 ). Most such systems can be modeled as neural-like networks with dynamic or complex behavior. Such networks are systems composed of artificial neurons and artificial neural links whose structure and functions may be simulated in a similar manner as the biological neural networks or circuits of neurons linked via synapsis as found in brain. Seven principles to facilitate convergence have been formulated reflecting the unifying behavior of the neural-like networks describing the respective systems. Using convergence principles, multidomain knowledge databases, digitization, and artificial intelligence are tools for bridging diverse fields together toward a holistic comprehension. Illustrations of shared goals are research toward realizing an emerging technology, satisfying the environmental planetary boundaries, and better decision-making in research funding organizations. Understanding the evolution of natural ecosystems is driven by astro-geo-physics-bio convergence principles within the nature bounding constrains.

Convergence processes not only connect across domains of human activity but also along evolution in time and across types of behavior, architectures, and actions. A convergence process is evolutionary and transformative achieving mutual compatibility, synergism, and integration of seemingly different disciplines, technologies, and communities to create added-value transformations for shared goals. Convergence is a way of thinking that requires a specific culture. Convergence is a process that advances creativity, invention, and innovation. Convergence in society ultimately leads to finding better solutions in daily tasks at work, for learning, aging with dignity, and physical and cognitive wellness.

This is a conceptual shift from the focus on studying the components of a system to managing both the components and the overall system. How will convergence change society and how can individuals and groups adjust and take advantage of this? Convergence for reaching a common goal in a system, or in brief “convergence,” offers a framework for philosophical concepts and culture that connect nature and society.

Convergence may begin with setting together multidisciplinary teams or integrating multiple disciplines, and it continues with several essential phases such as creating a new system from where divergence to new competencies and applications take place to reach the desired goals. Convergence is not described just “by coincidental links” or “multiple nodes” in a networked system—but it is an interactive, purpose-driven strategy and process. Promoting links alone may lead to “info silos” or “eco chambers.” Convergence does not imply “top-down governing” in an ecosystem—but convergence governance is dominated by horizontal links and self-organization principles.

• Convergence science

Convergence science includes the underlying theories, principles, and corresponding specific methods that facilitate convergence, as presented later in this paper. Ten theories underpin the origin and relevance of convergence beginning with unity of nature and human interaction ecosystem. At the core of transforming features, there are seven convergence principles and corresponding methods, beginning with the holistic view of a system and closing with the confluence of resources to transform the system.

All ecosystems in nature and society are guided by similar bottom-up principles and patterns, originating from similar dynamic behavior of their neural-like networks even if they have different domains of application (social, production, or biological networking) and different system architectures (linear, hierarchical, others). This is true for societal interactions including for areas such as semantic systems and religious beliefs (Bainbridge 1995 , 2004 ). The tools of the digital economy, IT, and AI facilitate the establishment and operation of a global neural-like network with heterogeneous composition.

Similar dynamic patterns can be found in the spiral space-time evolution of natural processes (e.g., tornado and stellar system; see Fig.  1 ), the spiral of innovation describing the evolution of smart phone technology platform (crossing in time multiple S&T fields such as materials, cognition, electronics, energy, personalized learning, and packaging, with the same common goal; Roco et al. 2013 ), and the spiral of multidisciplinary approach to advance unifying educational programs (teaching similar foundational S&T modules by rotation in different disciplinary fields/courses; Roco and Bainbridge 2003 ). The spiral convergence pattern also is a characteristic of the growing Internet of Things (IoT) progressing in time across multiple fields. The global IoT in 2017 had more than 5 billion components and an extended network of 50 billion things, poles, and processes, plus others affected by the network. For the first time in history, most human activities are linked in a unifying world network.

Spiral patterns of convergence structures in nature: a tornado (credit Real Tornado, Google) and b stellar system (credit Perfect Spiral Galaxy, Gemini Observatory)

Observing and controlling convergence in complex systems

To identify the essential and unifying characteristics in large dynamic systems, one needs observations and analysis based on abstraction (to see what is essential), system view (holistic understanding, see what are the unifying characteristics), generalization (across domains), and simplicity (eliminate non relevant details to avoid system noise). The reductionism to essential features does not means reduction to individual components. There is an increase use of general-purpose mathematics, nanotechnology, digitization, artificial intelligence and the so-called universality concepts as tools of implementing convergence. Control of convergence in complex systems can be done by changing the system boundary conditions, controlling the rules for interaction links between nodes or of a subset of essential nodes, and guiding information and energy distribution. A trend in observing complex systems is the increase use of system AI.

Possible benefits

Several possible benefits from implementing convergence are:

Creating generalizations in understanding of systems (“unity in diversity”) and new ideas in research and production at the confluence of fields, which are achievable with relatively small added effort or investment. Identifying general theories or “universality” in reaching a goal in complex adaptive systems is one of science’s and society’s main challenges.

Realizing compelling goals in complex systems, which are difficult to reach with other strategies.

Addressing emerging topics that could not be identified and addressed well otherwise. Illustrations include confluence of general-purpose AI and societal trends including human rights, emerging technologies for biomedical breakthroughs, and connecting quantum theories to manufacturing and space exploration.

Improving human behavior and capabilities, teamwork methods, and outcomes.

Creating convergence culture as a framework of mind for individual and groups, to improve results and overall human development, with potential relevance to all areas of human activity (NASEM 2019 ).

Implementing convergence principles in several areas of multidisciplinary research, education, biomedicine, and production, to be discussed later in this paper will bring immediate returns that are low-hanging fruit.

This paper outlines the basic concepts for convergence science (underlying theories, principles, and methods of convergence) and illustrates its implementation in key societal activities, with a focus on nanoscale-inspired converging technologies. This is explained from the perspective of evolving neural-like network describing most complex systems. This paper makes the case that convergence, as defined here, is a key transformative approach to improve societal outcomes that is expected only to increase in importance as societal interactions grow and convergence methods improve.

Earlier studies on science and technology convergence

It is well-known that “natural interdependence” has been prevalent in native Indian culture in North America. Unity of nature and society was at the core of the Renaissance ideas in Europe in the fifteenth century. Earlier signs of convergence concepts may be identified in China and India traditions. At the end of the twentieth century, “unifying knowledge” leading to a holistic approach has been advanced in several academic circles at Harvard University (Wilson 1999 ) and technology-driven projects (Kurzweil 1999 ).

The report on “Converging technologies for improving human performance: Nanotechnology, Biotechnology, Information Technology and Cognitive Science” (Roco and Bainbridge 2003 ) was followed by two complementary books on coevolution of human potential and converging technologies (Roco and Montemagno 2004 ) and managing nano-bio-info-cogno innovations (Bainbridge and Roco 2006a ). The 2003 report aimed at visionary targets to 20 to 50 years into the future.

An international benchmarking survey in over 30 countries on decision-making and problem-solving has shown that knowledge, technology, and society convergence are prevalent, even if not always explicitly recognized and methodically applied (Roco et al. 2013 ). Seventy-five case studies on the application of convergence to advance science and engineering have been illustrated in a handbook (Bainbridge and Roco 2016a ). Relatively recent reports on convergence as applied to various areas of relevance (such as health, research and education centers, and culture) are shown in Fig.  2 (Roco et al. 2013 ; NASEM 2014 ; MIT Press 2016 ; Bainbridge and Roco 2016a ; NASEM 2017 , 2019 ).

Key convergence reports published between 2013 and 2019

The National Academies of Science, Engineering, and Medicine (NASEM 2014 ) report marked the broader acceptance by the science and technology (S&T) community of the convergence approach. After 2016, NSF implemented this approach in about half of the new program announcements, with the term “convergence” being in either the project title or abstract. After 2017, convergence became a priority in The Academies (NAS, NAE, NIM), as highlighted in the report “Fostering the Culture of Convergence” (NASEM 2019 ).

Diverse international communities aim at specific convergence approaches in reaching their goals of satisfying the needs and aspirations of people in society. The United Nations, Organization for Economic Co-operation and Development (OECD), G7, various Academies, and other organizations have created such frameworks for reaching visions on sustainable human and societal development (e.g., United Nations 2019 ; NAE 2008 ).

Key underlying theories

Convergence has ten key underlying theories, outlined below (Fig.  3 ) (Bainbridge and Roco 2016b ). The first three theories—unity of nature, human interaction ecosystem, and systems adaptive complexity—are essential for convergence systems. The remaining theories provide the context for convergence.

Convergence is realized in conjunction with ten interconnected theories that are applicable to systems in either nature, knowledge, technology, or society

The unity of nature theory

Since antiquity, people have explored whether a unified set of principles and corresponding coherent set of laws could explain world events. In the scientific realm, mathematics, fractals, and frequency distributions functions of events in physics, evolutionary concepts from biology to social sciences, and more recently “neural networks” and “universal scaling laws” (West 2017 ; Danielmeyer and Martinetz  2015 ) representations have strengthened the support for this theory. Unifying concepts and holistic perspectives, such as the integral philosophy of creative transformation (Tanaka 2018 ), have generated a theoretical foundation for applying convergence to societal systems. In another example, nanotechnology provides unifying structures, phenomena, processes, and methods across disciplines for both the material and biological worlds (Roco et al. 2000 ).

The human interaction ecosystem theory

All material, biological, and societal systems have natural tendencies to interact at their interfaces, assemble, and act and evolve collectively. Their interdependence affects their evolution and long-term transformation. Hierarchical, self-regulating large systems seem to have developed as a result (Lovelock and Margulis 1974 ). This theory provides a foundation for the system-based strategies in convergence. For illustration, a cell’s evolution is determined by its interactions with other cells in the respective tissue, organ, and overall living system. A human group’s effectiveness is affected by the connectivity between its individual members across diverse backgrounds technical expertise and moral beliefs.

The systems adaptive complexity theory

Most natural and human systems are large and heterogeneous, and they may be described by nonlinear interaction networks and hierarchical architectures that evolve under external constrains at various spatial and temporal scales. They often reach emergent behavior. Such complex systems may survive through adaption and a natural selection process akin to biological evolution (Levin 2005 ). Understanding such systems is limited if using disconnected disciplinary approaches. Full system understanding and transformations may require convergence of science and technology. For example, changing an internal interaction mechanism or the type of links between nodes in a neural-like network may determine changes in the overall system properties and functions.

The economic growth theory

Modern society is prosperous enough to afford research and development projects that ensure that growth continues. Faster economic growth is made possible by concurrence of knowledge areas and investment efforts to introduce new technologies and products. This suggests the possibility of funding coordinated societal efforts to realize a compelling goal. For instance, significant financial efforts worldwide have sustained development of the semiconductor industry following the Moore’s Law, and NSF funding of more than one billion dollars led to the detection of gravitational waves in only several decades after the initial decision, both allowing further progress in society.

The cluster specialization network theory

The dynamics of teams or communities change as the number of their members increase, and the same is true for the proliferation of subdisciplines that must cooperate with each other (Massey 2002 ). The theorized effects are enhanced by convergence processes of smaller groups. The results from many specialized networks within a system are generally superior to that from larger groups or individuals in the same system (Galesic et al. 2018 ). This underlines the importance of suitable clustering structuring of a convergence system to improve outcomes. For example, structuring of materials into nanoscale clusters significantly change the properties of those materials.

The reverse salient drawback theory

If science and technology advance all along the front, except for a stall in one sector, that is, a reverse salient, the histories of the electric power and appliance industries (Hughes 1983 ) have shown that the reverse salient is a critical drawback for the field. If disciplines of science and technology are advancing without much convergence between them, some areas between disciplines (“salients”) will fail to advance, and the overall field will suffer. This theory underlines the importance of coherent development of disciplines and fields of relevance. For example, when safety or ethical issues are neglected, all other technical achievements may lose their recognition in an emerging technology.

The shared fundamental principles theory

This theory postulates that phenomena and processes have essential laws and fundamental principles that may cross various domains of knowledge and applications. It has relevance to the higher-level multidomain languages needed in convergence. For example, concepts from one field of science and technology can be applied to other fields, and data and methods of investigation and transformation may be integrated over larger knowledge and application domains.

The progress asymptote theory

This theory postulates that there exist natural limits to what can be discovered by science and created by engineering. This is important in setting the vision and goals of convergent processes. If indeed we are approaching the natural limits of science and technology in a specific field, then the last few advances may require unusually great investment not only of money but also of diversity of technical expertise in that field. An example is the increase expertise and investment needed to realize semiconductors with nanoscale features close to molecular and atomic levels.

The exogenous revolution theory

Science and engineering are societal institutions, and a radical transformation elsewhere in human institutions can trigger transformations in technical fields. Convergence processes among initially distinct domains become important. Societal shifts, such as economic changes favoring growth in a new industry, or unexpected developments in an adjacent field can break the stasis into which one discipline has frozen, thus liberating it to achieve new progress through an unexpected convergence from outside forces. For illustration, the nanotechnology and nano-bio-info-cogno technology convergences have reached recognition and societal support in the past 15 to 20 years and led to significant progress in science, medicine, electronics, environment, energy, space, and other areas.

The response to social problems theory

Science and technology are occasionally enlisted in a public response to an acute social problem, such as war, epidemic disease, or economic depression, and each problem may require a specific new partnership among disciplines that had not already converged. For instance, it is easy to think of convergent examples from the Second World War that contributed to subsequent peaceful technologies, such as civilian nuclear power and rockets to launch satellites. A more recent example is the coordinated response of science (e.g., virology and structural biology/chemistry, virus transmission models), engineering (e.g., vaccine biomanufacturing and environmental engineering of virus transmission by contact and aerosols), and social and behavioral sciences (e.g. implementation of social distancing measures, mask coverings, and vaccine acceptance) to address and control the Covid-19 pandemic.

Principles and methods to facilitate convergence

We have identified seven principles guiding convergence of knowledge, technology, and society (Roco 2016 ), as listed in Fig.  4 . They are applicable to a general case of systems that can be modeled as neural-like networks. Each principle leads to corresponding methods for facilitating convergence.

Principles to facilitate convergence

Holistic view (Fig.  5 ): exploiting the interdependence and unity in nature and society

The behavior of a system is a function of its components and interactions between those components. Identifying the holistic characteristics for the respective system including its essential and unifying features and the systemic interdependencies (D’Agostino and Scala 2016 ) is a challenge. This can be facilitated by system science, team science, and interpersonal and intrapersonal education. Convergence methods associated with this principle include integrating originally distinct information systems and changing local interactions and inter-domain connectivity characteristics to change the system outcomes. A holistic view of human activity ecosystem is given in Fig. 5 . Each converge platform (foundational S&T fields, Earth-scale, human-scale and societal-scale) is characterized by a set of concepts, group of participants, and specific investigative tools (Roco and Bainbridge 2013 ).

Holistic view of human activity ecosystem (modified after Roco and Bainbridge 2013 )

For illustration, nanomanufacturing enterprise changes from vertical and concentrated production to a more distributed and specialized enterprise because of changes made in local interactions, node characteristics, and improved connectivity (Roco et al. 2013 ). In another example, advancing “teamwork” leads to increased interactions and group efficiency in an ecosystem (NASEM 2015 ). One way to facilitate information exchange for cross-field interactions is creating a “general-purpose database” or an “open knowledge network” for many types of information, ideas, and applications (Roco et al. 2013 ; NSF 2019 ).

Common goal (Fig.  6 ): using vision-inspired basic research and innovation to address common system challenges

Identifying and reaching visionary goals beyond the known concepts and applications (“New use” in Fig. 6 ) is a main objective. Convergence methods associated with this principle include forecasting and scenario development and anticipatory measures for preparing people, tools, organizations, and infrastructure for the future technologies and relationships. A recommended approach is reverse-mapping and planning, to work backward from the vision to investigate the intermediate research steps and approaches. Sufficient time to imagine and define the vision needs to be dedicated before working a solution.

Vision-inspired basic research and inventions are essential to address system challenges: The fifth domain “Vision-inspired Basic Research” was added to the initial quadrangle Stokes diagram (modified after Roco and Bainbridge 2013 )

For illustration, the National Nanotechnology Initiative (NNI, www.nano.gov ) was proposed based on a 20–30-year vision of systematic control of matter at nanoscale for societal benefits (Roco et al. 2000 ; Roco 2011 ). The core concept was formulated in 1995–1996, the supporting technical studies were completed in 1997–2000, and the NNI announcement by President Clinton was made in January 2000. The NNI has continued for 20 years leading to research programs with cumulative research funding of about $29 billion by 2020. The global nanotechnology revenues of products where nanotechnology is the key competitive factor have been estimated to reach about $3 trillion in 2020, of which about 1/4 in the USA (Roco 2018 ). New areas of research and engineering such as metamaterials and plasmonics have emerged, and “new uses” appear in emerging technologies such as molecular manufacturing and production platforms for smart phones.

In another example, the Grant Opportunities for Academic Liaison with Industry (GOALI) concept proposed at NSF and extended to other organizations in the USA and abroad has the vision of advancing various collaborative models of participation of industry in long-term basic research performed by academic organizations. The models based on mutual interest principle expand from students and faculty internships in industry to full industry participation in joint research (Roco and Senich 1999 ). The concept was proposed in 1991, followed by a study on major engineering platforms in 1992–1993, and the first GOALI program announcement in 1994. Its impact has continued for 25 years, with numerous projects in various programs such as GOALI research project partnerships, Innovation Corps, and Intern.

Evolution pattern (Fig.  7 ): the typical convergence–divergence evolution cycle of natural or human processes is dominated by the innovation cross-domains-time spiral

The path of this spiral passes through the various domains of the system during successive time intervals while advancing toward a goal. The spiral path takes a shape that is determined by the internal mechanisms and external environment drivers.

The spiral process of convergence (“confluence of knowledge” and “integration”) and divergence (“innovation” and “spin-off”) in S&T: under the effects of science push, technology pull, and S&T and societal context

There are four phases of a typical convergence approach:

Convergence–confluence phase : Confluence and assembling of knowledge, tools, domains, and modes of thinking are driven by a set of unifying concepts for reaching a common goal. The confluence may be across the domains of activity (disciplines, topics, economy sectors), participants involved (team interaction, integrated education, levels of organization), length scales (across domains), and along time (for evolutionary processes).

Convergence–integration phase : To form new frameworks, paradigms or systems that allow people to answer questions, resolve problems, and build things that isolated capabilities cannot. The process of deep integration leads to the new system behavior as compared with its components. The outcomes are creating or changing a system able to address the respective common goals, satisfying nature constrains, or respecting human values. For example, the use of three-dimensional printing and control of nanoscale interfaces leads to a new medical treatment system for tissue reconstruction.

Divergence–innovation phase : From where novel pathways, opportunities and frontiers diverge (expand, branch-out) for new problem-solving and applications. This divergence stage may lead to expansion in knowledge, innovation, competencies, technologies, and applications. For example, after the basic logic unit CMOS for integrated electronic circuits were created, four qualitative R&D branches expanded around 2000: continuing Moore’s law based on miniaturization; “More Than Moore” electronic elements to include in other existing technologies; “More Moore” to extend CMOS technologies using nanoscale phenomena and devices; and “Beyond CMOS” to create logic and memory elements beyond Moore’s law as well as new architecture and multi-technical concept integrated systems.

Divergence–spin-off phase : The initial outcomes of innovation create opportunities for spin-off development to new areas not planned in the initial phases and create seeds for new convergence-diverge cycles. For example, nanotechnology development has expanded into more than twenty spin-off S&T fields, from synthetic biology to quantum systems. Furthermore, foundational nanoscale knowledge, tools and products enable quantum information, AI systems, advanced wireless, advanced manufacturing, nano-biotechnology, nano-medicine, energy, water, food and environmental sustainability. 

An illustration of the evolution pattern for S&T is shown in Fig. 7 . The push of knowledge and technology that is dominant in the convergence phases of the process is combined with application and societal pull that is dominant in the divergence phases (Roco 2016 ), as well as integrated with other “lateral” and “time interval” domains. The convergence phases (“confluence” and “integration” in Fig. 7 ) lead to the creation of a new set of tools, framework, and/or ecosystem able to address the shared S&T goals. The divergence phases (“innovation spiral” and “spin-off” in Fig. 7 ) lead to emerging S&T solutions, qualifications, capabilities, and applications.

Methods associated with this convergence principle are supporting the respective four phases of the convergence–divergence process such as creativity, system integration, multiple outcomes from the innovation spiral path, and spin-off to unexpected outcomes. The challenge is to optimize the overall evolution pattern for the spiral path to reach the desired outcome most efficiently.

We have established the innovation index in a convergence process , which is determined by the evolution pattern and can be used for process optimization (Roco et al. 2013 ):

is the potential increase of outcomes (innovation index describing augmentation of the effects of convergence or convergence intensity).

is the timescale for the convergence–divergence cycle (proportional with the time needed for information exchange in the system).

is the size of the convergence domain from where information is collected (the domain that is crossed by the innovation spiral; or the number of disciplines or application areas intersected by the discovery and innovation spiral).

is the outcome ratio between the output and input; the ratio between outcome (O) and time (T) characterizes the divergence angle of the process (diffusion coefficient).

is the coefficient of proportionality (a function of convergence domain S and external context E).

Several cases of (1) are:

The “Metcalf’s law” (the value of a network scales is proportional to the square of the number of nodes ( I  ~  S 2 ) in network; Shapiro and Varian 1999 )

The “Moore’s law” in semiconductor industry (the proportionality with the ( I  ~  O / TT) agrees with the exponential growth of technological developments)

The rate of technology diffusion ( I  ~ 1 / T )

Convergence accelerators for innovation ( I  ~ 1 / T 3 ) (NSF 2020 )

Formula of the innovation index process (1) underlines the importance of reducing the time of convergence for improved outcomes. Several models for “convergence accelerators” have been established in industry (Intel, SRC, others) and government programs (such as NSF and AFOSR in the USA).

Events from the upstream and downstream of an innovation process also affect a convergence–diverge innovation cycle. For example, connecting core research programs to upstream preparatory work (such as Germination program at NSF) and facilitating downstream connections to users (such as I-Corps program at NSF) can enhance the research and education projects and their impact.

An illustration of the convergence–divergence evolution cycle is its application to the development of nanotechnology in the USA coordinated by the National Nanotechnology Initiative (Roco and Bainbridge 2013 ).

System-centric actions (Fig.  8 ): making deductive system-logic decisions

This principle implies taking local decisions by considering the entire system and its evolution. This approach to problem-solving in complex hierarchical systems combines the top-down system vision with bottom-up research input, as well as with lateral and time evolution effects in decision-making.

System-logic deduction in learning, decision-making, and problem-solving. Results are better if the systems are larger, and information circulation across the systems is faster

An illustration of this principle is creating hierarchical decision-making systems for in R&D funding programs for nanotechnology regulatory aspects. Governance applies to four hierarchical levels of governance (Roco 2008 ): (a) adapting the existing regulation and organizations; (b) establishing new programs, regulations, and organizations; (c) building capacity for addressing those issues in national polices and institutions; and (d) advancing international agreements and partnerships.

Cross-domain languages (Fig.  9 ): creating and applying higher-level cross-domain languages (concepts, principles, and methods)

This principle facilitates the transfer of knowledge, synergism, and new solutions. It includes using universal languages such as mathematical abstraction, music, general-purpose databases, and general system architectures. It also includes identifying essential system characteristics through “simplicity” for efficient and timely solutions. Creating and sharing large multidomain databases and “trading zones” between areas of research and education in distinct areas facilitate developing multidisciplinary fields. Promoting technology integrators and benchmarking to facilitate introduction of emerging technologies in multiple areas are useful in developing multi-technology fields.

Schematic for robustness-speed behavior of systems as a function of their architectures

This principle has multifaceted dimensions. For example, Doyle and Csete ( 2011 ) have identified cross-domain unifying neural-like network diffusion patterns in many distinct systems and correlated the robustness-speed behavior relationship for those systems (Fig. 9 ). There is a similar resilience-efficiency relationship in the behavior of a system. A major lesson from Covid-19 pandemic in 2020 is that science and economics have overemphasized efficiency by short term optimization of componenets and left entire society to function with less resilience than needed in a longer term in a crisis or other low probability event. In another example, Jolliffe ( 2013 ) developed an algorithm designed to visualize complex databases to uncover information that can reveal the global structure of the data under consideration while preserving local characteristics. The algorithm, Intensive Principal Component Analysis, has general applicability in fields such as astronomy, physics, and biology. In a separate project, Sia et al. ( 2019 ) proposed a community identification algorithm in complex networks based on interactions among entities. The approach also can discover hierarchical structures of the respective complex network. Universal laws for system architectures, including correlations and scaling laws have been proposed by West ( 2017 ). A universal theory for natural patterns has been advanced by Passotand and Newell ( 1994 ). Fortunato et al. ( 2018 ) have suggested that science may be an expanding and evolving network of ideas, communities, and publications. Searches can be made for universal and domain-specific laws underlying the structure and dynamics of science. Novelty is unconventional assembling of elements forming emerging ideas.

Multi-tasking (Fig.  10 ): to address concurrent cause-and-effect pathways in a large system

It leads to coevolution of paradigms for reaching a system goal, which may include multiple angles of observation, pathways, algorithms, lines of actions and modeling/simulation methods, and overall choices in multi-tasking (Prabhakaran et al. 2019 ; Rocks et al.  2019 ). Investigation of a large system requires competition of multiple-choice decision pathways and approaches (of logic steps, timescales, small parameters). Selection of investigative methods may lead to different conclusions. Knowledge mapping, network visualization, and fractal analysis are tools to identify the relevant cause-and-effect system patterns. A key concern is optimization and stability of the system functions. The challenge is to realize coherent management of various nonlinear and interdependent multi-algorithms for best system outcomes. Actions may include co-design, co-production, and co-management.

Concurrent pathways with multi-tasking enable system multi-functions: (i) Multiple cause-effect pathways. It leads to co-current paradigms, which co-evolve and compete; (ii) e.g., water distribution network with multiple sources and sinks (concept Rocks et al. 2019 )

The limits of multi-tasking in physical, biological, and distribution networks, as well as in other complex systems, can be estimated (Rocks et al. 2019 ). This also appears to be true in a research and development endeavor. Smaller groups disrupt, and larger groups with increased multi-tasking develop (Wu et al. 2019 ). Physical examples of multi-tasking are the distribution networks of water (Fig.  10 ii), oil, or electricity that may involve multiple supply and consumer nodes. Biological networks have an even greater level of multi-tasking.

Added-value (Fig.  11 ): synergistic confluence of resources determines pronounced and accelerated system changes

In a typical situation, this yields the S-curve of increase of outcomes versus investments. Convergence is about changing the system (generating new system functions, changing the spatial, temporal and structure of the underlying neural-like network) and increasing the efficiency in the modified system. A specific innovation can produce a pattern of change that starts slowly as early adopters in the social system implement novelties, then accelerates as they influence others to follow their example, and then slows again as the innovation approaches full adoption. The challenge is proper concurrence of resource and staggering transformative actions.

Confluence of resources leading to system changes: illustration of the S-curve estimated for two emerging S&T fields (Ex: GAO 2014 )

Concurrence of scientific activities for a compelling goal is driven by both the internal scientific progress and external collaborations and requirements. Convergence of knowledge and technology realizes the benefits better if it is executed on an accelerating path (see (1) where the index of innovation I  ~ 1 / T 3 ). This principle is at the origin of the Convergence Accelerators program (NSF 2019 ).

In another illustration, the NNI simultaneously has invested in a large spectrum of research programs, infrastructure, education and training, environmental and health issues, ethical and legal issues, and international collaborations to reach its S&T targets.

The seven convergence principles have a dynamic collective action. They corroborate in reaching a common goal in a complex system. Each principle leads to various methods to facilitate convergence that has different relevance in various applications (Roco 2016 ).

Three hierarchical stages of science and technology convergence are underway

The emerging convergence S&T system at the beginning of the twenty-first century is based on five elemental building blocks: atoms and qubits, information bits, logic steps, genes, and neurons (Figs.  12 and 13 ). Three hierarchical S&T platforms have resulted from convergence of disciplines and technologies originating from these elemental building blocks (Fig.  14 ), and they have brought significant progress in economy and society:

General-purpose S&T fields : (i) Nanotechnology integrating from atoms and qubits, (ii) IT (digital technology) integrating from bits of information, and (iii) AI integrating logic steps.

Convergence foundational S&T system (Nano-Bio-Info-Cogno-AI, in brief NBICA) integrated from their elemental building blocks (atom and qubit-gene-bit-neuron-logic step, in brief a-q-g-b-n-l) (Fig.  13 ). A foundational S&T field is built up by hierarchical integration from a typical elemental building block, and the convergence foundational S&T system is built by hierarchical and cross-field integration of various building blocks.

Convergence of knowledge and technology solutions for global society . The combined tools enabled in various human activity platforms (Fig. 5 ) are integrated to address converging solutions for societal benefit and human development, driven by societal values and needs.

Elemental building blocks of the convergence S&T system: atoms and qubits, genes, bits, neurons, and logic steps

NBICA convergence S&T system : foundational and emerging S&T fields (nanoscale, bio, information, cognitive, and AI) built from the five elemental building blocks

Three hierarchical S&T platforms resulted from convergence: (I) General-purpose fields (Nano, IT, and AI), (II) convergence foundational system (NBICA), (III) convergence for global society (CKTS). The S&T evolves following a spiral path in time crossing these three platforms

General-purpose science and technology fields

General-purpose S&T fields are based on their respective elemental building blocks: atoms and qubits for the material world, bits of information for the information and communication world, and logic steps for the decision-making and artificial intelligence world.

a. Nanotechnology —a term used for “nanoscale science, engineering, and technology”—integrates disciplines and knowledge of matter from the atomic and qubit level up to macroscale for all materials, devices, and systems. Similar nanostructures, nanoscale phenomena, and processes are investigated and applied in a variety of fields of relevance, from advanced materials and nanoelectronics to biotechnology and medicine. Nanotechnology currently continues its quasi-exponential growth by advancing its scientific depth, science-to-technology transition in areas such as nanoelectronics and nanomedicine, expansion to new areas such as in agriculture and constructions, and establishing new frontiers such as in nanophotonics and metamaterials. The National Nanotechnology Initiative (NNI) was proposed in the USA to take advantage of the new opportunities (Roco et al. 2000 ; Roco 2018 ). Nanoscale processes and phenomena also are important to understand nature.

Nanotechnology development has been guided by the convergence principles as summarized in Fig.  15 .

Nanotechnology development has been guided by convergence principles

b. Information technology (IT) integrates digital information, computer science, and data management, having as foundational element “a bit of information.”

Digital society is an outgrowth of capabilities created by IT tools and has immediate relevance to the digital economy (Ansip 2016 ), digital manufacturing, cyber-physical-social systems, large databases, and Internet of Things. Digital relationships and networking are expected to change the ecosystems for production, learning, trading, and other areas. Digital convergence facilitates dissemination and replication of results, establishment of ubiquitous digital platforms, and multi-contribution patents and products. One facet of it is digital government (Fountain 2016 ), which refers to the use of information and communication technologies in governance. It encompasses citizen participation and engagement. Digital convergence within government has a focus on coordination and collaboration across boundaries to create “virtual agencies.”

c. Artificial intelligence (AI) is evolving toward a general-purpose approach in science, technology, and society, to enable smart systems “to logically act like a human.” It uses “logic steps” as the foundational elements. A more inclusive name of the field is “system AI” because both software and properly adapted hardware of a system need to be address.

The defining characteristics of AI are still evolving. AI was initially associated with pattern recognition and building models (symbolic, probabilistic, causal, hierarchical, artificial neural network) for the world. More recently, we are looking at building AI in a similar manner as a person grows from childhood. This includes earlier childhood contextual analysis, common sense knowledge and architecture, learning to learn, generalizing from an example, iterations in an artificial neural network thought engine, and going from vision to language.

System AI is the capability of machines to perform tasks and solve problems that require perception, reasoning, and logic, using information about the world and addressing competing objectives and constraints in the presence of uncertainty. AI systems may have the ability to learn, communicate, and act in the physical world; work collaboratively with humans; exhibit flexibility, resourcefulness, creativity, real-time responsiveness, and long-term adaptive capacity and resilience; use a variety of representation or reasoning approaches; and demonstrate competence in complex environments and social contexts.

The recent advances in AI and its emerging uses in various knowledge and technology fields have been enabled by improved logic algorithms, machine learning, increased computing power and availability of large data sets, improving model-free approaches, natural language processing, and understanding of self-organizing neural-like networks. Furthermore, significant progress in designing and creating new hardware suitable for AI, growth in automation and robotics, efficient handling of large complex systems, and new design and manufacturing methods in education are highlighting the role of engineering. The National Artificial Intelligence Research and Development Strategic Plan (NSTC 2019 ) provides a framework for the visioning activities and strategic objectives of investments in AI research in the USA.A convergence challenge is seamless integration of such logic steps and processes into key technologies and daily life. Another challenge is sharing and including in the AI process “foundational,” moral/ethical, and “higher-level” values as they imply multiple and interdependent logic steps for which is more difficult to set rules. The goal is how to build AI to serve the human vision, instead of evaluating how technology would drive the society. Besides the general-purpose AI approach, one should consider the specifics of various areas such as using AI for “invention in the methods of invention.” AI advances convergence of other S&T fields transferring concepts between fields such as from games to robotics.

An example of potential application is creation of Intelligent Cognitive Assistants. These are systems using AI for developing smart interfaces between people, people and machines, and people and environment (see more details later in the paper).

NBICA (nano-bio-info-cognitive-AI), the converging foundational S&T system

NBICA integrates five emerging and foundational S&T fields from their basic elements: atoms and qubits for nanotechnology, genes for modern biology, bits for information-networking-digitization, neurons/synapses for cognition-neurology, and logic steps for AI. The resulting technologies use similar system architectures, dynamic networking concepts, and scaling laws, driven by the convergence principles (Fig.  16 ) (Roco and Bainbridge 2003 , 2013 ). Convergence yields new science and technology platforms that are different from just summing the components.

Convergence principles applied to the NBICA foundational S&T system

NBICA convergence shares abstractions from information technology and system theory, as well as solutions that are hierarchically integrated across technology domains and length/timescales. NBICA already has made inroads in areas such as nanoelectronics; synthetic biology; biomedical research at confluence of biology, medicine, physical sciences, and engineering; and in bio-nano-informatics.

In response to international interest, OECD has created a Working Party on Biotechnology, Nanotechnology, and Converging Technologies (BNCT) to address progress and organizations serving converging technologies. Other international policy efforts building bridges between emerging converging technologies are the Global Science Forum (GSF) of OECD, the Group of Senior Officials (GSO) of G7 Science Ministers, and Global Research Council (GRC) formed by heads of national research organizations.

A schematic showing the NBICA system and its expansion is shown in Fig. 17 . The research and education grants related to NBICA are about 6% in all NSF in 2019–2020 and about 50% in NNI projects (~ 14%). Nano-bio-science and engineering awards have the largest contribution, and AI-nano-info-related ones are the fastest growing in the 2019–2020 interval.

Emergence and divergence of the foundational NBICA system

The industries of the future advanced by the US National Science and Technology Council in 2020 are included in Fig.  18 , including Systems AI, Quantum Information Science, 5G Advanced Wireless, Advanced Manufacturing, Brain research, and Bioeconomy. IT and nanotechnology are general-purpose technologies providing innovative solutions and enabling the industries of the future.

Converging foundational NBICA system is at the origin of emerging S&T initiatives in the USA

Converging knowledge and technology solutions for global society

The seven convergence principles have been applied to the key platforms of societal activity—NBICA tools, human-scale, Earth-scale, societal-scale, and system behavior (Fig. 5 ) whose actions are motivated by the need to societal values and needs (Fig.  19 ). The first meeting on Converging Technologies for “Improving Human Performance: Nano-Bio-Information-Cognitive Technologies” was held at NSF in 2001 (Roco and Bainbridge 2003 ). An overview of the main topics and their benchmarking in over thirty countries has been presented in the report “Convergence of Knowledge, Technology and Society” (Roco et al. 2013 ). AI has become more relevant to NBICA after 2015 as “systems AI.” NBICA is driven by unifying concepts for common core goals such as learning, productivity, and aging. An integrated vision for human development and the future society to be aimed by NBICA system have been proposed in the United Nations Millennium Development Goals reports.

US global society-oriented initiatives are addressing the main human activity platforms (NBICA, human-scale, Earth-scale, societal-scale, and convergence governance)

Topical applications of convergence

Convergence is increasingly accepted as a method for future innovation and facilitating societal development in all fields, from topical to holistic (see convergence culture discussed by NASEM 2019 , Murray and Calabrese 2019 ).

Convergence principles in nature

Everything is connected in nature. Astronomy, geology, life ecosystems, and interactions with people describe facets of it. Patterns resulting from interactions and evolutions have turbulent-like behavior with randomness at small scales and coherence at large scales. They typically have convergent–divergent evolution cycles, with spiral domain-time patterns. Figure 20 shows how convergence principles facilitate comprehension of nature.

Convergence principles applied to understanding nature

Let us illustrate how convergence principles function in nature:

Holistic : Longitudinal (evolutionary) connections have been essential in nature, as it has been in the bacterial “tree of life.”

Common goals/trends : Formation of chemical elements and high-level organization material structures and biosystems has been a general trend. Population growth affects global trends such as global warming and decrease biodiversity.

Evolution patterns : Natural convergent–divergent cycle (e.g., cell growth–division cycle) and the space–time spiral structures (e.g., tornado pattern, constellation pattern) are typical in nature.

Unifying actions : Smaller scale Earth events are affected by the global natural context, leading to similar patterns, such as fractals exemplified by a “fingerprint” in nature that holds across scales and fields (e.g., river drainage network, a network on a leaf, and lung and blood networks).

Cross-domain: Physical and biological laws are crossing water, air, soil environments, with same diffusion, convection, and radiation laws for temperature, mass, and contaminants.

Multiple tasking : Multiple cause-and-effect pathways coexist in nature. Complex natural ecosystems are the result of the confluence of various sources and sink events, pathways, and bifurcations caused by small perturbations. Multi-tasking is needed to address various dimensions of a natural ecosystem.

Added-value : Concurrence of natural and human-made events leads to significant ecosystem changes. For example, simultaneous, multiple disasters such as earthquakes, tsunami, and storms cause geographical/geological and infrastructure modifications.

Production processes

Convergence has the potential to bring major advances in production processes including manufacturing and services. Science and technology are increasingly integrated with emerging high-tech production. Convergence leads to introduction of NBICA manufacturing cells and modular fabrication. Exchanges of models between various production domains create “trading zones” in manufacturing. Digitization and cloud manufacturing are growing with the Internet of Things. Converging “supply chains,” from concept to internet, production, and use, leads to “cyber-physical-social” manufacturing with cloud “mass customization” distributed model.

Convergence changes the processes in each manufacturing unit and in the network as illustrated by IT equipment convergence and sensors-computer-medical devices convergence. Interdependence in production, crowd funding, and overall convergence change the system itself. Convergence in manufacturing may lead to a bottom-up strategy to enable a self-propagating, profit-driven evolution of the software and hardware infrastructure needed to realize the “factories of the future.” Individuals and communities will be empowered by distributed technologies. Integration required in production provides a good feedback for adopting convergence.

Sustainability in manufacturing, the life-cycle approach, and circular economy are fast growing paradigms. Convergence will change nano-EHS (environmental, health, and safety) and ethical-legal-societal-governance needs and capabilities by the introduction of concurrent processes, use of common language, and especially by emphasizing the societal context.

Biomedicine

Convergence catalyzes new research directions and guides research priorities in biomedicine. Convergence of life sciences, physical sciences, and engineering have been emphasized in the last decade in order to improve understanding, introduce new biomedical solutions using the DNA and cellular levels, advance personalized medicine, and overall create the environment for more breakthroughs in biomedicine (NRC 2009 ; MIT 2016 ; Sharp and Langer 2011 ). According to NASEM ( 2014 ), convergence is an approach to problem-solving that cuts across disciplinary boundaries from health sciences, physical, math, and computational sciences, engineering disciplines, and beyond to form a comprehensive synthetic framework for tackling scientific and societal challenges that exist at the interfaces of multiple fields. Nanotechnology alone has opened significant innovations in areas such as diagnostics (imaging diagnostics, blood analysis, saliva analysis); therapeutics (targeting drug delivery, targeted cancer detection and therapy nanostructured implantable materials: bones, scaffolds); and regenerative medicine (tissue engineering, gene therapy for healthcare, stem cells, single cell conditioning).

Implementing R&D

Convergence offers a new universe of discovery and innovation in research through specific principles and methods. Vision-inspired and system view planning and implementation of research use forecasting and various processes for setting grand challenges (Bainbridge and Roco 2006a , b ; Roco et al. 2013 ). Convergence includes cross-disciplinary, cross-sector, cross-cultural, and international sharing of organizations and projects. It may require combining multi-topic databases and changing the researchers and faculty recognition system.

Convergence has been embraced at NSF after 2017: “Convergence is the deep integration of knowledge, techniques, and expertise to form new and expanded frameworks for addressing compelling scientific and societal challenges and opportunities.” Examples of ideas and programs are “Future of Work at the Human-Technology Frontier,” “Big Idea: Growing Convergent Research,” and “Convergence Accelerators.” An example of education and research center is the “National Convergence Technology Center” ( www.connectedtech.org ) that leads the Convergence College Network (CCN), a group of 50+ community colleges and universities from across the country that shares resources and best practices at both regularly scheduled meetings and special one-off webinars. Convergence opportunities in education and research were surveyed by Herr et al. ( 2019 ).

Forming efficient science and engineering research ecosystems may require changing interactions between students, faculty, and administration (e.g., student-driven research in collaborations with faculty), using system and team science or employing bottom-up incentives for convergence in degree accreditation, to name a few. Changing the culture is an ultimate goal that may include recognition and respect of other disciplines, leaving the comfort zone, facilitating and enabling meeting places, and networking at institutional and national levels.

Convergence already has contributed to developing the NBICA unifying S&T system, methods for identifying new fields on the map of emerging fields (extending, interpolating, and re-combining of fields shown in Fig.  17 ), and improved governance of S&T.

Personal behavior

One may argue that effective personal behavior also may be guided by general convergence principles. Figure 21 shows the correspondence between the convergence principles and the “habits of highly-effective people” behavior as described by Covey ( 2003 ) and explained in Eyre et al. ( 2017 ).

Convergence principles applied to individual behavior

Personalized learning

Creating an improved ecosystem for personalized learning includes several convergence-driven trends. One is establishing a universal (multidomain, general-purpose) language and database library that makes connections between concepts and methods among various fields. Use of intelligent cognitive assistants, virtual reality, and other convergence-based methods to teach individually is another trend. One needs to integrate cognitive psychology for learning, motivation, and emotional intelligence of individual and group in personalized learning process.

Improve team science outcome

The convergence approach facilitates team science by enhancing group interactions, decisions and their efficiency as applied to knowledge, technology, or society systems (Cooke and Hilton 2015 ; NASEM 2015 ). The implementation of convergence principles to team science is illustrated in Fig.  22 .

Convergence principles applied to improving team science (collective behavior)

Local, national, and global governance

Governance refers to the collective capacity for achieving socially desired community benefits under complex and changing conditions. This capacity is most robust to the extent that it is distributed across multiple stakeholder groups, emphasizes both innovation and responsibility, and consists of multiple instruments, both voluntary (organic) and enforced (hierarchical) (Roco et al. 2013 ). The convergence governance process is different from top-down governing as it is dominated by horizontal links and self-organization principles. Convergence in governance typically aims at changing the system to improve or expand its performance. “It must be remembered that there is nothing more difficult to plan, more doubtful of success, nor more dangerous to manage, than the creation of a new system” (Machiavelli 1513).

Convergence governance may contribute to major changes in science, technology, and society. For example, the US nanotechnology governance approach has aimed to be “transformational, responsible, and inclusive, and to allow visionary development” (Roco 2008 ). Innovative individuals in public groups (e.g., entrepreneur/inventor Elon Musk and his company SpaceX) and of public–private partnerships will increasingly push the development of new converging technologies separate from the roles of governments. New tools will emerge for participatory governance, such as games, collaborative design, and social media. Coevolution between science, technology, and societal norms and values will become increasingly evident to a larger number of actors.

Two regulatory approaches are developing in parallel for converging technologies: one is probing the extendibility of regulatory schemes (“developing the science” approach), and another is developing exploratory (soft) regulatory and governance models that work reasonably well even with insufficient knowledge for full risk assessment. Proactive convergence governance is essential for obtaining the benefits of the new technologies, limiting their negative implications, and fostering global collaboration.

A “Convergence knowledge and technology office” has been proposed (Roco et al. 2013 ) for R&D program and investment decisions to be taken by considering all the factors in a coherent and systematic way. Besides facilitating connections, that office would include tools for stimulating creativity, invention, and innovation paths, promoting longer-range connections and examining potential for the future. The Convergence Research Policy Center was established in Korea Institute of Science and Technology, South Korea, for national coordination of government decisions using convergence principles. Examples of successful governance of ecosystems are the convergence platforms for the earlier spaceflights, Silicon Valley (The Rainforest), and Semiconductor Research Corporation (SRC) and its community (Roco et al. 2013 ), to name a few. Measuring convergence in government research institutes is discussed by Bae et al. ( 2013 ) and Coh et al. ( 2019 ).

Convergence for sustainable society

A sustainable, progressing global society has many interconnected dimensions that require a convergence approach to address them holistically and effectively. These dimensions include environmental sustainability in planetary boundaries (such as keeping it clean, biodiverse, renewable) and resilience aspects (related to infrastructure, cities, and emergency response for life cycle). Sustainability also is determined by economic aspects (e.g., do “more with less,” managing resources as materials, water, energy, land, food, climate, green chemistry), social aspects (population growth and human needs, governance, enduring democracy), and the efforts for maintaining quality of life and expectations for current and future generations (Diallo and Brinker 2010 ; Diallo et al. 2013 ). To address its multiple facets, sustainable nanotechnology may make use of cross-domain databases and neural network models enabled by artificial intelligence and managed under a unified digital network. A framework for reaching sustainable society is Deep Reasoning Networks (Chen et al. 2019 ) that combines deep learning with logical and constraint reasoning for solving complex tasks using stochastic-gradient-based neural network optimization. The Computational Sustainability Network ( https://www.compsust.net/ ) has successfully implemented this approach. Figure 23 illustrates how convergence principles would apply for reaching a sustainable society.

The convergence principles applied for reaching a sustainable society

Several trends

Improving human capabilities.

The 2003 report Converging Technologies for Improving Human Performance (Roco and Bainbridge 2003 ) describes convergent approaches in a broad set of themes, including expanding human cognition and communication, improving human health and physical capabilities, enhancing group and societal outcomes, national security, and unifying science and education. The coevolution of human potential and converging new technologies is a trend with major implications for individuals, organizations, and society in the decades to come (Roco and Montemagno 2004 ).

Improving human capabilities has been a dream for centuries. At the beginning of the twenty-first century, we stand at the threshold of a New Renaissance in science and technology, based on a comprehensive understanding of the structure and behavior of matter from the nanoscale up to the most complex system yet discovered, the human brain. Rapid advances in convergent technologies have the potential to enhance both human performance and the nation’s productivity. Examples of payoffs will include improving work efficiency and learning, enhancing individual sensory and cognitive capabilities, revolutionary changes in healthcare, improving both individual and group efficiency, highly effective communication techniques including brain to brain interaction, perfecting human–machine interfaces, and ameliorating the physical and cognitive decline that is common to the aging mind. Convergence may help to break those limits in the next decades.

Intelligent cognitive assistants (ICAs)

ICAs are harnessing new machine intelligence and problem-solving capabilities to work collaboratively and enhance human cognitive and physical abilities—by assisting in working, learning, and interacting with new cyber-physical systems, transport, healthcare, and other activities (Bainbridge and Roco 2016a , b ; SRC/NSF 2016 , 2018 ). ICAs are conceived to be smart interfaces between an individual or group with other people, with the surrounding environment, and with tools and machineries (Fig. 24 ). ICAs are an outgrow of NBICA convergence, with two main roots: (a) the report on advancing the human–technology frontier in Roco and Bainbridge ( 2003 ) where one of the visionary projects for 20–30 years ahead has been “personal assistant and broker” and (b) the brain-like computing grand challenge to “Create a new type of computer that can proactively interpret and learn from data, solve unfamiliar problems using what it has learned, and operate with the energy efficiency of the human brain” (OSTP/NNI Grand Challenge, http://www.nano.gov/futurecomputing , 2015).

Schematic for Intelligent Cognitive Assistants

ICAs are at the forefront of multiple fields of research including human-centered intelligent engineered systems with cognitive capabilities, artificial intelligence, and deep learning. Their development is based on semiconductors going beyond the Moore’s law, complex cyber-physical-social modular systems, smart engineering materials, devices and systems, and large nano sensor systems. ICAs have areas of confluence with smart and autonomous machines, modular system architectures and devices wireless technologies, cognitive psychology, cognitive prosthetics, large data for decision-making and problem-solving methods, autonomous chemistry, neural-like systems, and neurotechnology. This makes ICAs a good case for convergence in the process of human–technology coevolution. The increase of human capabilities and opening of new fields of activity will be indicators of success.

Typical ICA functions are improving daily activities through human-machine collaborative work, learning machines, exploring things not possible before, and overall enhancing human abilities. Goals for ICAs include learning insights from data, solving unfamiliar problems, creating decision and action capabilities, and providing informed advice. They are at the confluence of IT-computer science, brain science, cognitive technologies, and nanotechnology.

Citizen science and innovation

Citizen science is an outgrowth of increase of general level of education, open communication, crowd sourcing, and the convergence of knowledge and technology in society that allows ordinary citizens to be partners in the progress of science, engineering, and innovation.

The term citizen science describes people who are not paid for their work and do not possess higher academic degrees but contribute to scientific progress. Examples are in the discoveries of previously unknown birds, fossils, and even galaxies. While less frequent, advances in emerging technologies are possible through projects such as Nanocrafter, “a citizen science platform for the discovery of novel nanoscale devices built out of self-assembling strands of DNA” (Barone et al. 2005 ).

The technological equivalent of citizen science would logically be called citizen innovation . A related development is open source technology (Crowston 2016 ). The Maker Movement initiated with the introduction of additive manufacturing and three-dimensional printing has received considerable government support in the US. The Maker Movement has important implications for education.

Collaboration and conflict resolution in society

Peace is one of the most complex and important systems (Donofrio 2020 ) where convergence may play a role. Through convergence, people interact and understand better, and converging technologies offer means of reaching common goals by collaboration, rather than by confrontation. By changing the balance from advantages sought by confrontation and conflict to the shared benefits that can be realized by collaboration with the convergence tools, one may advance common goals via conflict resolution or, in other words, peace building. A critical phylosophy in convergence education is succeding in reducing the disturbances created by the “human instinct of aggression” (Peters 2020 ).

This challenge for the complex dynamic human system may be met as a result of the several trends, including:

Convergence to intellectual global thinking and training , with a focus on common values, approaches, and opportunities. The wholistic approach has the potential to diminish possible conflicts between the short-term or small group efficiency actions and the longer-term optimization endeavor for the entire community. A metric for success is the progress in “cross-domain languages.”

Open deliberative observatories, interactions bridges, and networks between society groups and organizations are increasing. A metric for success is “beneficial to all people.”

People become more interactive and promote collaborative behavior and win-win approaches between individuals, groups, and organizations.

Transparent changes in the disadvantage-benefit balance from more disadvantages to more benefits by conflict resolution. The schematic in Fig. 25 suggests how the benefits derived from collaboration would grow in time with convergence in society, as compared with possible advantages derived from confrontations that are decreasing in time.

Improve decision-support tools by leveraging both human and machine intelligence to augment decision-making in individuals and organizations, aiming to create algorithms to manage potentially conflicting preferences using computational social choice, crowdsourced democracy, and crowdsourced forecasting (Joseph et al. 2019 ).

Perceived change of balance of benefits from confrontation to collaboration through convergence

Closing remarks

Convergence approach offers a general opportunity of progress in knowledge society. It opens a new universe of discovery, innovation, and applications in research, education, production, and other societal activities. It already has changed the landscape of S&T fields. This paper has presented relevant theories, principles, and methods of the emerging convergence science. The case studies outlined on this basis show the generality of the convergence approach in reaching goals in science and technology, human development, society, or understanding nature. Education and organizational and cultural changes are needed to better solve emerging problems that transcend traditional boundaries.

Convergence in manufacturing, biomedicine, and cognitive technologies appears to bring earlier societal benefits as compared with other areas. Cross-domain programs in universities and funding agencies also show earlier results. International collaboration is essential for the development of convergence science and of convergent technology platforms.

Application of the principles of convergence in nature and society has successfully advanced from facilitating general-purpose S&T fields such as nanotechnology, digital technology, and AI to enabling broad knowledge, technology innovation and cultural interactions for global societal progress. Convergence offers efficient possibilities for improving human activity outcomes beginning with personal learning and production processes to improving economic performance of an organization and addressing societal conflicts. It brings science, technology and applications closer and accelerates their integration. Convergence offers the foremost opportunity for the comprehension of nature and societal progress in the increasingly “connected world” of the so-called fourth industrial revolution.

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This manuscript was written based on professional activities of the author and was presented as an international overview of the field of convergence at the US-Africa Forum of Convergence Nanotechnology (2019).

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Roco, M.C. Principles of convergence in nature and society and their application: from nanoscale, digits, and logic steps to global progress. J Nanopart Res 22 , 321 (2020). https://doi.org/10.1007/s11051-020-05032-0

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1 Introduction

Convergence is an approach to problem solving that integrates expertise from life sciences with physical, mathematical, and computational sciences, 1 medicine, and engineering to form comprehensive synthetic frameworks that merge areas of knowledge from multiple fields to address specific challenges. Convergence builds on fundamental progress made within individual disciplines but represents a way of thinking about the process of research and the types of strategies that enable it as emerging scientific and societal challenges cut across disciplinary boundaries in these fields. The concept of convergence as represented in this report is thus meant to capture two dimensions: the convergence of the subsets of expertise necessary to address a set of research problems, and the formation of the web of partnerships involved in supporting such scientific investigations and enabling the resulting advances to be translated into new forms of innovation and new products.

Convergence represents a cultural shift for academic organizations that have been traditionally organized around discipline-based departments. The overall ecosystem needed to foster and sustain convergence draws not only on academic contributors but increasingly also on the cross-fertilization of ideas with stakeholders and partners from national laboratories, industry, clinical settings, and funding bodies, as well as insights from economic, social, and behavioral sciences. The process of convergence is applicable to basic science discovery as well as translational application. Because it is commonly focused on achieving an outcome to a challenge at the frontiers of knowledge, many convergence efforts include an entrepreneurship component that leads to the development of a surrounding web of startup companies and economic innovation.

1.1. A SCIENCE AND TECHNOLOGY REVOLUTION IS OCCURRING

During the 20th century, major breakthroughs in advancing research-based knowledge and its applications to societal problems resulted from bringing together disciplines across physical sciences and engineering. Satellite-based global positioning systems that applied physical principles, including the development of accurate atomic clocks corrected for gravitational and atmospheric effects, now underpin vehicle navigation systems and provide location data for ubiquitous mobile phone and tablet computer apps ( IOP 2009 ; Lucibella 2012 ). The combination of an image sensor such as a charge-coupled device that converts light into electrical signals, signal processing into images that can be stored and printed, and the ability to handle millions of pixels of data fueled the adoption of digital cameras, which were first marketed as consumer products in the late 1980s and early 1990s. The field of nanotechnology was built on the development of analytical technologies such as the scanning tunneling microscope as well as materials science and surface chemistry that enabled scientists to understand and control properties at the atomic scale. Today nanomaterials are found in products ranging from conductive inks for printed electronics to advanced batteries ( NNI 2014 ). In each case integrating methods and tools from physical sciences and engineering were keys to both new knowledge and product innovation.

It has been postulated that the 21st century will become the “century of biology,” enabled by the impressive progress made in understanding the molecular basis of life and in applying that knowledge in new directions ( Venter and Cohen 2004 ; Dyson 2007 ). Determination of the structure of DNA in 1953 led to the elucidation of the central dogma of biology and the development of principles relating DNA's structure to the mechanisms of reproduction and translation, providing for the first time a unifying concept of how information was transmitted within the cell and between generations. Within 20 years, the scientific community had developed the ability to not only sequence and synthesize a gene but to combine genes and pieces of genes, founding the age of biotechnology. Fifty years on, the technology to sequence, computationally compare, and interact with the complexity of the human genome, and to do all of that at relatively low cost, in turn spawned revolutions in areas ranging from genomics to bioinformatics. A critical dimension of this new century will be the further integration of life sciences into physical sciences and engineering fields, and vice versa. Making use of the wealth of information that molecular biology, genomics, and the other “omics” fields are now yielding will require contributions from multiple disciplines, moving beyond the first revolution of interdisciplinary molecular and cellular biology and the second revolution of genomics to a third revolution marked by transformative integration of life sciences, physical sciences, medicine, and engineering (Sharp and Langer 2011; Sharp et al. 2011 ) (see Figure 1-1 ).

The continuing integration of life sciences, physical sciences, medicine, and engineering represents a third revolution in life sciences, building on prior revolutions in molecular biology and genomics. SOURCE: Courtesy of Phillip A. Sharp, Institute (more...)

The process of this convergence among life and health sciences, physical sciences, and engineering along with the increasing incorporation of contributions from social and economic sciences has the potential to fundamentally impact the organization and conduct of research in the coming decades. Exploring why this process represents a promising frontier of new knowledge and what strategies can nurture it within institutional structures will constitute both an opportunity and an ongoing challenge for organizations across the research enterprise.

1.2. CONVERGENCE IS AN EXPANDED FORM OF INTERDISCIPLINARY RESEARCH

The goal of merging expertise to address complex problems is not new, and there are myriad examples in which researchers from multiple disciplines have worked together to solve problems that are beyond the scope of individual scientific areas. Most often described as an “interdisciplinary” approach, this goal has been a common feature of industrial research laboratories since the 1920s, and many research initiatives based in academic laboratories also rely on collaboration among investigators from more than one field. At the heart of the current momentum for convergence, however, is the realization that physical and biological sciences can each benefit from being more fully integrated into the intellectual milieu of the other. By working together in a coordinated and reciprocal manner, engineers might learn how diatoms create silica nanostructures in seawater at room temperature, something that humans can only accomplish at high temperatures. The production of such silica nano-structures may have wide-ranging applications in areas like novel sensors and improved batteries ( Vrieling et al. 2005 ; Khripin et al. 2011 ; Luo et al. 2013 ). On the other hand, biologists might learn from the techniques that nanoengineers are developing for surmounting physical barriers, such as the endothelial cells that line blood vessels or that comprise the blood–brain barrier ( Chrastina et al. 2011 ; Jain 2012 ; Patel et al. 2013 ; Tosi et al. 2013 ). This knowledge could lead to new targeted therapeutics delivered more efficiently in the body.

The terminology used to capture and discuss the shift in thinking required for convergence can be confusing because of varied interpretations of inter-, multi-, or transdisciplinary research. This report draws on definitions and framing concepts from the academic community that studies the organization and conduct of research (discussed in greater detail in Chapter 3 ). The key message of convergence, however, is that merging ideas, approaches, and technologies from widely diverse fields of knowledge at a high level of integration is one crucial strategy for solving complex problems and addressing complex intellectual questions underlying emerging disciplines. Of necessity, convergence requires an open and inclusive culture, and requires practitioners to move beyond a single language to being conversant across disciplines and to building a common set of concepts and metrics and a common understanding about goals.

In this way, convergence represents an expanded form of interdisciplinarity in which bodies of specialized knowledge comprise “macro” domains of research activity that together create a unified whole. When integrated effectively, these convergent macro domains offer the possibility of a new paradigm capable of generating ideas, discoveries, methodological and conceptual approaches, and tools that stimulate advances in basic research and lead to new inventions, innovations, treatment protocols, and forms and strategies of education and training. Such a comprehensive level of integration, without specifically using the term “convergence,” has been conceptualized in several recent reports ( Figure 1-2 ).

Two representations of the process of integration represented by convergence. Top, in order to take advantage of new opportunities, a merger of expertise from life and physical sciences and synergy across academic, industry, and government sectors is (more...)

When done well, convergence can represent a roadmap for innovation, and in particular for generating what has been called combinatorial innovation, a process that happens when a new technology or set of technologies offers a rich set of components that can be combined and recombined to create new products and services. These components catalyze a technology boom as innovators from multiple fields work through the possibilities.

In biomedicine, convergence will be one essential strategy for making progress in the treatment of disease to improve health outcomes while lowering costs, but a number of real-world problems do not respect disciplinary boundaries and a convergence approach has the potential to benefit many areas of research and development. Examples of such problems include meeting the world's need for secure food supplies on a hotter, drier planet while reducing the environmental footprint of agriculture; providing new treatments for the chronic illnesses that are plaguing an increasing number of people worldwide; and directly attacking the mechanisms of aging in ways beyond addressing the individual diseases of aging. Chapter 2 highlights further examples of convergence in action.

1.3. CONVERGENT THINKING IS ADVANCING SCIENCE

Numerous reports over the past decade have explored the advances enabled when disciplines come together in integrated partnerships. Several address broad questions of how integrative and collaborative research can be fostered and what this means for the future of the American research enterprise. Others focus on specific research challenges at the intersection of the physical and life sciences or present a vision for the future of biology.

1.3.1. The Research Ecosystem Involves Multiple Disciplines and Multiple Partners

A recent report from the American Academy of Arts and Sciences makes the case that research is at a tipping point in a transition from ultra-specialization and defined problems to one in which integrative and collaborative approaches are needed to solve complex challenges. The report examines how research practices and policies will need to be revised in order to integrate over two planes necessary to address this pivotal point: across disciplines in the form of transdisciplinary and convergent science, and across stakeholders to produce additional synergy and account for the changing funding landscape (see Figure 1-2 , top). The report argues that, without both of these planes, the process represented by convergence cannot effectively happen ( American Academy of Arts and Sciences 2013 ).

The report also emphasizes a need for cooperative, synergistic interactions among the academic, government, and private sectors throughout the discovery and development process. One of the report's conclusions is that historical differences exist in the culture of physical sciences and engineering, on the one hand, and life sciences and medicine, on the other. While engineering and the physical sciences have a rich tradition of placing discovery and application on a continuum, the ends of this spectrum have traditionally been disconnected in the life sciences and medicine. For example, the report notes that most of the company spinoffs generated by the genomics revolution have been initiated by physical scientists and chemical engineers. As a result, the report argues that it will be imperative for many biologists to develop a fuller awareness and capacity for applications of research.

Similarly, a recent report from the National Research Council discusses the roles of research universities as assets for the future and recommends actions to maintain and further strengthen them for the benefit of U.S. science and technology ( NRC 2012a ). The report's vision emphasizes many of the characteristics highlighted by the American Academy of Arts and Sciences, including a need for comprehensive partnerships among government, academia, and industry to “facilitate the transfer of knowledge, ideas, and technology to society and accelerate ‘time to innovation' in order to achieve our national goals” ( NRC 2012a , p. 11).

1.3.2. Convergence Will Accelerate Discovery and Innovation

An array of reports from the National Research Council (NRC) have examined key opportunities enabled by science that occur at the intersections of disciplines and have set forth the view that multiple fields are poised to make significant advances if communities collaborate across life, physical, mathematical, computational, and engineering fields. These publications include Mathematics and 21st Century Biology ( NRC 2005a ), Catalyzing Inquiry at the Interface of Computing and Biology ( NRC 2005b ), Inspired by Biology: From Molecules to Materials to Machines ( NRC 2008 ), A New Biology for the 21st Century ( NRC 2009 ), Research at the Intersection of the Physical and Life Sciences ( NRC 2010 ), and Research Frontiers in Bioinspired Energy: Molecular-Level Learning from Natural Systems: A Workshop ( NRC 2012b ). Such reports, along with others from outside the NRC, provide compelling examples of what can be achieved by drawing together diverse areas of expertise and argue that activities conducted at the interface between life and physical sciences will continue to be an integral part of the scientific enterprise looking toward the future. A New Biology , in particular, argues that advances in biological research will accelerate if directed toward grand challenges and that integrating life sciences research with other disciplines will gain a deeper understanding of biological systems and achieve new biology-based solutions to critical societal problems in the areas of health, environment, energy, and food (see Figure 1-2 , bottom).

Many of these earlier reports did not specifically adopt the terminology of “convergence” to refer to the goal of merging expertise across disciplines, although the concept they described is similar in intent. A specific vision for the convergence of life sciences, physical sciences, medicine, and engineering to advance health was more fully articulated by scientists and leaders at the Massachusetts Institute of Technology ( Sharp and Langer 2011 ; Sharp et al. 2011 ). It has continued to capture the attention of scientists who practice at these convergent interfaces ( Sharp and Langer 2013 ; Sharp and Leshner 2014 ).

1.3.3. Convergence Is About Science and Society

A recent report expands this concept of convergence to encompass the broad convergence of knowledge, technology, and society across multiple dimensions ( Roco et al. 2013 ). Convergence is placed in the context of a creative “convergence–divergence” process that brings areas of knowledge together into a new system to spin off applications and elements that can in turn be recombined and integrated. Research activities from across a spectrum including pure basic research, use-inspired basic research, and “vision-inspired” basic research, as well as applied research, are needed throughout this repeating cycle ( Figure 1-3 ). Although placing convergence in a very broad context, the report emphasizes a critical role of the merging of life and physical sciences expertise. In their chapter Implications: Human Health and Physical Potential , for example, Urban and Grodzinski state, “over the next ten years, the major scientific infrastructure needed will be an effort to define these ‘laws of biology' within a convergence approach that nurtures engagement of the physics and physical sciences research communities” ( Urban and Grodzinski 2013 , p. 184).

The role of research in the convergence–divergence process. Scientific research can be characterized by its motivation to advance fundamental knowledge and have practical utility. Roco et al. add a new box for “vision-inspired basic research” (more...)

1.3.4. Implementing Convergence Builds on Prior Reports

In order to be successful at harnessing the combined transformative potential of life and physical sciences with engineering, key stakeholders across the research enterprise need to think strategically about the policies necessary to support such efforts and how to implement and sustain them. The challenges inherent in creating new research, teaching, institutional, funding, partnership, and other structures likely to be required as part of successful convergence efforts can be enormous. The report Facilitating Interdisciplinary Research , published by the National Research Council almost a decade ago ( NAS et al. 2004 ), lays a foundation for how collaborative scientific endeavors can be fostered and provides numerous recommendations, many of which can be extended for the purpose of convergence. In fact, the top three actions identified by 341 survey respondents in 2004 for institutions seeking to support interdisciplinary research (IDR) were “to foster a collaborative environment (26.5 percent), to provide faculty incentives (including hiring and tenure policies) that reflect and reward involvement in IDR (18.4 percent), and to provide seed money for IDR projects (11.1 percent)” ( NAS et al. 2004 , p. 270). These points continue to be strongly echoed in the committee's data gathering for the present report.

Despite progress in establishing interdisciplinary, transdisciplinary, and convergent research programs and the existence of agency policies designed to support collaborative scientific endeavors, challenges clearly remain. The Roco et al. volume notes that “there has been a growing appreciation in scientific and academic communities worldwide that converging technologies…are likely to create important advances toward societal gain,” but the authors continue to raise the concern that “the R&D focus for converging technologies publications has remained reactive (or ‘coincidental') to various opportunities for collaboration rather than being driven by a holistic, systematic, proactive approach towards promoting convergence” ( Roco et al. 2013 , p. 138). Organizations and practitioners wishing to undertake convergence face a lack of practical guidance in how to do it.

The present report does not seek to re-tread all of the ground covered by these prior activities. Rather, it revisits key themes they highlighted and provides tailored examples of strategies relevant to addressing the continuing challenges of fostering convergence among life sciences, physical sciences, medicine, and engineering in different settings. It also considers the opportunities and challenges that arise from expanding convergent research initiatives to include contributions from additional fields such as the economic and social sciences and humanities.

1.4. INSTITUTIONS NEED GUIDANCE TO FOSTER CONVERGENCE EFFECTIVELY

Now is an opportune time to consider steps that can be taken to foster convergence among biological, physical, and engineering sciences. Institutions continue to face a lack of guidance on how to establish effective programs, what challenges they are likely to encounter, and what strategies other organizations have used to solve the issues that arise. The present study was undertaken to help address this gap and to provide an opportunity for members of the research community to come together and discuss their challenges. Responding to the messages from reports such as those above and the needs of their scientists and communities, institutions have increasingly moved to implement programs that foster convergence or are interested in how they can better facilitate convergent research. The number of research universities that are making investments in convergence is increasing and so, too, is the diversity of institutional practices being used to facilitate convergence, ranging from new educational modules (see Section 4.6 ), to cluster hiring ( Section 4.4 ), to establishing multidisciplinary research institutes ( Section 4.3 ). The success of the National Academies Keck Futures Initiative at catalyzing the formation of research teams that start new avenues of investigation is yet another example of the growing appreciation of the role of convergence among many in both the research and policy worlds ( Porter et al. 2008 ; NAS et al. 2013 ).

In parallel, the federal government has announced funding for several large convergent initiatives focused around specific research areas. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) initiative is a multiagency effort led by the National Institutes of Health (NIH), Defense Advanced Research Projects Agency (DARPA), and the National Science Foundation (NSF) with significant support from private research institutions and foundations. It seeks to generate new understanding about how the brain works and, to succeed, it will require convergence among fields such as neuroscience, nanoscience, synthetic biology, genetics, optics, computer science, and informatics. The Tissue Chip Project, a collaboration among NIH, DARPA, and the Food and Drug Administration, aims to foster convergence among tissue engineering, cell biology, microfluidics, analytical chemistry, physiology, drug development, and regulatory science to develop three-dimensional chips that mimic human physiology. NSF's Integrated Support Promoting Interdisciplinary Research and Education program, the National Cancer Institute's Alliance for Cancer Nanotechnology and Physical Sciences Oncology Centers, and DARPA's Quantitative Effects in Biological Environments are other examples.

Despite strong models, however, a number of cultural and institutional roadblocks slow implementation of convergence and creation of a self-sustaining ecosystem of convergence. The committee's task was to explore the mechanisms used by organizations and programs to support convergent research and to distill messages that arose into a report that seeks to provide informed guidance for the community (see Box 1-1 for the full statement of task and Appendix A for committee member biographies).

Statement of Task. The National Research Council will appoint an expert committee to explore the application of “convergence” approaches to biomedical research and beyond. This approach is intended to realize the untapped potential from (more...)

A primary mechanism by which the committee gathered information on relevant programs and activities was its workshop on “Key Challenges in the Implementation of Convergence,” held September 16-17, 2013. A cross section of over 100 participants ranging from graduate students to senior institutional leaders to scientists from foundations and agencies gathered at the National Academy of Sciences in Washington, D.C. (see Appendix B ). The group discussed examples of programs that had been created and what has worked and not worked in varied settings, with an emphasis on strategies to tackle practical needs and challenges in areas such as organizational infrastructure, faculty development, education and training, and the formation of interinstitutional partnerships. The result of the workshop discussions and additional research undertaken by the committee is the following report, which seeks to harness the promise of the concept of convergence and channel it into the policies, structures, and networks that will better enable it to realize its goals.

1.5. ORGANIZATION OF THE REPORT

The report explores convergence in context and in action—examining why it is a paradigm for generating innovative science, why and how institutions and agencies can foster cultures of convergence, and why further coordination among the academic, clinical, industrial, and funding communities interested in convergence is needed. Chapter 2 provides examples of convergence in action that demonstrate the promise of convergent thinking in advancing knowledge and in achieving problem-based solutions at the interfaces of life, medical, physical, and engineering sciences, and beyond. The chapter also highlights some of the ways that a convergence ecosystem cross-fertilizes interactions with industry partners to help stimulate biotechnology innovation. Chapter 3 presents a snapshot of research in some of the foundational areas that inform an understanding of convergence, especially transdisciplinarity and team science and new approaches in science, technology, engineering, and mathematics education. The report does not attempt to provide an authoritative review of these rich and diverse fields. Rather, it seeks to make science practitioners and institutional leaders aware of complementary bodies of knowledge that may provide further insights into ways they can meet the challenge of nurturing environments in which convergence occurs. Chapter 4 builds on the examples presented during the project's data-gathering workshop as it begins to formulate a picture of how convergence can be fostered in organizational settings. Finally, Chapter 5 provides the committee's overall conclusions and recommendations.

Throughout the rest of the report, the term “physical sciences” is commonly used as shorthand to include fields such as physics, chemistry, materials science, and the mathematical and computational sciences.

• Cite this Page Committee on Key Challenge Areas for Convergence and Health; Board on Life Sciences; Division on Earth and Life Studies; National Research Council. Convergence: Facilitating Transdisciplinary Integration of Life Sciences, Physical Sciences, Engineering, and Beyond. Washington (DC): National Academies Press (US); 2014 Jun 16. 1, Introduction.
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• A SCIENCE AND TECHNOLOGY REVOLUTION IS OCCURRING
• CONVERGENCE IS AN EXPANDED FORM OF INTERDISCIPLINARY RESEARCH
• CONVERGENT THINKING IS ADVANCING SCIENCE
• INSTITUTIONS NEED GUIDANCE TO FOSTER CONVERGENCE EFFECTIVELY
• ORGANIZATION OF THE REPORT

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The debate of convergence or divergence in IHRM

Business Saviness

April 26, 2024

A Critical analysis of the international convergence-divergence debate about International Human Resource Management (IHRM) practices drawing upon specific examples to contextualise academic theory.

IHRM is an essential attribute within an MNC, defined as ‘understanding, researching, applying and revising all human resource activities in their internal and external contexts…throughout the global environment.’ The growth of globalisation only increases the importance of IHRM as organisations rely even more heavily upon an international, multicultural workforce to compete. Regarding organisations with multiple international subsidiaries, the HR practices that should be utilised have been subject to much academic debate; convergence vs divergence.

Convergence puts forward that IHRM practices are becoming more similar and will eventually ‘converge’ so that the same best practices are employed globally. However, divergence opposes this, arguing that international human resources management practices will remain distinct from one another despite globalisation. This submission will first examine the convergence debate, adopting a critical view. While evidence suggests some practices have become more similar, they will never fully converge for various reasons. Then, an analysis of the divergence debate will take place. Finally, this submission will adopt a nuanced view, acknowledging that aspects of both arguments are accurate and that a hybrid model of the two is most likely.

Convergence Thesis

The convergence thesis effectively portrays that IHRM practices will converge globally for two key reasons: globalisation and industrialisation. It is essential to acknowledge that there is substantial evidence supporting this theory. Regarding the industrialisation debate, Kerr et al. (1960) put forward that companies will have to converge their industrial practices to retain their competitive advantage for companies to compete in the global economy. This is further supported by Womack et al. (1990), who argued that manufacturing procedures would have to adopt lean production methods. If one MNC adopts these measures, but their competitors do not follow suit, they will risk losing customers due to low efficiency and price. This principle has been applied to IHRM practice and is known as a universalist approach.

Moreover, the link between globalisation and this argument is great. Historically, orthodox economists believed that the unfettered flow of international trade would effectively lead to poorer countries copying the practices of the richer countries. This would create uniformity in national business patterns (Rowley and Bae, 2002). Although this model was criticised as globalisation increased, it became increasingly relevant. Regarding IHRM, Clark and Claydon (2010, p.599) argued that ‘firms will increasingly tend to adopt, based on efficient markets, similar approaches to work organisation, training, pay, employee involvement, etc.’ There is a broad range of practices that convergent theorists believe will be affected by globalisation. This argument was then developed further to state that within IHRM, there are principles that operate superiorly to all others and that, eventually, these will be applied globally. This idea of ‘best solutions’ or ‘best practices’ believes that MNCs will be pushed towards homogenisation.

The following study is presented as evidence for this theory. Gould-Williams and Moamed’s (2011) comparative study of the effect of ‘best practices in Malaysia illustrated that a bundle of HR practices had a positive effect, which ‘supports the universal thesis.’ Moreover, Chris Brewster conducted a 3-year survey of 14 European countries, which promoted the notion of a New European HRM Model. This study recognised the increased homogenisation of trade unions and employment IHRM practices in its sample. However, it is important to acknowledge that Gould-William’s study also found negative effects on the best practices.

Moreover, European countries are in a unique situation as most of these countries were in the UK; a political union already striving towards homogenisation. As European national institution patterns are so different that ‘no standard model is likely to emerge in the foreseeable future, this study cannot evidence global convergence. While the convergence debate is logical and has some evidence to support it, the overall thesis assumes that globalisation will automatically lead to convergence. Therefore, it is submitted that the convergence thesis is based on a false premise.

A Critical View: Convergence

As previously mentioned, globalisation does not automatically equal convergence. Ferner et al. (2006) evidenced this by stating that these ‘best practices are often transformed considerably when introduced to other domestic countries. Elenkov (1998) further supports this submitting that the distinct state of national contexts prevents convergence as cross-cultural differences are too broad to assume that Anglo-American IHRM techniques are directly transferrable. The convergence thesis is flawed for several reasons. Primarily, nation-states will still play a key role in regulating their economic affairs. The concept that MNCs are reducing nations’ sovereignty is overstated at best. Although MNCs are growing in number and power, there are few genuine examples of transnational companies. Often these international organisations merely operate between well-established networks of countries. Martienz-Lucio supports this:

‘ MNCs continue to require a set of political and regulatory interventions and support from nations, which they as private organisations cannot supply. The idea that we are seeing the emergence of omnipotent companies such as Apple or Sony ignores the complex reality of globalisation and the continuing role of national regulatory systems. (2014: 18).’

This illustrates that national contexts are still significantly influencing IHRM practices through laws and regulations, and whilst MNCs can exploit this, total convergence cannot happen. Secondly, critics of the convergence debate also suggest that national contexts influence the effectiveness of ‘best practices.’ Rowley and Bae (2002) argue that successful implementation of IHRM practices depends on performance and internalisation. Essentially, even if there are a set of superior best practices, their success is still reliant on the employees within each country accepting them. For convergence to truly take place, far more is required than merely the existence of best practices. Thirdly, there is the issue of subcultures. Culture is a broad and elusive concept, and consequently, only considering convergence adapting to national culture is a vast simplification of culture itself. Rarely, if ever, does one country have ‘one culture’ with individual cities often having their subcultures. These subcultures can also influence IHRM, with Guirdham (2011) proposing that these differences can result in various communication styles, non-verbal communication, communication rules, politeness, and conversation constraints. Effectively, the convergence debate underestimates the issues discussed above and is further away from actualising than is often acknowledged in the literature.

Divergence Thesis

The divergence debate is based on the premise that IHRM practices and strategies will differ in different countries. These practices are embedded in socio-economic contexts, and often best practices require adaptation to suit national contexts. Hall and Soskice (2001) demonstrate continued diversity in local and national patterns through their varieties of capitalism frameworks. Within VoC, academics highlight each country’s different socio-economic characteristics based on national culture, economic and political conditions, institutions, and historical legacies that substantially shape employment relations (Bryson and Frege, 2010). Despite the financial pressures pushing towards divergence, there is remarkable resilience in cultural and institutional contexts, maintaining divergent employment relationships and resultantly IHRM practices (Clark and Pugh, 2000).

The divergence thesis is based on two main grounds: divergence through culture and institutions. Regarding divergence through culture, the argument is that the cultural orientation of national contexts shapes the IHRM practices. The specific practices that can be affected include international negotiations, the importance of distributive justice, and the nature of relationships between managers-subordinate. Moreover, it can also affect wages, a central concept within IHRM. An example will contextualise this. Within the Netherlands, a ‘feminine’ culture (using Hofstede’s cross-cultural framework) encourages Dutch workers’ antipathy towards ‘hard’ HRM practices. Whereas ‘Sweden’s strong collectivist culture counters the development of an individualist orientation to the employment relationship.’ (Clark and Pugh, 000, p.96). This illustrates how cultural differences influence divergent IHRM practices.

Additionally, Ngo et al. (1998) examined the effect of the country of origin through US, UK, and Japanese MNCs in Hong Kong – the result showed that several distinct aspects of home country practices influenced the IHRM implemented in the foreign branches. The home country of an MNC used its culture to implicitly or explicitly influence IHRM practices. Moreover, this divergence is even more apparent in Asia, where Paik et al. (1996) found strong support for the divergence hypothesis even among Chinese-based countries, e.g. Hong Kong, Singapore, and Taiwan. Even countries with seemingly similar cultural backgrounds diverge.

Secondly, the formal and informal institutions within a national context influence the IHRM practices regarding divergence by institutions. Whitley (1999, p.3) put forward that despite global economies being more interconnected:

‘Societies with different institutional arrangements will continue to develop and reproduce varied systems of economic organisation with different economic and social capabilities in particular industries and sectors.’

An example of these differences will contextualise this. In Germany, trade unions and work councils ensure that industry-wide wages have a noticeable influence on recruitment and pay HR practices. In stark contrast, the US has no such arrangement. Moreover, in Europe, there is generally greater regulation regarding recruitment and dismissal, more formalised educational certification, and quasi-legal aspects to the industrial relations framework (Gold, 2009). This differs massively again from America, allowing unregulated and de-centralised systems to give organisations the power to hire and fire almost entirely free of regulation. These countries could not embody one ‘best practice’ re IHRM as their national institutions led to differing employment laws and norms. 

Nuanced Approach

Hybridisation has been the critical result of these debates. Essentially, this is an IHRM strategy that combines different orientations and is arguably more appropriate than convergence or divergence. Chung, Sparrow, and Bozkurt (2014) did a study, and in all nine of the companies used, their IHRM system embodied that of hybridisation. However, this submission will not detail this topic as it is vast in itself. Merely, it will use it to present a nuanced picture of the convergence-divergence debate. Like with most things, neither side of this debate is entirely correct. However, it is also important to note that they are not wrong.

Chris Brewster summarises this:

‘Those looking to defend one position or another can easily find evidence to support their case. Thus, there do seem to be trends…that are widespread, even if they do not seem to be diminishing the differences between the countries in the way they manage their HRM.’

Various scholars have now adopted a nuanced view, basically stating that whilst globalisation has promoted ‘homogenisation’ (convergence), the extent to which it is happening must be re-evaluated from early literature on the topic. This submission adopts the view that ‘convergence is always tempered by divergence.’ The two arguably go hand in hand, as it is unfair to say IHRM practices are getting less similar. Still, the idea that they will converge into one set of principles is a vast simplification of globalisation, culture, and IHRM itself.

In conclusion, whilst both sides have empirical evidence and logic supporting their theories, the debate is regarding an increasingly complex topic. Globalisation is neither leading to people becoming exclusively more similar nor more different; it is simultaneously doing both: ‘Paradoxically, at the same time as transactional boundaries weaken, there is an increased awareness of cultural differences and a growing celebration of cultural diversity. Globalisation may therefore be stimulating divergent as well as convergent developments….’ Child (2002):

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