La empatía como una elección

Empathy as a choice

By Jamil Zaki

About 250 years ago, Adam Smith famously described the way observers might feel watching a tightrope walker.  Even while standing on solid ground, our palms sweat and our hearts race as someone wobbles hundreds of feet in the air (you can test this out here).  In essence, we experience this person’s state as our own.

Centuries later, this definition does a surprisingly good job at capturing scientific models of empathy.  Evidence from across the social and natural sciences suggests that we take on others’ facial expressions, postures, moods, and even patterns of brain activity.  This type of empathy is largely automatic.  For instance, people imitate others’ facial expressions after just a fraction of a second, often without realizing they’re doing so. Mood contagion likewise operates under the surface.  Therapists often report that, despite their best efforts, they take on patients’ moods, consistent with evidence from a number of studies.

One tempting conclusion about automatic behaviors is that are also “dumb:” occurring whenever the right stimulus comes along.  On this view, empathy is the emotional equivalent of a patellar reflex: while observing someone’s emotions, you can’t help but take those emotions on yourself.  Intuitive as it may be, a “reflex model” glosses a vital feature of empathy: it is often a choice.  Even if others’ emotions rub off on us automatically, this process is only set in motion if we decide to put ourselves in a position for empathy to occur.  And that decision is anything but automatic.  Instead, people frequently make deliberate choices to avoid others’ emotions, in attempts to stave off the discomfort or costs of empathy.

One of my favorite studies on this topic—a long forgotten gem from 1979—measured empathy by circumference.  Mark Pancer and his colleagues set up a table in a busy tunnel at the University of Saskatchewan, and secretly measured the distance people kept from the table while walking past.  They manipulated two features of the situation.  The first was whether or not the table had a box placed on it requesting charitable donations.  The second was who was manning the table: (i) no one, (ii) an undergraduate, or (iii) an undergraduate sitting in a wheelchair.  Both the request to donate and the presence of a handicapped person were considered triggers to empathy.  Instead of approaching these triggers, however, students avoided them: walking a wider arc around the table in the presence of either trigger, and keeping the greatest distance in the face of both the handicapped student and donation box.

In a more recent study along the same lines, Daryl Cameron and Keith Payne examined the well-known “collapse of compassion.” Cameron and Payne told participants about the suffering of children in the wake of Darfur’s civil war, and showed them pictures of either one or eight of these children.  Critically, they told some participants that—after viewing these pictures—they would have a chance to donate money to help these children.  Participants who believed they would be put on the spot to donate felt less empathy for eight children than for one, consistent with the idea that they purposefully “turned down” their empathy when empathizing could prove costly.

Together, these studies suggest that instead of automatically taking on others’ emotions, people make choices about whether and how much to engage in empathy.  Pancer and Cameron’s observations at first appear bleak—people shut down empathy when it might cost them—but I think they paint a more encouraging picture.  For instance, Paul Bloom recently argued that empathy is a bad guide for decision-making, precisely because it is a slave to triggers such as images of others’ suffering.  On Bloom’s reasoning, this means that empathy will often drive irrational choices based on emotions: for instance, helping a single suffering child we see on television while ignoring countless others who receive less press.  Although Bloom is right in many cases, if empathy is a choice, then people can presumably learn to use it when they know it is most important.  For instance, people could decide to “turn up” empathy for victims with whom they might not immediately connect (a suggestion made earlier by Daryl Cameron as well).  Broadly speaking, empathy we can control is empathy we can co-opt to help others as much as possible.

Scientific American

About the Author: Jamil Zaki is an assistant professor of psychology at Stanford University, studying the cognitive and neural bases of social cognition and behavior. Follow on Twitter @jazzmule.

¿Tener amigos (monos) incrementa el tamaño de tu cerebro?

Social Networks Matter: Friends Increase the Size of Your Brain

By Eric Michael Johnson 

Scientific American

New research confirms that social complexity enriches cognitive growth. Could having more Facebook friends actually make you smarter?

"The Social Network" by Nathaniel Gold

   

Let’s face it, as a species we’re obsessed with ourselves. The vast majority of us spend our days at work or school where a considerable amount of time is taken up not discussing the important issues of the day, but rather the juicy details of one another’s personal lives. Then we go home only to sign on to social network services like Facebook, Twitter, orGoogle+ and continue where we left off. In this respect we’re fairly typical primates. Most of our simian relatives, particularly our great ape cousins the chimpanzees and bonobos, like nothing better than keeping a watchful eye on what other members of their troop are up to. But our species has taken this preoccupation one step further.

Human beings are the most social of the primates and have the largest group sizes of any species in our order. For about 90% of our existence we lived in hunter-gatherer societies with populations that likely clustered around 150-200 individuals. By way of comparison, baboons come in a distant second with an average of about 50 group members. Now, thanks to modern industrial agriculture, our species has pushed that range well into the millions, a development that has resulted in considerable stress on our slightly above average primate brains. Of course, all organisms need to successfully predict and navigate their environments in order to relay their genes on to the next generation. It’s just that this becomes increasingly complicated when there are many individuals all interacting in the same environment simultaneously. Merely keeping track of these relationships requires a considerable amount of time and energy, not to mention brain power.

In the 1990s the British evolutionary anthropologist Robin Dunbar championed an idea known as the Social Brain Hypothesis. He found that mammals who lived in the largest social groups often had the largest neocortex to brain ratio. Since the neocortex — composed chiefly of gray matter that forms the outermost “rind” of our cantaloupe-sized stuff of thought — is associated with sensory perception and abstract reasoning, Dunbar hypothesized that the demands of group living resulted in a selection pressure that promoted the expansion of neocortical growth.

Figure 1. As average group size increases in monkeys and apes, so does neocortex ratio. Reproduced from Dunbar and Shultz (2007).

In 2009 I co-authored a study in the Journal of Human Evolution with colleagues Evan MacLean, Nancy Barrickman, and Christine Wall of Duke University that found no relationship between relative brain size and group size in lemurs (a clade of strepsirrhine primates that last shared a common ancestor with the haplorhine monkeys and apes about 75 million years ago). However, where it comes to these more recently evolved haplorhines, the data is remarkably consistent with Dunbar’s interpretation (see Figure 1 below).

Primates, and humans in particular, are such good social cooperators because we can empathize with others and coordinate our activities to build consensus. It is what also makes us so remarkably deceitful, allowing us to manipulate other members of our group by intentionally making them think we will behave one way when our actual plans are quite different. A successful primate is therefore one who can keep track of these subtle details in behavior and anticipate their potential outcome.

But therein lies a chicken-and-egg problem. How do we know whether it’s the social networks that have promoted an increase in neocortical growth or whether that same expansion of gray matter simply allowed these social networks to expand? A new study published in the November 4th edition of Science addressed this question by housing monkeys in different sized groups to find out if their neocortical gray matter increased as the number of individuals grew. A team of neuroscientists led by Jérôme Sallet and Matthew Rushworth of the University of Oxford in England randomly assigned 34 rhesus macaques to separate social groups ranging in size from 1 to 7. The researchers conducted magnetic resonance imaging (MRI) scans on 23 of the monkey’s brain structures both before they were placed into their various groups and again after more than a year had passed.

Their analysis revealed a clear, linear relationship between the size of a monkey’s social network and an increase of neocortical gray matter in regions involved with social cognition (such as the mid-superior temporal sulcus, rostral prefrontal cortex as well as the frontal and temporal cortex). Previous research has shown that these regions are important for a variety of social behaviors, such as interpreting facial expressions or physical gestures, “theory of mind,” and predicting the behavior of other group members. Overall the monkeys demonstrated an expansion of gray matter ranging from 3-8% (depending on the brain region) for each additional member of their social network. In other words, monkeys that lived in the most socially complex group had an average increase of 20% more neocortical growth than monkeys housed individually.

Figure 2. Gray matter increased with social network size; P < 0.005. Reproduced from Sallet et al. (2011).

In order to make sure that the increased brain growth corresponded with more successful social behaviors, the research team also tested whether there was a correlation between gray matter volume and a monkey’’s rank within their group (as in many other primates, rank in rhesus macaques is a strong predictor of reproductive success). Once again the researchers found a linear relationship, at a ratio of 3-to-1, between a monkey’s dominance behavior and the growth of key regions in their neocortex. This means there was individual (potentially genetic) variation that allowed certain monkeys to experience greater neocortical growth than other group members that were living in an identical environment. This strongly suggests that it is the cognitive demands of a larger social network that has resulted in the growth of brain regions beneficial to social behavior in primates.

“Social network size, therefore, contributes to changes both in brain structure and function,” said Sallet. “Individual variation in brain anatomy should have implications for an individual’s success within the social group.” Crucially, these individual differences remained consistent for more than four months. Certain individuals happened to be better suited for dealing with the demands of larger social groups, but they had to first live in that environment before their natural abilities could emerge.

This raises a provocative question. Individual variation is the raw material on which natural selection operates. But in a rapidly changing environment — like in many human societies ever since the invention of agriculture 10,000 years ago — there will be many new adaptive opportunities that may never have existed throughout most of human evolution. Consider those individuals who have made successful careers (and had large families) through their skill as novelists, DJs, or computer programmers. Certain aspects of their skill sets would certainly have been based in our long history of hominin evolution, but other parts may have had little or no adaptive value at any other time than the present.

It is this capacity that was the focus of a study published last month in Proceedings of the Royal Society that investigated the biological variability in another form of social behavior: online social networking. In a collaboration between neuroscientists and anthropologists led by Ryota Kanai and Geraint Rees from the Institute of Cognitive Neuroscience at University College London, the researchers investigated social media users, specifically Facebook, for the same kinds of biological variation that distinguished certain social monkeys over others.

“These services allow individuals to articulate and make visible their friendship networks,” explained Kanai, “and it is apparent that there is considerable variability in the size of such networks.”

By comparing the differences between individuals and the size of their online network of friends, real-world friends, as well as the size of neocortical brain regions involved in social behavior, the researchers were able to identify a strong correlation between the volume of three neocortical regions and the number of that individual’s Facebook friends. Crucially, these brain regions (the right superior temporal sulcus, left middle temporal gyrus, and entorhinal cortex, areas previously implicated in social perception and associative memory) had no relationship to the real-world social networks of these individuals. There was only one area, the amygdala, that showed a correlation between gray matter density and both forms of social networking. The other brain regions seemed to be, quite literally, wired for the web.

However, unlike the study with monkey social networks, there was no way to determine whether it was the number of an individual’s Facebook friends that had pushed this neocortical growth or if it was actually the other way around. But given the similarities in function, it is certainly a tempting conclusion to reach. Could it be that online technology has allowed some individuals to express (and expand) a form of social behavior that emerged for other adaptive reasons but which has been underutilized until now?

Given the regular jeremiads from self-appointed cultural guardians over what they see as the danger of our increasing reliance on online networks at the expense of real-world ones, the possibility that we may actually be enhancing untapped potential is a refreshing idea. At the same time, however, it’s probably a good idea to wait until we know for sure before sharing the news with any other primates. The last thing I need is a slew of hairy faces crowding my wall. I have enough trouble keeping track of my online network of friends as it is.

References:

Sallet, J., Mars, R., Noonan, M., Andersson, J., O’Reilly, J., Jbabdi, S., Croxson, P., Jenkinson, M., Miller, K., & Rushworth, M. (2011). Social Network Size Affects Neural Circuits in Macaques, Science 334 (6056), 697-700. DOI: 10.1126/science.1210027

Kanai, R., Bahrami, B., Roylance, R. and Rees, G. (2011). Online Social Network Size is Reflected in Human Brain Structure, Proceedings of the Royal Society B: Biological Sciences, published online Oct. 12, 2011. DOI: 10.1098/rspb.2011.1959

Dunbar, R.I.M. and Shultz, S. (2007). Evolution in the Social Brain, Science 317 (5843), 1344-1347. DOI: 10.1126/science.1145463

MacLean, E.L., Barrickman, N.L., Johnson, E.M. and Wall, C.E. (2009). Sociality, Ecology, and Relative Brain Size in Lemurs, Journal of Human Evolution 56 (5), 471-478. DOI: 10.1016/j.jhevol.2008.12.005

Tambayong y Carley (2013): Análisis de red de textos en etnografía

Tambayong - Network Text Analysis in Computer-Intensive Rapid Ethnography Retrieval: An Example from Political Networks of Sudan

Visualización: La red de comercio global

Mapping Globalization: Visualizing the Network of Global Trade

Manish Nag

Doctoral Candidate at Princeton University

mnag@Princeton.edu

Mapping Globalization: Visualizing the Network of Global Trade

Caption

How global is globalization?  The last 20 years have witnessed an explosion of international connections and transactions: we travel more to each other’s cities, buy more of each others’ products, and are more likely to read each others’ newspapers and best-sellers.  But there are severe limits on the reach and degree of globalization.  European and North American newspapers are more likely to be read by an international audience than their Indian or Brazilian counterparts.  Style and sophistication are still more associated with Paris than Shanghai, not to speak of Mumbai.  When we speak the global language of business, science, and the arts, it sounds remarkably like English.

                Even in the most globalized of arenas, the pattern of relations and connections can still look remarkably like the 19^th century.  Despite the prophesied rise of a “Pacific Century”, most of the global action remains rooted in the North Atlantic.  While the past decades have witnessed the rise of East Asia, the Global South plays a small role in global trade.  This is particularly true of commerce in manufactures and other high value-added products whose production remains concentrated in relatively wealthy countries.  (The design and sales of these products, where the greatest profit can be derived, is even more concentrated).  When the economies at the global margin do participate, they often do so through the sale of a single commodity or through the export of labor.

                Our animation documents this by tracking global trade in 2001.  Counting all possible dyadic transactions we have taken graphic photographs of four levels of trade. The first image of all global trade includes the numerous, but often insignificant, links connecting the globe.  In the next image of the top 75% of trade, the number of countries involved and lines linking these are noticeably reduced (and the overall geographical concentration and centrality of the United States and Western Europe becomes clear). The next picture subtracts even further to the few commercial relationships needed to account for 50% of the total.  In the last image we can see the relatively few country pairs with the largest commercial transactions adding up to 25% of the global total.

Self-Commentary

                Our visualization was created using Sonoma, a new software tool that exists to create geospatial visualizations of social networks. The tool allows researchers to build maps, and then to automatically overlay social network graphs. As a result of using this tool, creating the visualizations was simply a matter of using Sonoma's user interface to define a map projection and map colors, to upload trade network data in a matrix file, and to upload a separate file for latitude and longitude data for each actor on the map.

                For our example, since nations were our actors, we positioned each graph vertex on the nation's capital city. The latitude and longitude data was obtained from the CIA World Factbook. Once, the data files were uploaded, the Sonoma user interface was used to define visual attributes of the network graph's vertices and ties, along with schemes for scaling the colors and widths of ties based on tie weights.

                The matrix data was furnished by the Mapping Globalization website at Princeton. Though the original data provided directed matrix data for world trade, we converted this data to an undirected format by simply taking the sum of trade in both directions between each dyad of nations. The choice was made to use undirected network data because introducing directional arrows in a global map would create too much visual clutter.

                Once images were created in Sonoma, an animation was rendered using Adobe Photoshop.  Due to the existence of Sonoma, the real challenges in creating the visualization were more in the conception and visual design of the visualization.

Though we created visualizations for other percentages of world trade, we found that choosing the top 25, 50, 75, 100 percentages of world trade summarized the larger point of how much the network of nations shrank as we visualized smaller slices of world trade.

PEER REVIEW COMMENT No. 1

This is a creative animation; when all of the global trade is included it does appear as if global trade is truly global, as the map is literally filled with connections.  But the story is quite different, when one only considers the top 75%, 50% or 25% of the global trade: here the marginal countries drop out of the network and only the major industrialized nations remain.  This large scale visualization tells a clear story in a creative manner, but the figure could perhaps be improved by adding a bit of color to liven the picture or layer more information (such as content of trade, say).  It might also be useful to make the edges more transparent, so that the map shows through even when full.

PEER REVIEW COMMENT No. 2

This visualization uses an interactive layout to show how regions of the world are integrated through trade.  At the most integrated level when 100% of global trade is depicted, the entire world appears integrated. When that level is dropped to 75% of global trade, the picture is very different. The wealthiest nations, and within them – regions, remain. This visualization is very effective already, but perhaps a heat color pattern on the underlying picture or variable line thickness would be a nice addition, to help contextualize each ‘slice.’  The dynamic elements are rhetorically effective – the inequality jumps out in the contrast between the slices – but I wonder how effective it would be to shade ties by proportion of world trade and then layer the information as a single figure?

PEER REVIEW COMMENT No. 3

This map does making a striking clear visual case for the inequality among national actors involved in the global economy.  Its use of edge thresholds leads us naturally to the author’s conclusion without needing to convince us with captions and supplementary material.  I would love to see the edges draw with edge opacity proportional to the trade volume represented by the tie (this might yield a single image that displays all ties, but still permits those few, elite, high-volume ties to stand out).

Journal of Social Structure

ARS: El grafo riverplatense

La red social de River, según algunos

Un email anda divulgando una serie de enlaces (como proxy de asociaciones de algún tipo) sobre la red social de las entidades y actores de la escena política del club River Plate (Argentina). ¿Es una red de uno o dos modos? Más allá de la falta de precisiones técnicas, es una atractiva forma de acercar el ARS al escenario de la propaganda política.

vom Lehn: Respuesta a Christakis

christakis vs. dirk vom lehn

OrgTheory.net

Dirk vom Lehn is a lecturer in the Department of Management at King’s College London. His research focuses on ethnomethodology in organizational settings. He asked if I could post this response to Christakis’ NY Times article on the need to update the social sciences.

Stagnating the Social Sciences? A response to Nicholas Christakis?

In his recent piece “Let’s Shake Up the Social Sciences” published in the New York Times on July 19^th, Nicholas Christakis calls for interdisciplinary research that creatively links the social sciences to other disciplines, in particular the natural sciences. I very much welcome his efforts to open a debate about the future of the social sciences. All too often scientists create separate enclaves of knowledge that, if joint up with others, could lead to important new academic, technological and political developments. There however are a few problems with Christakis’ argument. I wish to briefly address three of these problems here:

I am surprised Christakis puts forward the argument that “the social sciences have stagnated” over the past years. He gives no empirical evidence for such a stagnation of the social scientific disciplines and I wonder what the basis for this argument is. If he was to attend the Annual Conference of the American Sociological Association (ASA) in New York in August he will see how sociology has changed over the past few decades, and he will be able to identify specific areas where sociologists have impacted developments in policy, technology, medicine, the sciences, the arts and elsewhere.

His argument ignores also the long-standing cooperation between social scientists, technology developers, computer scientists, medics and health services providers, policy makers, etc. etc. etc. For example, for several decades social scientists, computer scientists and engineers have collaborated at research labs of PARCs,  Microsoft and elsewhere, jointly working to develop new products and services.

Christakis refers to the development of new fields like neuroscience, behavioral economics and others that “lie at the intersection of natural and social sciences”. Because “behavioral economics” is popular also with policy makers let us take this new field as an example: one of the key findings of this new field is the importance of “non-rational action” for people’s decision making. I very much enjoy the creative research undertaken by scholars in this field, but it is quite surprising that it gets away with by-and-large disregarding 100 years of social scientific research. Critique of arguments that prioritize rational action over other types of action has been key to Max Weber’s famous work in the early 1900s, Talcott Parsons’ discussion of the utilitarian dilemma, Harold Garfinkel’s breaching experiments and many other sociologists’ research and teaching.

Speaking of Garfinkel and his breaching experiments: Christakis suggests that social scientists do not use lab experiments in their teaching. He might be pointed to Garfinkel who used experiments or “tutorial exercises”, as he called them, on a regular basis to have students discover how people organize their action and interaction that bring about society. Experimental research has been conducted also by Carl Couch and the Iowa School since the 1960s with the aim to identify the key elements of social relationships. And, there are a considerable number of more social scientists who have used lab experiments to understand social action and interaction.

However, it has been noticed since that time that society does not happen in the lab. Therefore, in many social scientific disciplines lab experiments are rarely seen as the best way forward to find out about the organization of society. Garfinkel, for example, has continued to use tutorial demonstrations in his teaching but increasingly looked into the organization of the everyday world as it manifested itself in waiting queues, traffic jams and elsewhere. And the Iowa School and its experimental approach has largely vanished whereby its methods and findings can be found in symbolic interactionism and other areas. While the influence of experimental approaches has diminished, naturalistic, ethnographic and video-based research has come to the fore, most notably in workplace studies, in studies of interaction in urban environments and public places as well as in online environments. This body of studies builds on a history of more than 100 years of sociological ethnography, going back, for example, to Robert Park, Everett Hughes and the Chicago School of Sociology. Here, sending students into the field, i.e. into workplaces and schools, onto city streets, on street-markets, into museums, into parks, into Second Life and other virtual worlds, etc. has been at the center of education, training and research as it allows students to discover first-hand how society works. Scholars also increasingly use video-based research to explore the practical organization of work in complex organizations, such as operating theaters in hospitals, control rooms of rapid urban transport systems, museums and galleries, etc.

Christakis’ article is an unfortunate case of a contribution to a debate that means well in steering up discussion about the future of the social sciences, that however ends up playing into the hands of those who have launched an “attack on the social sciences”, as Sally Hillman, Executive Officer at the American Sociological Society, has called it in the association’s newsletter ‘footnote’ in June. Senators and members of the House Science Committee have suggested to “defund” Political Science at the NSF and proposed bills that “would […] prevent NSF from funding any social science research” (Hillman June 2013).

Articles like Christakis’ imply that current social sciences have little impact on society, policy makers and knowledge development more generally, whilst research in the natural sciences, in their view, has more “impact”. They, however, overlook and disregard social scientific research that has been forgotten because scholars and policy makers follow the latest fads and fashions, such as so-called Big Data research and the opportunities of brain-scans, rather than using and further developing the existing theoretical, methodological and empirical basis of the social sciences. Moreover, they pretend that the social sciences and the natural sciences basically could achieve the same impact, if only the social sciences would make appropriate use of scientific methods. Thereby, however, they ignore what social scientists have shown over and over again over the past 100 years or so, i.e. that the social is fundamentally different from nature; it always is already interpreted when the social scientist arrives. The ‘social’ requires interpretation of a different kind than nature as encountered and then interpreted by natural scientists. Furthermore, people often change their behavior in response to the research process and in response to social scientific findings. Nature remains nature. Apples keep falling down from trees.

I am all in favor of interdisciplinary research and benefit enormously from my cooperation with scholars and practitioners in the computer and health sciences as well as in the arts and humanities. I also find Christiakis’ research interesting and important. However, to use the need for interdisciplinarity as an argument for the defunding of established social science disciplines would be like throwing the baby out with the bath water. The social scientific knowledge base developed over the past 100 or more years is too precious to sacrifice just for instrumental reasons; i.e. to satisfy policy makers interested in saving money or to show “impact” however that is defined.

While the social sciences rely on and advance their knowledge base they have not been stagnating. On the contrary, they have prospered and further developed by virtue of discussions at discipline-specific conferences and in their journals as well as by cooperating with a wide range of other disciplines.

Dr Dirk vom Lehn
Lecturer in Marketing, Interaction & Technology
Department of Management
King’s College London
Franklin-Wilkins Building, 150 Stamford Street
London SE1 9NH

Tel. +44 20 78484314
dirk.vom_lehn@kcl.ac.uk

http:///www.vom-lehn.net

Christakis: Un sacudón hacia la complejidad en las ciencias sociales

Let’s Shake Up the Social Sciences

By NICHOLAS A. CHRISTAKIS

TWENTY-FIVE years ago, when I was a graduate student, there were departments of natural science that no longer exist today. Departments of anatomy, histology, biochemistry and physiology have disappeared, replaced by innovative departments of stem-cell biology, systems biology, neurobiology and molecular biophysics. Taking a page from Darwin, the natural sciences are evolving with the times. The perfection of cloning techniques gave rise to stem-cell biology; advances in computer science contributed to systems biology. Whole new fields of inquiry, as well as university departments and majors, owe their existence to fresh discoveries and novel tools.

In contrast, the social sciences have stagnated. They offer essentially the same set of academic departments and disciplines that they have for nearly 100 years: sociology, economics, anthropology, psychology and political science. This is not only boring but also counterproductive, constraining engagement with the scientific cutting edge and stifling the creation of new and useful knowledge. Such inertia reflects an unnecessary insecurity and conservatism, and helps explain why the social sciences don’t enjoy the same prestige as the natural sciences.

One reason citizens, politicians and university donors sometimes lack confidence in the social sciences is that social scientists too often miss the chance to declare victory and move on to new frontiers. Like natural scientists, they should be able to say, “We have figured this topic out to a reasonable degree of certainty, and we are now moving our attention to more exciting areas.” But they do not.

I’m not suggesting that social scientists stop teaching and investigating classic topics like monopoly power, racial profiling and health inequality. But everyone knows that monopoly power is bad for markets, that people are racially biased and that illness is unequally distributed by social class. There are diminishing returns from the continuing study of many such topics. And repeatedly observing these phenomena does not help us fix them.

So social scientists should devote a small palace guard to settled subjects and redeploy most of their forces to new fields like social neuroscience, behavioral economics, evolutionary psychology and social epigenetics, most of which, not coincidentally, lie at the intersection of the natural and social sciences. Behavioral economics, for example, has used psychology to radically reshape classical economics.

Such interdisciplinary efforts are also generating practical insights about fundamental problems like chronic illness, energy conservation, pandemic disease, intergenerational poverty and market panics. For example, a better understanding of the structure and function of human social networks is helping us understand which individuals within social systems have an outsize impact when it comes to the spread of germs or the spread of ideas. As a result, we now have at our disposal new ways to accelerate the adoption of desirable practices as diverse as vaccination in rural villages and seat-belt use among urban schoolchildren.

It is time to create new social science departments that reflect the breadth and complexity of the problems we face as well as the novelty of 21st-century science. These would include departments of biosocial science, network science, neuroeconomics, behavioral genetics and computational social science. Eventually, these departments would themselves be dismantled or transmuted as science continues to advance.

Some recent examples offer a glimpse of the potential. At Yale, the Jackson Institute for Global Affairs applies diverse social sciences to the study of international issues and offers a new major. At Harvard, the sub-discipline of physical anthropology, which increasingly relies on modern genetics, was hived off the anthropology department to make the department of human evolutionary biology. Still, such efforts are generally more like herds splitting up than like new species emerging. We have not yet changed the basic DNA of the social sciences. Failure to do so might even result in having the natural sciences co-opt topics rightly and beneficially in the purview of the social sciences.

New social science departments could also help to better train students by engaging in new types of pedagogy. For example, in the natural sciences, even college freshmen do laboratory experiments. Why is this rare in the social sciences? When students learn about social phenomena, why don’t they go to the lab to examine them — how markets reach equilibrium, how people cooperate, how social ties are formed? Newly invented tools make this feasible. It is now possible to use the Internet to enlist thousands of people to participate in randomized experiments. This seems radical only because our current social science departments weren’t organized to teach this way.

For the past century, people have looked to the physical and biological sciences to solve important problems. The social sciences offer equal promise for improving human welfare; our lives can be greatly improved through a deeper understanding of individual and collective behavior. But to realize this promise, the social sciences, like the natural sciences, need to match their institutional structures to today’s intellectual challenges.

Sunday Review - NYT

Nicholas A. Christakis, a physician and sociologist at Yale University, is a co-director of the Yale Institute for Network Science.