Social Science Bites

Sheila Jasanoff, the Pforzheimer Professor of Science and Technology Studies at Harvard University’s John F. Kennedy School of Government, is a pioneer in the field of STS. That acronym can be unpacked as either ‘science and technology studies’ or ‘science, technology and society.’ Jasanoff -- who describes herself as a sociologist of knowledge and a constructivist, trained in law, working in the tradition of the interpretive social sciences – is content with either use. “I think that represents two phases of the same field,” she tells interviewer David Edmonds in this Social Science Bites podcast. “First of all, it’s the field that looks in detail at the institutions of science and technology and asks, ‘What are they like?’ ‘What does it feel like to be doing them?’ ‘What do they operate like as social institutions, as cultures, as formations in society?’ The other face of STS – science, technology and society – is more about how science and technology function when they get out into the world at large.”

Amid that expansive view, some areas, of course, particularly interest Jasanoff. “The more interesting turn,” she details, “was the turn that tried to occupy the territory previously given to philosophy of science, and started asking sociological and political questions about it.”

One such question is the eternal “What is truth?” STS, a brash newcomer, took on the inquiry with gusto.

“It took a kind of arrogance, if you will, certainly a bravery, in the 1970s, to say that, ‘Hey, truth isn’t just out there. It’s not just a Platonic thing and we try to approximate it. We can actually study truth as if it was a social production.’ That,” she explains, “was the heartland of science and technology studies.”

In the interview, Jasanoff outlines how science is often presented as a capital-T repository of Truth even in an age where the ‘death of the expert’ has become a common trope.

Citing the pandemic and how scientific advice changed on mask wearing, Jasanoff argues that “people should not be surprised that in crisis mode the way we know things changes and therefore the advice may change. Science has been sold as a bill of goods for so long that it is the Truth, it is reliable, a fact is always fact the moment we assert it, that these sorts of commonsensical things that we ought to understand have become difficult for people to grasp.” (Jasanoff’s own research often looks at cross-national differences in her research, and after looking at mask-wearing in 16 nations she reports that “only in America has it become an article of faith – are you for science or against science” – based on your mask usage.)

Remember, she continues, “The expert is not an embodiment of scientific fact. An expert is a particular kind of person who is qualified in particular ways, and every time we say ‘qualification,’ something about the English language or about language in general, forces us to look at the skills that allow one to be considered qualified.

“In fact, we should look at the external periphery of the qualification; a qualification sets boundaries on what you know, but it also sets boundaries on what you don’t know.” Expertise is this double edged-thing.”

Jasanoff is the founder and director of Harvard’s Program on Science, Technology and Society. She’s the author of several books aimed at both the academy and the public, such as 1990’s The Fifth Branch: Science Advisers as Policymakers, 2012’s Science and Public Reason, and Can Science Make Sense of Life? in 2019.

The University of Bergen, acting for the Norwegian Ministry of Education and Research, awarded her the Holberg Prize in March. That was the latest in a slew of honors for her research, including the University of Ghent Sarton Chair and the Reimar Lüst Award from the Alexander von Humboldt and Fritz Thyssen Foundations, a Guggenheim fellowship in 2010, and in 2018 the Albert O. Hirschman Prize from the Social Science Research Council. She is an elected foreign member of the Royal Danish Academy of Sciences and Letters, and a fellow of the American Association for the Advancement of Science, where she served on the board of directors.

Direct download: Jassanof_MixSesMwav.mp3
Category:general -- posted at: 12:16pm PDT

Any work in social and behavioral science presumably – but not necessarily immediately - tells us something about humans in the real world. To come up with those insights, research usually occurs in laboratory settings, where the researchers control the independent variables and which, in essence, rules out research ‘in the wild.’

Enter John List.

“For years,” he tells interviewer David Edmonds in this Social Science Bites podcast, “economists thought that the world is so ‘dirty’ that you can’t do field experiments. They had the mentality of a test tube in a chemistry lab, and what they had learned was that if there was a speck of dirt in that tube, you’re in trouble because you can’t control exactly what is happening.”

Since this complex real world isn’t getting any cleaner, you could conclusively rule out field experiments, and that’s what the ‘giants’ of economics did for years. Or you could learn to work around the ‘dirt,’ which is what List started doing around the turn of the millennium. “I actually use the world as my lab,” the Kenneth C. Griffin Distinguished Service Professor of Economics at the University of Chicago says.

Since an early start centering on sports trading cards and manure-fertilized crop land (real field work, a self-described “bucolic” List happily acknowledges), his university homepage details a raft of field experiments:

“I have made use of several different markets, including using hospitals, pre-K, grammar, and high schools for educational field experiments, countless charitable fundraising field experiments to learn about the science of philanthropy, the Chicago Board of Trade, Costa Rican CEOs, the new automobile market, coin markets, auto repair markets, open air markets located throughout the globe, various venues on the internet, several auction settings, shopping malls, various labor markets, and partnered with various governmental agencies. More recently, I have been engaged in a series of field experiments with various publicly traded corporations—from car manufacturers to travel companies to ride-share.”

In the podcast, List explains, “I don’t anticipate or assume that I have a ‘clean test tube,’ but what I do is I randomly place people into a treatment condition or a control condition, and then what I look at is their outcomes, and I take the difference between those outcomes. That differences out the ‘dirt.’

“I can go to really dirty settings where other empirical approaches really take dramatic assumptions. All I need is really randomization and a few other things in place and then if I just take the simple difference, I can get an average treatment effect from that setting.”

His work – in journal articles, popular books like The Voltage Effect and The Why Axis, in findings applied immediately outside of academe – has earned him widespread praise (Gary Becker terms his output as “revolutionary”), a huge list of honors, and a recurring spot on Nobel shortlists.

For this podcast, List focuses on two of the many areas in which he’s conducted field experiments: charitable giving and the gig economy.

He describes one finding from working with different charities around the world over the last 25 years on what works best to raise money. For example, appeals to potential donors announcing their money would be matched when they gave, doubling or tripling a contribution’s impact. When he started, it was presumed that the greater the leverage offered by a match, the more someone would give, since their total gift would be that much greater.

“There was no science around it … it was art, or gut feeling.” It was also wrong.

List tested the assumption, offering four different appeals to four different groups: one with just an appeal for funding, one with a 1:1 match, one with a 2:1 match, and the last a 3:1 match. And the results bore out that matching a contribution amped up the results – but the leverage didn’t matter. “Just having the match matters, but the rate of the match does not matter.”

List was later the chief economist with ride-share behemoth Uber – and then with its competitor, Lyft. He coined the term Ubernomics for his ability to manipulate the tsunami of data the company generated. “It’s not only that you have access to a lot of data,” he says, “it’s also that you have access to generating a lot of new data. As a field economist, this is a playground that is very, very difficult to beat.”

Direct download: List_MixSesM.mp3
Category:general -- posted at: 5:23pm PDT

Kathelijne Koops, a biological anthropologist at the University of Zurich, works to determine what makes us human. And she approaches this quest by intensely studying the use of tools by other species across sub-Saharan Africa.

“Look at us now …” she tells interviewer David Edmonds in this Social Science Bites podcast. “We are really the ultimate technological species. And the question is, ‘How did we get to where we are now?’ If we want to know why we are so technological, and how do we acquire tool-use skills, etc., it’s really interesting to look at our closest living relatives, chimpanzees and also bonobos.

“Why do, or don’t they use tools, and what do they use tools for, and what environmental pressures might influence their tool use.”

So Koops has been studying, first as a grad student and now as director of her own lab, the Ape Behaviour & Ecology Group at the University of Zurich, several groups of wild apes. (Chimps and bonobos, along with orangutans and gorillas, are labelled as great apes, and with humans, are members of the family Hominidae.) She also directs the Swiss National Science Foundation-funded Comparative Human and Ape Technology Project, which looks at ecological, social and cognitive factors on the development of tool use.

In this interview, Koops focuses on two decades of work she and her team conducts, along with Guinean collaborators from the Institut de Recherche Environnementale de Bossou, in the Nimba Mountains in the southeastern portion of the West African country of Guinea. The field site is remote, and work takes place in 10-day shifts at one of two camps. Researchers gather data on the chimps during daylight hours – if the chimps cooperate. “If the chimpanzees want to get away they can,” Koops details, “so even though we’ve worked there a long time you cannot follow them all day like you can at some other study sites.” The researchers also use motion-triggered cameras near well-trod areas  – the humans dubbed them “chimpanzee highways” – where the chimps frequent.

Among the tool-using behaviors Koops has seen in the study group is seeing these chimps use long sticks to dig up ants for a snack without being devoured themselves, and using stones and branches to open up fruit casings. What this group doesn’t do, she continued, is use “percussive techniques” to open up edible nuts, even though another population of chimps a few kilometers away does exactly that.

To see if it is opportunity or is it necessity that spurred tool use and tool evolution, Koops’ team “cranked opportunity up by a million” by scattering lots of nuts that were otherwise less common in the primary forest habitat of the Nimba residents alongside lots of handy stones good for nut-cracking. The result was … not much innovation by the chimps.

“It really seems difficult to innovate on your own,” she comments. “… They really need to see from another chimpanzee how to crack these nuts.” In general, she notes, there’s not much ‘active teaching’ among her subjects but a lot of observation of older individuals.

She cites other experimenters’ similar work on 4- and 5-year-old humans, which in turn saw similar low instances of innovation. While being careful not to overclaim, Koops says “it looks like some of the building blocks of our culture are really already there in chimps.”

Direct download: Koops_MixSesM1.mp3
Category:general -- posted at: 3:00pm PDT

The idea of walking a mile in someone else’s shoes is often trotted out as a metaphor for understanding empathy. The act of imagining someone else’s reactions may be hard, but based on the body of work by George Loewenstein, predicting how -- under varying circumstances -- we might walk in our own shoes may not be all that easier.

Loewenstein is the Herbert A. Simon University Professor of Economics and Psychology at Carnegie Mellon University in Pittsburgh, Pennsylvania. His enormous range of research interests can be boiled down, after a lot of boiling, to applying psychology to economics and, more recently, economics to psychology.

His career as a founder of both behavioral economics and neuro-economics has seen him delve deeply into how we react when our “affective state” is cold – when are emotions are absent and our physical needs are currently met – compared to when our affective state is hot. The latter is when out emotions are active or when our passions, as the old philosophers might term things like things hunger, thirst, pain, sexual desire, are pulling us.

It turns out, as he explains to interview David Edmonds in this Social Science Bites podcast, “when we are in one affective state it’s difficult for us to imagine how we would behave if we were in a different affective state. … The worst mistakes we make are when we are in a cold state, because we just can’t imagine how we would behave if we were in a hot state.”

While this may seem like something we know intuitively (or after years of high-profile experiments by Lowenstein, his frequent collaborator Leaf VanBoven, and others have conducted, several described in this podcast), it’s not something we act on intuitively. “No matter how many times we experience fluctuations in affective states,” Loewenstein says, “it just seems we don’t learn about this. We are always going to mis-predict how we’re going to behave when we’re in a hot state if we’re making the prediction when we’re in a cold state.”

This, in turn, affects the products of people who make predictions (or if you prefer, policy prescriptions) as a profession, he adds, such as economists.

“According to conventional economics, when we make decisions about the future we should be thing about what it is will we want in the future. What all of these results show is that your current state influences your prediction about what you’re going to want in the future; it influences these decisions that we make for the future in unproductive, self-destructive ways.”

Direct download: Loewenstein_MixSesM_1.mp3
Category:general -- posted at: 3:00am PDT

“I tell my students, ‘If somebody utters the sentence that starts with the words, “History teaches us” the rest of the sentence is probably wrong.’ History has no direct lessons for almost anything. Our own age is sufficiently different, sufficiently unique, from what happened in the past that any facile lessons from history are more likely to mislead than to enlighten.”

That series of caveats comes from Joel Mokyr, who, perhaps counter-intuitively, is an economic historian. And in fact, the Robert H. Strotz Professor of Arts and Sciences and professor of economics and history at the Chicago-area Northwestern University shows in this Social Science Bites podcast that there’s quite a bit to learn from history if you keep your expectations in check.

For example, he explains that “the good old days weren’t all that good and that the very best time to be born in human history is today. That sounds hard to believe in an age where we’re all running around with face masks and facing quarantine, but it’s still true.”

For his own part, Mokyr tells interviewer Dave Edmonds, “I use economics to understand history, and I use history to understand economics.” Mokyr’s ties to economic history are deep: he was president of the Economic History Association in 2003-04, spent four years in 1990s as senior editor of the Journal of Economic History, was editor-in-chief of the Oxford Encyclopedia of Economic History, and is currently editor-in-chief of the Princeton University Press Economic History of the Western World series of monographs.

From that perch, he explains, presumably with a smile, that his peers work with ‘expired data.’ Economic historians “scour the past looking for large data sets that we can use in some way to make inferences. The issue of causality becomes somewhat of an obsession in economics these days, and economic history is very much a part of this.”

In this interview, Mokyr details how the improvement in the human condition he cited above is connected to the Industrial Revolution. “The Industrial Revolution is particularly important because that’s where it all started -- before 1750 almost nowhere in the world were living standards approaching anything but miserable and poor.”

Economic activity before the year 1750 was mostly the story of trade, he explains, while after 1750, it became the story of knowledge. “The Industrial Revolution was the slow replacement of trade and finance and commerce by another thing, and that is growing knowledge of natural phenomena and rules that can be harnessed to material welfare of people.”

To demonstrate this approach, he offered the example of steel. While it has been made for centuries it wasn’t until 1780 that anyone knew roughly why  this alloy of iron and carbon resulted in such a useful metal, and therefore could exploit its properties more by design than by chance. “If you don’t know why something works,” Mokyr said, “it’s very difficult to improve it, to tweak it.”

Mokyr’s scholarship has earned him a variety of honors, including the biennial Heineken Prize by the Royal Dutch Academy of Sciences for a lifetime achievement in historical science in 2006. He has also written a number of prize-winning books, including The Lever of Riches: Technological Creativity and Economic Progress, The Gifts of Athena: Historical Origins of the Knowledge Economy, and most recently, A Culture of Growth.

Direct download: Mokyr_MixSesM.mp3
Category:general -- posted at: 8:20pm PDT