Big Data and Potential Worlds

Big Data

An avalanche of newly accessible datasets – popularly called “Big Data” – is transforming research questions and processes across the social sciences. Dialogo, UChicago Social Sciences, spoke with Howard C. Nusbaum and James A. Evans to discuss the impact and opportunities surrounding these changes. Link to original article below. 

 

Dialogo: What does big data mean in the realm of the social sciences?

James Evans:  Big data can mean many different things. The classic triptych is high volume, high variety, and high velocity. In the social sciences especially, it’s increasingly high volume and high variety. Each does a different kind of thing. Large-scale data comes off of highly instrumented social processes. For example, our cell phones and all of the transactions that we engage in online and in many other contexts are instrumented by an ensemble of sensors. Those sensors create large streams of data that allow us to ask and answer questions about social process at high levels of resolution than we could have only conceived before, and with much larger scale data over many different kinds of interactions and time periods, et cetera.

The variety part means that we can also explore the relationship between different kinds of social action because they exist in this common format in a way that was previously only conceivable in contexts like ethnography, where people were looking at multiple modes but in very small scales.

Overall, it’s a game changer in social sciences.

Howard Nusbaum:  For a long time, social scientists have used survey instruments like the General Social Survey, which is a very structured set of questions that people answer, and tracked that data over a long period of time. We used to consider that big data, but now there are projects like the Kavli HUMAN Project at New York University, where they intend to survey 10,000 people. To extend this into a place where there are 10,000 people instrumented across the boroughs of New York City gives access to multidimensional data in a way that we’ve never had before. One can think about it as the Hubble telescope of social sciences, moving the social sciences into the realm of something where we have evidence about people’s movements, people’s choices, people’s feelings, interactions between individuals.

Evans:  Recently, we published a study that used all of the Amazon.com book purchase data, along with Barnes and Noble, and other online book purchasers to identify the association between preferences for political ideology books on their red or blue side, and all other consumptive science and literature. That’s a transaction trace, but also clearly reveals insights about the way in which people who hold or consume information about a certain ideology also consume other kinds of things.

We are also using eye-tracking data of a variety of types, which again, increasingly is able to provide really rich interaction signals. We’re able to instrument in ways that before were specific to like one or two labs. Now, you can run a virtual laboratory of 10,000 or 15,000 or 100,000 people and get detailed interaction traces that capture arousal and attention, and other things.

In another study, we took data for tens of thousands of publications related to gene/drug interactions in the literature and aligned them with data from a high-throughput experiment on gene/drug interactions that replicated about 1.7 million of those interactions. We used the trace of collaboration and a whole host of variables that we extracted from the original papers to predict, in some cases with enormous success, the degree to which different kinds of communities produced knowledge that was more or less replicable in the future. This would have been impossible without the ability to perform high-throughput experiments, on the one hand, or use computational tools to extract information in mass from publications, on the other.

In short, there is data that we previously didn’t think of as data; like full text, government documents, user-generated images and videos, from which we can pull signals which are, in some cases, enormously predictive.

Nusbaum:  Finding signals that were heretofore unused or hidden or latent is interesting. That standard model of a meta-analysis, which you’re alluding to as an upgraded approach, the standard modeling of published research in psychology and other fields, is taking studies — specifically the summary statistics recorded in those studies — and analyzing them for consistency across conditions reported in the studies for those statistics. You’d say, ‘Oh look, nine out of ten studies, or 100 out of 150 studies show a certain kind of pattern of data consistent with the conclusions,’ so you have this sense of reproducibility. Now there are new methods of using data in publications that can lead to new insights.

For example, with functional magnetic resonance imaging (fMRI) papers — those publications have data tables in them, so the data tables have X-Y-Z coordinates corresponding to neural activity in specific spots in your brain. Instead of just taking summary statistics, an approach called NeuroSynth is used to recreate an idealized version of the data from the data tables from each of these studies, generating a new synthetic data set at a much finer grain resolution that the old approach to meta-analysis.  This actually lets you do new experiments on data that has been published. This is a way of doing new studies that are a type of synthetic research.

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Howard Nusbaum (left) and James Evans. Photo by Mark Lawton

 

Dialogo: Are conclusions in research stronger because of the volume of data that is available?

Evans:  The answer to this question has to be ‘yes and no,’ right? Because the ‘yes’ acknowledges that, okay, we’re able to access data from new places, and at new scales. And the ‘no’ highlights that digital data is data from the wild, so to speak…data from transactions or data from clicks online, or from online activity, or dating sites, or wherever, has this deep problem of algorithmic confounding. You have data on choices (e.g., “clicks”), but those choices were given to you because it was predicted that they would most appeal to you, and so as researchers we don’t know what part of online activity is a result of people’s preferences, and the “smart” algorithms that were used to predict them. As a result, there’s way more data on these huge global platforms, but the platforms are smart and that smartness shapes the results of the experiment that you’re performing every time you go online and search for things. It creates enormous opportunities, enormous challenges.

Nusbaum:  Every method, regardless of where it comes from, has its pluses and minuses. In the past days, social psychologists, sociologists, and political scientists would go to NORC (a social sciences research organization at University of Chicago) and collect stratified samples of data from populations according to a certain kind of model. Cognitive psychologists like me would run 10, 20, maybe 30 people if we were lucky, in our laboratories and collect data. Then Amazon came along with Mechanical Turk, and researchers started running studies online. We can ramp up a study now from 10 people in the lab to 1500 people (online) basically in a week.

And those people are sitting at home, perhaps watching TV while they’re doing a study. There could be kids running around and dogs barking. If you’re doing an auditory study, the quality of the headphones differs. We have to insert new kinds of quality control checks to see if people are actually engaged in a task. We have to collect demographics in a way we didn’t before. We have to find ways to collect online measures over the Internet. Yet, at the same time, we can see that we generally get very similar results from 1500 people in the field to 10 people in our laboratory. Because of that, it gives us a methodological reach in new directions that we didn’t have before.

At the same time, by going out on the web, we can now collect data from a wide variety of people. For example, there are supposed to be roughly one in 10,000 people who have absolute pitch, the ability to name the note when you hear a note played. As it turns out, we can find them all over the place, and if you set up a website and do testing for absolute pitch, we can start to bring them in to the site for testing. We can now get people with different kinds of backgrounds interested in doing our studies from all over the world. We never could have done that before.

That’s not big data, per se, but it’s a kind of reach into a data space that we didn’t have before.

Evans:  It’s big sampling.

Nusbaum:  It’s big sampling, that’s right. One of the things that is interesting about big data is we’re now trying to think about data in different ways. Scientists in social sciences who perhaps never thought about those issues are confronting those kinds of forces as well, grappling with how to think about the kind of person who has produced these data. How do you think about the framework and situation under which data was collected? What were the intents of the researchers compared to the participants?

Dialogo: What are some of the other challenges that come out of big data?

Evans:  The institutions with the greatest sense or reach into human activity are not public researchers. They’re private companies like Facebook, and LinkedIn, and Google. They have more touches of more individuals than anyone else; any other government agency.

That creates a couple of different kinds of challenges. One is that there’s a hierarchy of access by selective individuals who have selective relationships with important people and these companies that creates a kind of random access to this data by the social sciences. A second associated challenge is that the government has decided to invest less in social science data, which puts at risk the possibility that more and more of the science that emerges from these social data streams becomes private rather than public science.

Nusbaum:  There are also problems of meaning. For example, suppose you want to do a study that looks at the neighborhood safety of older people in different income brackets. How do you go about that? There are different ways of deciding what the meaning of safety is and how that translates into existing data or collecting new data, such as converting street view images from different addresses into visual measures of local safety.

The other problem that the data scientists talk about is sustainability. As more data is collected, it piles up and the set of data gets bigger and bigger.  How do you organize the data? How do you organize and allow access to the data, maintaining privacy and security? How do you maintain reproducibility as opposed to replicability such that the same data can be processed by the same kinds of tools and get the same result or the same conceptual kind of tools even as software develops over time?

Evans: Reproducibility and replicability have become deeper issues on platforms that are constantly changing. That’s the polar opposite of something like a NORC survey, which has been the same for 50 years. Just the velocity of technological change for filtering out information from noise signal is changing dramatically. I completely agree with Howard that often data science teams are just looking for variation and they rediscover things over and over again that have maybe been discovered 50 or 100 years before in small scale data.

One of the biggest challenges for the new kinds of insight that comes from big data is that as social scientists we have a taste for certain kinds of questions and we like answers of a certain resolution that conform to a certain kind of story, in the same way that a blockbuster movie has to be between an hour and a half and two and a half hours. You can’t have a five-hour movie or a half-hour movie. It’s both a problem to digest those new studies and to take them seriously, but its also an opportunity, because it holds the possibility of expanding the collective imagination of the social sciences.

Nusbaum:  Early on, the Journal of Cognitive Neuroscience required that every time you published a paper, you had to put your data in a central repository they maintained. The problem is data came from different scanners, different instruments with different properties, with different work flows, with different kinds of data structures. Nobody could easily make use of it.

Now there is the opportunity for somebody who doesn’t know anything about, for example, Alzheimer’s disease to basically analyze brain data in a unique way that psychologists or neuroscientists haven’t thought about, because we had preconceived notions of the disease.  A computational approach that looks for data patterns can come up with some new information that can provide fundamental insights. Getting more of that behavioral and neuroscience in common formats that are publicly accessible with common data modeling and analysis tools is critical for making breakthroughs in a lot of areas.

Evans:  But many of these methods are fundamentally not “statistical” yet. They’re so high dimensional. There’s no meaningful articulation of a confidence interval or anything like that because we have no precise sense of the search space that methods like multi-layer neural nets explore to identify their answers. And it remains unclear how these kinds of issues are going to shake out in the social sciences.

Dialogo: How is the availability of big data impacting methodologies?

Evans: We see it even in the traditional survey. Today – and this has really been pushed and piloted by social media and information companies like Facebook and Google – has been this development of what I’ll call active and interactive learning surveys, where you’re predicting the answer to the next question that a person might be posed.

Rather than asking a thousand questions, you might ask six personally sequenced questions to maximize that information, which means you have more space and time to ask about a whole host of other things. That’s a big shift using these models and using prediction in the context of performing survey and I would say observational data is similar.

Nusbaum:  That’s an extension of an old process that’s taken place in other areas, often called adaptive testing. GRE uses this kind of adaptive testing. On the one hand, it’s efficient and often effective, and predicts performance in other circumstances. On the other hand, in other cases, it can miss out on some things. We know from work by people like (U.S.C. Professor) Norbert Schwarz that the context of the questions matters as much as anything. If the context changes by adaptive testing, then there may be things changing that we’re not aware of. One question primes you in one way. For example, if you say, ‘How good is your life?’ Then you say, ‘How good is your marriage?’ That gets one kind of ordering versus if you say, ‘How good is your marriage,’ and then, ‘How good is your life?’ It gives another kind of pattern of response. So thinking about those kinds of things are going to nuance the way we approach these things. That will be a developmental process, I think, over time.

Evans: This highlights that more than just forms of data gathering are changing. There was a recent paper by Tom Griffiths then at Berkeley, now Princeton, which talked about experimental design as algorithm design. The idea is when you’re using these algorithms to optimally collect data then, all of a sudden, the whole idea of collecting data and then analyzing it, with a strong wall between the two processes, doesn’t make sense anymore, right?

Nusbaum:  We don’t have yet the precision of understanding our instruments in the way that physicists often do because they’re building them from scratch. Our instruments are much more context dependent than their instruments. The algorithms we use for designing our studies and the algorithms that we use for analyzing our studies are slightly mismatched.

Evans:  By building these models, you figure out what is it that you know firmly, and what you know only loosely.

Dialogo: As big data continues to become bigger, what changes do you anticipate? What do you think will happen in future research?

Nusbaum:  From my perspective, we’re seeing a convergence of different kinds of research methods. James and I were part of a common National Science Foundation research project. The conversations that we had suggested a common approach in conceptualization and different kinds of data that we can bring to bear on the same question.

One of the things we’re seeing in the social sciences is sociologists are taking blood spots. Political scientists are taking buccal swabs. Economists are doing fMRI and using methods from neuroscience. We’re getting biological data. We’re getting behavioral data. We’re getting location and movement data. We’re getting choice data. We’re getting all kinds of data, and it doesn’t matter what discipline you are coming from.

Finding the causal links between the individual and the group by looking at how the individual’s choices and behavior are influenced by the invisible forces of society is fundamental whether we’re talking about linguistics or psychology. Social science research moving in a direction where we can start to address that, because we have data with the grain of the individual and data with the grain of the group. We can look at the big forces, and we can look at the individual in relationship to them. That’s one place in which we’re going to have traction that we have not had good traction in the past.

One thing that relates to this notion of multiple levels of resolution that are studied by different fields coming together is a shift from what a focus on establishing necessary causal conditions to establishing sufficient conditions. This is a distinction that we talk a lot about in explanations in the social sciences. Is the factor that you’re observing necessary for the operation of a mechanism? Is it necessary for the outcome that you observe? Or, is it sufficient? With the integration of different perspectives, and with large-scale data, there is an increasing taste for sufficient explanations that hold in different contexts and situations.

That’s driven almost all activity in the quantitative social sciences over the last 100 years; find something statistically significant, but typically … it’s really small, not really substantial. Increasingly by integrating all these levels of analysis, we’re able to explain sometimes 90, 95, 98, 99 percent of the activity of an individual or of a group in a particular setting.

It changes a lot, right? This can make social science more potentially applied, because now we are talking about effects that are reliable but maybe not substantial, and we’re talking about reproducing phenomena. This shift in stance will provide more opportunities for us to quickly send insights out into the world of systems that generate values for people.

Evans:  Our theories become shaped in a different way. That moves us closer to physics in certain ways. As theories about various phenomena become more complex, seeing the relationships among those kinds of structures becomes much more straightforward. We have this problem in genetics. People in genetics used to have these simple causal theories, ‘This gene produces this outcome.’ Now there are statistical theories, ‘This pattern of genes gives this population.’ There’s no causal theory there. It’s only a statistical association. They don’t go from genes to proteins to neurons to behavior, or structure. They’re in search of the same kind of problem and solutions that we are. They have very complex, highly dimensional problems with data, big data that relate these things. They don’t know how to connect them. There will likely be forms of theoretical solution that may be common amongst different fields now that didn’t used to occur because those disciplines weren’t viewed in common. I think that’s going to be a huge change.

Dialogo: Closing thoughts?

Evans:  There are a number of different potential worlds that could come out of this Big Data moment. In one world, I could imagine that the computational social sciences and behavioral sciences move so quickly and aggressively, and adopt or embrace other epistemological levels of analysis and styles that they separate, and you are left with psychology, and sociology, and political science on the one hand, and you separately have a  computational social science that has speciated from those things. On the other hand, you could have a world in which computational approaches just become the way of doing good sociology or psychology or economics, which brings all of those fields a little closer.

Questions also remain about whether the biggest tranches of data are going to be locked up in such a way that the science that comes out of them is really also locked up in databases and services, and can only be used by the proprietary producers of those things? Or, are they going to be become part of a broader interchange, and feed the individual social sciences that gave rise to them? I don’t know. I think none of us knows.

Nusbaum:  This is particular challenge we see right now. 23andMe has collected many people’s genetic data. If you want to ask questions of and get a guaranteed 10,000 responses with genetic analysis, it’ll cost you six figures. Essentially, you can pay them hundreds of thousands of dollars and run a social science study on the genetic database and you have guaranteed results. If you just imagine the fact that there’s this huge database of hundreds of thousands of peoples’ genetic data as a potential pool that you could sample, consider what kind of social science you could do.

As neuroscience tools have become more effective and cheaper, there has started to be a schism within the field of Psychology. As a cognitive neuroscientist, you might be using fMRI to address basic questions of mechanisms in language understanding and decision making, and you train students in neuroscience methods and forget about the deep theoretical background coming from psychology. There is now a whole cadre of people studying brains and forgetting that we know a lot about behavior and psychology. Hopefully in the future these perspectives will be merged together. In fact, as we’ve seen more biological methods used in other parts of the social sciences, there’s a hope that actually there can be a broader convergence of disciplines and methods, moving from the past separation of psychology versus sociology versus political science to have better understanding of the questions and theories that span the social sciences. I think that’s a real opportunity that’s been missing for a long time.

Read the article: Dialogo. (2018, May 2). Common ground: Howard Nusbaum and James Evans. UChicago Social Sciences. Retrieved from https://dialogo.uchicago.edu/content/common-ground-howard-nusbaum-and-james-evans


 

Howard C. Nusbaum is the Stella M. Rowley Professor of Psychology and director of the Center for Practical Wisdom at the University of Chicago. He is internationally recognized for his multi-disciplinary studies of the nature of wisdom and the cognitive and neural mechanisms that mediate communication and thinking. Nusbaum’s past research has investigated the effects of sleep on learning, adaptive processes in language learning, and the neural mechanisms of speech communication. His current research investigates how experience can increase wisdom and produce changes in insight and economic decisions, and examines the role of sleep in cognitive creativity and abstraction. He is a scholar with Virtue, Happiness, & the Meaning of Life.

James Evans is a professor in the Department of Sociology, director of Knowledge Lab at University of Chicago, and faculty director of the Masters program in Computational Social Sciences. In his research, Evans explores how social and technical institutions shape knowledge—science, scholarship, law, news, religion—and how these understandings reshape the social and technical world. He has studied how industry collaboration shapes the ethos, secrecy and organization of academic science; the web of individuals and institutions that produce innovations; and markets for ideas and their creators, as well as the impact of the Internet on knowledge in society.

“What Good Are the Humanities?” by Talbot Brewer, available in Raritan

The Spring 2018 issue of Raritan features our scholar Talbot Brewer’s piece “What Good Are the Humanities?”

You can watch a version of this talk on our website: http://virtue.uchicago.edu/brewer

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Talbot Brewer is Professor of Philosophy and Chair of the Philosophy Department at the University of Virginia. He specializes in ethics and political philosophy, with particular attention to moral psychology and Aristotelian ethics.  Brewer is a scholar with the project Virtue, Happiness, & the Meaning of Life.

VIDEO: Meaning

This discussion of meaning led by Owen Flanagan at the Moving Naturalism Forward workshop, October 2012, has recently been uploaded to YouTube, so we wanted to share it here as well.

Participants include Sean Carroll, Jerry Coyne, Richard Dawkins, Terrence Deacon, Simon DeDeo, Daniel Dennett, Owen Flangan, Rebecca Goldstein, Janna Levin, David Poeppel, Massimo Pigliucci, Nicholas Pritzker, Alex Rosenberg, Don Ross, and Steven Weinberg.


Owen Flanagan is James B. Duke University Professor of Philosophy at Duke University. He works in philosophy of mind, ethics, and comparative philosophy. His book, The Geography of Morals: Varieties of Moral Possibility was published in 2016 from Oxford University Press. Flanagan is a scholar with the project Virtue, Happiness, & the Meaning of Life.

Barriers to Empathy

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“Empathy Tent”. Photo by Roger Jones.

 

Note: This is part 3 of a 3-part series “Perspective-Taking, Empathy, and Self-Transcendence” based on a talk at the University of California, San Diego by Candace Vogler in June 2018 for WISDOM, COMPASSION, AND LONGEVITY.

 

Suppose you are ready to undertake the other-perspective form of imagination.  There seem to be three crucial aspects of the task.  The first is simply activating your capacity for perspective-taking.  The second is trying to adjust and correct for the virtually inevitable egocentric bias.  And the third is getting accurate information about the other you hope to understand.  We can encounter difficulties in any of these three areas.

 

We can fail to involve ourselves in the task of understanding another person’s perspective because seeing the person’s distress and moving quickly to help can impede any effort to understand how things are from their perspective. In this sense, the kind of image that can inspire us to donate to charities right off may be keeping us from trying to understand the perspective of those whose suffering has us reaching for credit cards.  More generally, we can fail to try to understand how things are for the other person because it is harder to try to get a sense for someone else than it is to stick with our own perspective.  There is ample evidence that we do what comes easily rather than what takes effort whenever possible.[i]  We can substitute the imagine-self variety of perspective-taking for the required imagine-other variety without even noticing ourselves making the shift.

 

This difficulty is related to a second one—the problem of adjusting for egocentric bias.  Even as adults, it can be very hard for us fully to realize that others do not see things the way that we do.  If you have ever had a friend who keeps a straight face when teasing others, you likely have a friend who is not always aware that what his target might take the joke seriously.  It’s obvious to the teaser that he’s teasing.  It is not always clear to the target that she is being teased.[ii]  The need to adjust for egocentric biases can arise more than once in imagine-other perspective-taking.  Epley and Caruso put the point this way:

 

[P]eople’s attempts to adopt another’s perspective are likely to retain some residue of their own.  When there are few cues that others are likely to see the world very differently, people may not adjust or correct an egocentric bias at all.  When the cues are ambiguous and there is some uncertainty about others’ perspectives, attempts to adjust one’s own perspective will tend to be insufficient, and resulting judgments are likely to be egocentric….[iii]

 

The third hurdle that we need to overcome if we are to engage effectively in imagine-other perspective-taking centers on having accurate information about the other whose experience we are trying to understand.  The first two difficulties arise because we are strongly inclined to use ourselves as guides to how things are for others.  And, of course, no matter how good I become at imagine-other perspective-taking, the imagination I build for how things are going for you is my imagination at the end of the day.  I do not disappear from my own sense of the world just because I am training my efforts on making your situation more vivid for me.  What I can do, initially, is draw from the whole field of my experience and understanding to begin to get a sense for you.  If you and I have some history together, I can draw from that interpersonal history.  I can train myself to notice things about you or yours that are striking and surprising to me—points where our perspectives are likely to diverge.  I can practice patience and humility in my efforts to understand you better—listen more than I speak, notice more than I show, and so on.  In all of these ways, I can work to develop my capacity for empathy by working to strengthen my capacity for imagine-other perspective-taking.

 

Empathy and Self-Transcendence

If I am successful in learning how to see how things are for others accurately, then empathy, as I am teaching myself to practice it, can help me to nurture a self-transcendent orientation to the world that we share.

 

[i] See, for example, Daniel Kahneman, Thinking, Fast and Slow, (New York: Farrar, Straus and Giroux, 2011), Part I, pp.19-108.

[ii] See, for example, Yumi Endo, “Division in Subjective Construction of Teasing Incidents: Role and social skill level in the teasing function,” Japanese Psychological Research, Vol. 49, No. 2, (May 2007), pp. 111-120.

[iii] Nicholas Epley and Eugene Caruso, “Perspective-Taking: Misstepping Into Others’ Shoes,” in Keith Markman, William Klein, and Julie Suhr, editors, Handbook of Imagination and Mental Simulation, (New York: Taylor & Francis Group, 2009), p. 304.

 


Candace Vogler is Professor of Philosophy at the University of Chicago and a Principal Investigator on ‘Virtue, Happiness, and the Meaning of Life’, a project funded by the John Templeton Foundation. She is also the Chair in Virtue Theory, a joint appointment with the Jubilee Centre and the Royal Institute of Philosophy. 

Empathy and Shifting Perspectives

Ready to Race
Photo by Chris Smith.

 

Note: This is part 2 of a 3-part series “Perspective-Taking, Empathy, and Self-Transcendence” based on a talk at the University of California, San Diego by Candace Vogler in June 2018 for WISDOM, COMPASSION, AND LONGEVITY.

 

Empathy and Shifting Perspectives

The term ‘empathy’ can cover a very wide range of our responses to another creature’s distress.  It can cover the rush of feeling that comes of seeing images of starving children or abused pets—the sort of responses that sometimes lead us to reach for our credit cards and donate to the Red Cross or one or another Society for the Prevention of Cruelty to Animals.  It can cover the sense that I might begin to have for one of my students who has suffered the loss of a loved one.  It can cover the slow, developing understanding I can have for the situation of parents struggling to raise their sons and daughters in my neighborhood on the South Side of Chicago, or the situation of my mother and her friends in the retirement home as they confront the varieties of loneliness and disappointment that come with challenges to mobility and cognitive functioning.  I will focus on the sort of empathy that grows out of cultivated capacities to track what is going on with others.

 

This sort of empathy requires having some understanding of what other creatures think, feel, suffer, enjoy, and want.  And although any sentient creature could be a focus of such empathy, most of the research I know concerns empathy for our fellow human beings.  And much of the research is predicated on the thought that if I am to empathize with you, I must have some capacity to understand your perspective on your situation.  Perspective-taking is key to this sort of empathy.  Nicholas Epley and Eugene Caruso describe things this way:

The ability to intuit another person’s thought, feelings, and inner mental states is surely among the most impressive of human mental faculties.  Adopting another’s perspective requires the ability to represent the self as distinct from others, the development of a theory of mind to realize that others have mental states in the first place…and explicit recognition that others’ mental states and perceptions could differ from one’s own.  Humans appear to be born with absolutely none of these capacities but instead develop them during the first few years of life.  Developing these perspective-taking abilities appears critical for many good things in social life, from empathy, to cooperation, to possible acts of altruism.  Not all humans develop these skills to equivalent degrees, and those who do not develop these skills to any degree are among the most puzzling (and occasionally horrifying) members of society as they look perfectly human but act completely unhuman.[i]

 

Like any of our capacities, our perspective-taking capacity can be underdeveloped or badly used.  We can fail to engage in perspective-taking when we ought to engage in it, and we can make many errors when we try to understand what is going on with others.  The empathy of interest to me depends upon perspective-taking.  And accurate perspective-taking, in turn, depends upon breaking free of egocentric bias.

 

There are two very different sorts of questions that researchers can ask when working to elicit empathy in their subjects.  They can ask subjects to think how they would feel if they found themselves in another person’s situation.  This sort of question, notice, leaves things entirely in the purview of the self.  Alternately, they can ask people to imagine how the other person feels.  This sort of question shifts the focus from the self to the other.  Daniel Batson calls efforts to imagine how things would be for me in your situation the ‘imagine-self perspective’ on your circumstances.  He calls the request to think how things are for you the ‘imagine-other’ perspective.[ii]  It turns out that these two forms of perspective-taking yield dramatically different results.  The difference is so dramatic that the self-perspective orientation may not count as empathetic at all.  Batson describes the difficulty with an example:

When the other’s situation is familiar or clear, imagining how you would feel in that situation may not be needed for sensitive understanding and may even inhibit it.  Hearing that a friend was recently ‘dumped’ by a romantic partner may remind you of your own experience last year when you suffered the same fate.  You may get so caught up reliving your own experience that you fail to appreciate your friend’s pain.  Especially if you found it easy to rebound, you may contrast your own experience to that of your friend, who is struggling.  Rather than sensitive understanding and empathetic concern, you may respond with impatience and judgment.  The role of an imagine-self perspective in evoking empathy is, then, indirect at best.[iii]

 

In Batson’s review of relevant research, there is significant evidence that subjects engaging in imagine-self perspective-taking show patterns of neurological activity importantly different from the sort characteristic of subjects engaging in imagine-other perspective-taking.  The two groups think differently, feel differently, and exhibit different patterns of neurological activity.  In effect, imagine-self perspective taking does nothing to disturb the egocentric bias so characteristic of our kind.

 

[i] Nicholas Epley and Eugene Caruso, “Perspective-Taking: Misstepping Into Others’ Shoes,” in Keith Markman, William Klein, and Julie Suhr, editors, Handbook of Imagination and Mental Simulation, (New York: Taylor & Francis Group, 2009), p. 297.

[ii] Daniel Batson, “Two Forms of Perspective-Taking: Imagining How Another Feels and Imagining How You Would Feel,” in Keith Markman, William Klein, and Julie Suhr, editors, Handbook of Imagination and Mental Simulation, (New York: Taylor & Francis Group, 2009), pp. 267-279.

[iii] Daniel Batson, “Two Forms of Perspective-Taking: Imagining How Another Feels and Imagining How You Would Feel,” p. 268.

 

Tomorrow, June 7: Barriers to Empathy


 

Candace Vogler is Professor of Philosophy at the University of Chicago and a Principal Investigator on ‘Virtue, Happiness, and the Meaning of Life’, a project funded by the John Templeton Foundation. She is also the Chair in Virtue Theory, a joint appointment with the Jubilee Centre and the Royal Institute of Philosophy. 

Empathy and Self-Transcendence

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“Empathy” | Photo by Sarah Barker.

Note: This is part 1 of a 3-part series “Perspective-Taking, Empathy, and Self-Transcendence” based on a talk at the University of California, San Diego by Candace Vogler in June 2018 for WISDOM, COMPASSION, AND LONGEVITY.

 

Introduction

Some colleagues and I are in the process of bringing a grant project to a close.  The project has given all of us a chance to think together about the relationship between working to be a good person, leading a meaningful life, and being happy.  These three need not coincide.  I could be working hard to deliver medical supplies, food, and drinking water to refugees in desperate circumstances.  I am helping set up a clinic in their camp, say.  New people keep arriving, fleeing the genocidal violence across the border.

 

Chances are that I have a strong sense of purpose.  There is meaning in the life I’m leading.  Chances are that I am a reasonably good person.  On some understandings of the term ‘happiness’—the sort associated with having a happy birthday, say, or a happy holiday—I am probably not particularly happy. But there is a kind of happiness I might have even in the camp.  I might get a profound sense of satisfaction from my work.  I might be exultant if we are able to save the lives of people who are half-dead when they arrive.  And I might be cheerful.  If profound satisfaction and the ability to maintain some balance and some capacity for joy amid immense struggle is what we mean by ‘happiness,’ then I am happy.

 

Our grant project was not explicitly directed to the situation of humanitarian aid workers and those who need the help they bring. We were mostly thinking about ordinary people who understand themselves as belonging to a middle class in places like North America.  We wanted to understand what might be involved in finding meaning and real satisfaction in leading ordinary lives in the kinds of extraordinarily fortunate circumstances middle class people around these parts enjoy.  We argued—in various ways, across various academic disciplines—that the key to bringing together efforts to be a good person, deep satisfaction, and a strong sense of meaning in one’s ordinary life was to be oriented to some good larger than one’s own success and the welfare of members of one’s circle.  Being entirely oriented to my own success, my own pleasures, my own comfort, my own prospects, is not a recipe for leading a good life.  It does not become a recipe for leading a good life even if I extend the sphere of my primary concern to cover the pleasures, comfort, security and prospects of my friends and family.  Finding meaning in my life, finding my life profoundly satisfying, putting my efforts to be a good person in their proper place—these things require being alive to participating in a good that goes beyond me and mine.

 

There are many ways that this can happen.  I can understand my life in the context of a multigenerational family that began long before I was born and will, with any luck, continue long after I die.  I inherited the benefits of the struggles of my ancestors.  I want to carry the good forward for my descendants—people I will never meet, whose names I will not know, but whose lives grow out of the life I lead.  Or perhaps it is like this—I work toward environmental sustainability, or I am devoted to social justice, or my religious faith animates my sense of my world and our place in it.  Lots of roads are made of good larger than the worldly gains of me and mine.  Following any of those roads can amount to living a life where ordinary things are meaningful, where life is deeply satisfying even when it is not much fun, and where the ordinary ethical struggles I face are worth the courage and effort it takes to begin to remedy my own failings.

 

One way of putting the central insight that animated our grant project, then, is this—to lead a life that is good in three senses—successful, satisfying, and ethically sound—we must break the spell of selfishness.  Breaking the spell of selfishness is not easy.  I will focus on one of the ways that we can loosen the hold of what Immanuel Kant called ‘the dear self’ today.  I will talk about the variety of compassion at issue in empathy.

 

Tomorrow, June 6: Empathy and Shifting Perspectives


Candace Vogler is Professor of Philosophy at the University of Chicago and a Principal Investigator on ‘Virtue, Happiness, and the Meaning of Life’, a project funded by the John Templeton Foundation. She is also the Chair in Virtue Theory, a joint appointment with the Jubilee Centre and the Royal Institute of Philosophy. 

Elizabeth Anscombe on Living the Truth

We are pleased to share this video of a recent lectured delivered by our co-PI, Jennifer Frey, here at the University of Chicago under the auspices of our institutional partner, The Lumen Christi Institute.

 

Here is the abstract associated with Professor Frey’s talk:

Elizabeth Anscombe was one of the most formidable and influential analytic philosophers of the twentieth century.  One of the last lectures she delivered was titled, “Doing the Truth.”  In it, she sets out to identify and clarify a specifically practical mode of truth as the proper goal of a specifically practical mode of reasoning and knowledge.  This talk explores how Anscombe understands practical truth by relating it to her influential theory of action; its ultimate suggestion is that “living the truth” just is living a good human life–i.e., knowingly performing actions in accordance with true judgments of right practical reasoning. The person who achieves such truth is virtuous and lives well.