News from Division of the Humanities and Social Scienceshttps://www.hss.caltech.edu/news-and-events/news2024-03-20T21:39:00+00:00Division of the Humanities and Social Sciences Staffquestions@hss.caltech.eduCopyright © 2024 California Institute of TechnologyWhen Does the Brain Process Reward and Risk?2024-03-20T21:39:00+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/when-does-the-brain-process-reward-and-risk<p data-block-key="7idkv">Imagine that you are considering buying stock in a company. You know what its current value is, and you suspect that you could make a healthy return on your investment. But this stock is very volatile: some days up, some days down. Yes, you could make a lot of money, but you could also lose a lot of money. There is a clear reward, but also a lot of risk.</p><p data-block-key="5jsra">Many decisions are like this. The can of tomato paste on clearance at the grocery store is a fantastic bargain if it has not gone bad, but if it has, you have thrown away your money.</p><p data-block-key="6q43n">Decisions like these are a classic situation considered by economists. New research from the lab of John O'Doherty, Caltech's Fletcher Jones Professor of Decision Neuroscience and an affiliate faculty member of the <a href="https://neuroscience.caltech.edu/">Tianqiao and Chrissy Chen Institute for Neuroscience</a>, aims to understand how the brain implements these kinds of decisions by testing a computational model that proposes how representations of reward and risk are built from experience. The neural processing of reward and risk was <a href="https://www.jneurosci.org/content/28/11/2745.short">previously studied at Caltech</a> via a technique called functional magnetic resonance imaging (fMRI), which measures changes in blood flow inside the brain. Researchers found that a region of the brain called the anterior insula is activated when people assess risk and process uncertainty.</p><p data-block-key="7i9v6">In a new study, electrodes implanted deep within the brains of patients (for unrelated therapeutic purposes) allowed O'Doherty and his team to obtain even more precise measurements of brain activity during decision-making. The work revealed that, as expected, the so-called reward prediction error (the difference between the expected value and the observed value) appears first and is followed by the risk prediction error (the difference between the expected uncertainty and the actual uncertainty), which relied on the same neural processes as the reward prediction error. Both signals were found in the anterior insula. These findings suggest that the reward prediction error is used to calculate the risk prediction error, which can then be used to learn to assess riskiness, which is a necessary guide to decision-making.</p><p data-block-key="2ttt2">The work was published in the March 9, 2024, issue of <i>Nature Communications</i>.</p><p data-block-key="56q40">Vincent Man, a senior postdoctoral scholar research associate in neuroscience and a co-author of the paper, explains: "fMRI is great at telling us where in the brain something is happening, but it is limited in terms of telling us <i>when</i> things happen, at least on the fast timescales at which we think these neural processes unfold."</p><p data-block-key="a8m9j">For this study, patients being evaluated for epilepsy were recruited at the University of Iowa Hospitals and Clinics. To monitor their seizure activity, these individuals had electrodes implanted deep in key regions of their brain, including in the anterior insula, which allowed researchers to detect neural activity at a microsecond timescale that is not possible with fMRI.</p><p data-block-key="a06hc">Then, the participants played a very simple card game using 10 playing cards numbered from ace to 10, with the ace counting as one. They were asked to predict, sight unseen, if the second card would be higher or lower in value than the first card. Since neither card was visible, this was always a completely random guess. After the first card was shown, participants would get some information about how accurate their guess might be. For example, if they predicted that the second card would be lower, and the first card was a 10, they would know immediately that their guess was correct. If the first card was an ace, they would know they were wrong. But if the first card was a five, the outcome remained uncertain until the second card was revealed.</p><p data-block-key="1chcm">"Basically, with this game we are drawing an arc from no uncertainty to maximal uncertainty," explains Man, who works in O'Doherty's lab. "The computational model predicts that you make one computation and form an expectation about risk. When you see card two, there is a second computation to assess the expected risk." The computations used to make these predictions are identified as the reward prediction error (RePE)—the process of updating between an expected reward and an observed reward (the actual card drawn), and the risk prediction error (RiPE)—the process of assessing the expected risk with respect to the observed risk.</p><p data-block-key="cjr4k">Activity detected in the anterior insula during these games showed exactly this two-step process following the display of card two: reward prediction evaluation first, followed by risk prediction error evaluation.</p><p data-block-key="8rhae">"We're validating a theoretical idea about the relationship between reward and risk and how they relate to each other," Man says. "The fact that the neural signature is consistent with the theory is nice; it grounds the theory."</p><p data-block-key="7q5as">O'Doherty adds: "Determining how the brain generates these kinds of computations can help us ultimately build more accurate models of how the brain learns and make decisions, which could be useful not only for understanding how the brain works in general, but also, potentially, for understanding how these processes might go wrong in diseases such as problem gambling, addiction, or other psychiatric disorders."</p><p data-block-key="9t91e">The <a href="https://www.nature.com/articles/s41467-024-46094-1">paper</a> is titled "Temporally Organized Representation of Reward and Risk in the Human Brain<i>.</i>" The authors are Man, O'Doherty, and Jeffrey Cockburn of Caltech; Oliver Flouty of the University of South Florida; and Phillip E. Gander, Masahiro Sawada, Christopher K. Kovach, Hiroto Kawasaki, Hiroyuki Oya, and Matthew A. Howard III of the University of Iowa.</p>Mechanism Design: An Interview with Axel Niemeyer2024-03-08T15:11:42.085271+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/interview-with-Axel-Niemeyer<p data-block-key="7idkv"></p><p data-block-key="2quia">Assistant Professor of Economics Axel Niemeyer, who joined Caltech last summer after completing doctoral work at the University of Bonn, specializes in mechanism design, a subfield of economic theory. Mechanism design helps economists create rules and procedures for achieving desirable social or economic goals in different types of economic situations. Central to the theory is the observation that information and the resources needed to achieve economic goals—which might be the maximization of social welfare, efficiency, or fairness—are often spread across individuals who pursue their own independent interests. The rules must then be designed to coordinate these different interests in a way that is beneficial to the broader goal. We recently sat down with Niemeyer to discuss his research in the field.</p><p data-block-key="2rsg2"><b>What is mechanism design?</b></p><p data-block-key="b197v">Often, when we do research in economics, we look at particular economic institutions, by which we mean all the rules and procedures that influence how individuals interact and decide in economic situations. We might explore, for example, how regulations affect trade and production in a market or how an income tax system affects people's labor decisions. Then we gather data and write theories about how these institutions work or when they might fail.</p><p data-block-key="3f9v9">Mechanism design is a theory that asks the opposite question. Instead of asking how existing institutions work, mechanism design invites us to imagine all possible institutions—all the possible ways people can trade or sell at auction, for example, or all the ways we could run an election. Then we model how individuals would interact within these hypothetical systems based on the rules and procedures we devise. Out of all these possibilities, we aim to identify an institution—a mechanism—where individuals interact in ways that align best with a broader social or economic goal.</p><p data-block-key="4cs0d"><b>Can you give an example?</b></p><p data-block-key="5reik">Yes, we can look at the example of an auction. We're trying to understand what, given the rules of the auction, people will bid if they are strategic about what they are doing. Imagine that we are running what's called a first-price auction: Everyone submits their bid in a sealed envelope, the highest bidder wins, and they pay the amount of their winning bid. In this scenario, let's say that I'm willing to spend $10. But if I can get the item for less than $10, that's better. I don't know how other people value this item; they're not sharing that information with me. So, thinking strategically, I have to weigh my options: If I bid more, I'm more likely to win the auction, but I may be paying more than I actually have to.</p><p data-block-key="pq64">Now imagine instead that we change the format to a second-price auction. If I win, instead of paying my own bid, I pay the amount of the second highest bid. Here the strategic thing for me to do is no longer to hide the amount that I'm truly willing to spend, but to bid that amount, my true valuation, outright.</p><p data-block-key="dm3sf">Something similar happens in elections if you vary the rules of how people can vote. If I'm only allowed one vote that goes to one candidate, I may think, "I really like candidate A, but I don't believe they can win the election. So maybe I should vote for candidate C instead." But we can imagine changing the rules for voting, perhaps allowing votes for multiple candidates. Then we can predict how this will change people's choices, and ultimately, the election's outcome.</p><p data-block-key="4nns9"><b>Are you empirically testing these different formats, say for auctions or for voting?</b></p><p data-block-key="epqvk">It makes me really happy to see these theories getting tested empirically! That's not what I do though. I'm more of a theory person. We're trying to figure out, for a given economic situation and a given social or economic goal, what might be the best format to use.</p><p data-block-key="4j0qr">Maybe you're an auctioneer who wants to maximize your revenue. What would be the optimal rules for an auction in this case? Or maybe you're an auctioneer who values efficiency: You want the goods to go to the people who can make the best use of them. If the government is running an auction to sell public assets, this may be the goal. Or if you're looking at rules for voting, maybe you want the winner to truly represent the population's preference.</p><p data-block-key="31m1p"><b>Is it correct to say that you are working with a mathematical system that is sufficiently abstract that you can plug in either profit values, or efficiency values, or normative values like fairness?</b></p><p data-block-key="bhvpt">Exactly. Part of the beauty of the theory is in its flexibility; we remain agnostic about what these goals or values should be. No matter the objective, we can try to design an institution that gets at the goal most closely.</p><p data-block-key="14jd5">A key concept in this approach is what we call an equilibrium, where if everyone follows a particular strategy, no one will have an incentive to try a different strategy. It's our forecast of what's likely to happen based on the rules we've set, considering what everyone knows and wants. Take the second-price auction as an example: Our equilibrium prediction is that people will bid their true valuation for the item. This way, if our goal is to ensure that the item goes to the person who values it most, the second-price auction does that for us, without us needing to have any idea about people's valuations upfront. Should we aim for a different goal, the ideal auction design might look quite different.</p><p data-block-key="7m1o5"><b>Is equilibrium a situation in which everybody feels they have been treated fairly?</b></p><p data-block-key="5fpqi">No, an equilibrium doesn't necessarily need to be fair. It only means that given what everyone else is doing, you can't choose a different strategy that will improve your situation.</p><p data-block-key="aflab"><b>Is there a specific problem you are working with now?</b></p><p data-block-key="eol4i">Yes, a key idea in mechanism design is that we can achieve better outcomes by arranging side payments between the involved parties. For example, in elections with two options, the majority wins, but the majority might care very little about the candidate or the issue while the minority might care a huge amount. This can be an inefficient outcome, which we could overcome, at least in principle, using monetary transfers.</p><p data-block-key="4ood2">But in many settings, we can't make these kinds of transfers, either for ethical reasons, legal reasons, or just practical reasons. This is certainly true with elections, but also in many other scenarios. I'm interested in how we can attain efficiency in a variety of settings. For example, how can we ensure that essential goods and services reach those who genuinely need them most, or allocate limited funds within organizations effectively?</p><p data-block-key="9fp5m">If you can't make or ask for payments, you have to find other ways to get people to reveal their true preferences and valuations—to not exaggerate or falsify what they really need. This might mean closely examining the claims people make, which can be a costly and time-consuming task. Then it's all about figuring out which claims to scrutinize and how thoroughly. Alternatively, we may utilize community knowledge. This is done in peer review for academic conferences or when targeting financial aid or credit to people in rural communities. Again, we must be careful of any strategic gaming this might invite. Another angle is to consider the repeated nature of many interactions. For example, if someone passes up on claiming resources today, signaling they're not in urgent need, we can promise to prioritize their needs in the future. This way, we can better identify those in need today.</p><p data-block-key="dvtk6"><b>But people do not know their own truth much of the time. You may know better than I do where the trade-offs are, and what the best choice is for me.</b></p><p data-block-key="dqndr">That's a great point. We all make mistakes sometimes or believe in erroneous facts. Or we might not pay enough attention to all the information out there. This raises interesting normative questions: Should the designer, if they think they know better, override people's preferences? Or should we stick to trying to figure out what people want, even if it seems like they're a bit off track?</p><p data-block-key="fg48b">It is the philosopher's job to answer that. As economists, we just say, give me the inputs: What is the economic situation? What is your goal? You can tell me what you want, and in principle, I can model the situation and try to solve the equations that will optimize the system for that.</p>Confidence (Or Its Absence) Is Contagious2024-03-06T21:55:03.420193+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/confidence-is-contagious<p data-block-key="7idkv"></p><p data-block-key="3jurv">New research by Caltech's Kirby Nielsen, assistant professor of economics and William H. Hurt Scholar, shows that the gender gap in confidence that is often held responsible for women's underachievement in the workplace is "contagious"; that is, when evaluating a worker's performance based on self-assessments, reviewers will reward apparent self-confidence—and conversely, penalize a lack of confidence—rather than focusing solely on performance.</p><p data-block-key="9615k">Think of it like this: You have been in your current job for three years, and you could really use a pay increase. Your performance reviews are good, and you are well within your rights to ask for a raise. Do you?</p><p data-block-key="2mvc7">Many factors influence a decision like this, but one, unquestionably, is gender. If you are a man, you are statistically more likely to reason that you're doing quite well at your job and deserve more money, and you will approach your boss with just this attitude: "It's time for a raise, and maybe a promotion too."</p><p data-block-key="71do5">But if you are a woman? You are statistically more likely to recall the "room for improvement" notes from your last performance review and imagine your colleagues are all performing better. You decide that your boss will offer a raise when you deserve it. Or, you may ask your boss for a raise, but when you do, you are hesitant, apologetic: "I shouldn't bother you, but do you think maybe it's time for me to get a raise?"</p><p data-block-key="iif6">One potential consequence of this so-called "confidence gap" is predictable: Even when equally performing, equally trained women and men are present in the workplace, on average men are paid more and have greater upward mobility than women.</p><p data-block-key="45npi">For some time, the standard advice given to women to rectify this problem was to "lean in," a slogan made popular by the 2013 book of the same title by Sheryl Sandberg, formerly the chief operating officer of Meta Platforms. Lack confidence in your own worth in the workplace? Lift a page from the careers of more successful men. Value yourself. Tell others they should value you. Nurture your self-confidence and, in the meantime, fake it as best you can, and the rewards will follow.</p><p data-block-key="c2tvh">Some have objected to this advice, believing the onus should be on employers to realize that women and men assess their own performance differently, and that self-reports should be read through this interpretive lens. "Many people know about the confidence gap," Nielsen reasons. "If I, as an employer, think about how people communicate, I might be able to realize that men and women communicate differently about their performance on average. If my male employee is saying he's amazing, maybe I should tone that down a bit in my mind. If my female employee is saying she's OK, maybe I should consider that an understatement."</p><p data-block-key="f7g5g">To shed some light on these questions, Nielsen crafted an experiment. Participants were recruited and assigned randomly to two categories: workers and evaluators.</p><p data-block-key="2nuo">The workers were given a 10-question math and science quiz. "We incentivized them to do their best by paying them more for each correctly answered question," Nielsen explains. This quiz was followed by 17 self-assessment questions, also incentivized: The closer participants got to their actual test scores in their self-assessments, the more they were paid. False modesty was not rewarded.</p><p data-block-key="eqrpm">One set of questions focused on the participant's absolute performance: Did they answer at least three questions on the test correctly? Another group of questions measured relative performance: Do they think they scored in the top half among everyone who took the test?</p><p data-block-key="creer">Finally, some questions were directed toward subjective beliefs about performance: Do they think another person would describe their performance on this test as evidence of poor skills in math and science?</p><p data-block-key="fc4sn">This first stage of the experiment yielded the expected confidence gap. Male and female participants' actual test scores landed in the same range; there was no difference by gender. But on the 17 measures of confidence, significant differences appeared. "On every single one of the self-assessment questions, women report more pessimistic beliefs about their performance than men," Nielsen notes. "Basically, we replicated the expected finding that there is a gendered confidence gap between equally performing individuals."</p><p data-block-key="7s1f6">Next, in the second part of the experiment, the evaluators stepped in. How would they react to these differences in confidence between the workers whose results they viewed?</p><p data-block-key="bnlgo">Evaluators were first presented with a random worker whose gender was specified but about whom nothing else was known. The evaluators were asked to guess the percentage chance that this worker's performance was poor. Evaluators gave similar guesses about performance for any random person, whether male or female. This eliminated the possibility of what Nielsen calls "taste-based discrimination"; that is, evaluators do not arrive at their task already believing that women are more likely to perform poorly on a math and science quiz.</p><p data-block-key="tuif">Then the evaluators were presented with the worker's self-assessments and were again asked to specify a percentage chance that this worker's performance was poor. Here, Nielsen says, "women's relative lack of confidence was shown to be contagious. It causes other people to now conclude that women performed worse."</p><p data-block-key="eev3">To test evaluators' prior familiarity with the gender gap in confidence, they were asked to guess workers' likelihood of being overconfident or lacking confidence. The evaluators guessed—accurately—that male workers were more likely to be overconfident and female workers were more likely to be lacking in confidence, indicating that they did know about the confidence gap. However, even being asked these questions did not help the evaluators recognize the influence of confidence in workers' self-reports.</p><p data-block-key="8867d">"We thought that maybe if we just asked them about gender and confidence, this would nudge the evaluators to take that into account," Nielsen says. "But that had no effect on their assessments about workers' performance. They continued to guess that women actually performed worse than men after learning about the workers' self-reports."</p><p data-block-key="ddnqa">"What the experiment indicates is that evaluators experienced a type of cognitive bias," Nielsen explains. "They were trying not to discriminate against women but ended up doing so anyway because of the women's pessimistic self-reports, even though they understood that women are typically less confident than men."</p><p data-block-key="7kaau">There are many real-world implications of this research, Nielsen says: "For example, some people think that having gender-blinded applications or reports could rectify gender imbalances. But this research shows that a gender-blinded process might only make the situation worse. Without knowing applicants' or workers' gender, evaluators would not be able to account for the gender gap in confidence even if they wanted to."</p><p data-block-key="1sqor">The cognitive bias uncovered in this research could well apply to other groups, for example, people whose cultural codes lead them to project more humility and less confidence. Nelson's experiment tested to see if evaluators would exhibit the same cognitive bias toward non-gendered groups by telling some evaluators that they were looking not at women and men but at members of "group A" and "group B." The results were the same.</p><p data-block-key="bak4p">Although the findings may be disheartening to people who present with less self-confidence, the good news, Nelson says, is that "we know a lot about cognitive biases, and we know that there are ways we can de-bias people. Evaluators form these biased assessments because they are having a problem incorporating the information they're given, not because they are actively discriminating against women. But this means that interventions to help on this dimension could be very promising."</p><p data-block-key="dnf3e">The paper describing Nielsen's research, titled "The Gender Gap in Confidence: Expected But Not Accounted For," appears in the March 2024 issue of the <i>American Economic Review.</i> Nielsen's co-author is Christine L. Exley of the University of Michigan.</p>Software in Science2023-11-22T00:48:00+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/software-in-science<p data-block-key="7idkv"></p><p data-block-key="1gmep">Computers dominate so many people's lives. Who doesn't log hours of screen time every day on their "phone"—a device that, yes, can initiate or receive telephone calls but mostly serves as a mini-portal to their email, texts, and a whole web of information and entertainment?</p><p data-block-key="7sfh5">For the average person, a key feature of software is its invisibility. It chugs along in the background, rarely perceived (at least until it ceases to function as desired). For scientists, however, background is often foreground. It was scientists, after all, who first developed computing software to carry out routine tasks with an error-free speed previously only imagined.</p><p data-block-key="7j3s4">Today, to a perhaps surprising degree, scientists are still writing their own code. Can we be content with this as a simple observation, or should we regard it as a cause for celebration or dismay?</p><p data-block-key="3jelo">For the Schmidt Academy at Caltech, now entering its fifth year, it's a bit of all of the above. As it is increasingly inefficient to ask scientists to write, maintain, and optimize the code they need for their research, scientists need translators: people who can understand science but whose greatest fluency is in programming languages.</p><p data-block-key="857kf">The Schmidt Academy offers an ingenious intervention to address this dilemma: Recent computer science graduates are invited to Caltech, embedded in science labs for a year or two, and mentored; meanwhile, they bring software engineering best practices to their host research groups—hopefully inspiring all team members to write better code in the process.</p><p data-block-key="fi1j0">Meet Howard Deshong, Schmidt Scholar, recent graduate of Harvey Mudd College, and happy resident in Assistant Professor of Physics <a href="https://www.caltech.edu/about/news/putting-tried-and-true-theories-to-the-test">Katerina Chatziioannou's</a> lab, which analyzes data from the Laser Interferometer Gravitational-wave Observatory (LIGO). "The Schmidt Academy appealed to me because it catered to two of my greatest interests—science and software," Deshong says. "It promised to scratch both those itches and has lived up to that promise."</p><p data-block-key="e7i3r">Since 2022, Deshong has been rewriting the code for <a href="https://sase.caltech.edu/projects/bayeswave.html">BayesWave</a>, a program used to process data from LIGO's detectors in Hanford, Washington, and Livingston, Louisiana. "These detectors change in length as gravitational waves pass through them, warping space-time as described by general relativity," Deshong explains. "The changes are incredibly small—the detectors are kilometers long, and they change in length by less than an atom's width under the influence of gravitational waves—so scientists and engineers have put a tremendous effort into cleaning up noise in the data."</p><p data-block-key="3ji80">BayesWave has been assembled over the past 10 years, almost entirely by LIGO scientists who are, of course, extremely familiar with how the detectors work, the potential sources of extraneous noise, and which patterns of gravitational waves indicate particular types of cosmic events. But the field of gravitational wave astrophysics is expanding rapidly, with more than 100 detections to date. The applications of the code have expanded as new use cases have been conceived and implemented by many LIGO scientists, with more advances yet to come. The load had become, in Chatziioannou's term, "unwieldy." And so she applied to the Schmidt Academy, hoping to bring on a software engineer who could "clean up the baseline stuff"— translating BayesWave from C, a programming language first developed in the 1970s, to C++, its successor—and enabling LIGO scientists to meet the needs of upcoming observations.</p><p data-block-key="5vjmn">Deshong, Chatziioannou points out, "could have learned nothing and just simply taken the existing code and translated it and fixed things." But because Deshong attends lab seminars and can grasp the science that motivates the creation and expansion of the software, he is able to work with a variety of graduate students, postdocs, and other scientists to better serve their data-analysis needs. And if Deshong is overwhelmed by the software engineering required, he can go to his mentor, Donnie Pinkston (BS '98), instructor for the Schmidt Academy. "He's bursting with advice about software design," Deshong says. "He'll either have thoughtful answers at the ready or he'll know where to point me so I can learn more."</p><h3 data-block-key="ee79v">Schmidt Futures</h3><p data-block-key="4dtsv">The Schmidt Academy was funded in 2018 by <a href="https://www.schmidtfutures.com/">Schmidt Futures</a>, a philanthropic initiative founded by Eric and Wendy Schmidt. Mike Gurnis, the John E. and Hazel S. Smits Professor of Geophysics and director and leadership chair of Caltech's Seismological Laboratory, was recruited as director, and the Schmidt Academy was underway.</p><p data-block-key="7mnjl">Four "Schmidt Scholars" came to Caltech in the summer of 2019 to begin work with Pinkston, a Caltech alumnus who has been teaching computer science at the Institute since 2005. With a projected 12 Schmidt Scholars joining the original four in 2020, Gurnis brought on Dave Rumph (BS '80), who had a prior career as software engineer at Xerox's Palo Alto Research Center, where he helped develop the first color laser-printer prototype, among other achievements.</p><p data-block-key="47vhk">It quickly became apparent that graduating Caltech computer science students would not be available to staff all of the Schmidt Academy positions. "A lot of the undergraduates at Caltech are ready to go someplace new when they graduate," says Pinkston, "and they're getting tempting industry offers."</p><p data-block-key="3ia0s">Fortunately, the solution to the dilemma lay only 25 miles east at Harvey Mudd College, the science and engineering college of the Claremont College Consortium. Caltech alumna Katherine Breeden (BS '08), assistant professor of computer science at Harvey Mudd, joined the Schmidt Academy steering committee early on and has since been instrumental in recruiting recent Harvey Mudd graduates to the program at Caltech. Harvey Mudd's computer science graduates have abundant job opportunities in industry, but Caltech is new to them, as is the opportunity to work in such a rich variety of research labs. Both Caltech and Harvey Mudd grads now fill the ranks of each class of Schmidt Scholars.</p><h3 data-block-key="95cvh">Why Scientists Need Software Engineers</h3><p data-block-key="5tbhd">There is no disputing that software is important in the sciences today. As Tapio Schneider, the Theodore Y. Wu Professor of Environmental Science and Engineering and JPL Senior Research Scientist, points out, "In some areas, the entire scientific workflow can be automated. Materials design is one such area. Typically, you conceive of a material, synthesize or assemble it, and characterize and test its properties in a lab. Rinse and repeat. All of that used to be done manually, but now you can automate a lot of it, sometimes all of it, through <a href="https://scienceexchange.caltech.edu/topics/artificial-intelligence-research">AI</a> [artificial intelligence] coupled with automated laboratories."</p><p data-block-key="b9pa6">With processes this complex, scientists must write software—or at least have a deep understanding of what it can and cannot do well—and then successfully communicate about it to others in their lab. As Schneider says, "AI and computing are the new calculus. Similar to how calculus and statistics are fundamental components of the education of scientists and engineers, learning about AI principles and applications should be equally emphasized." Or as Gurnis puts it, "Everything we do in science is dependent upon really good software."</p><p data-block-key="6g84r">Certainly, scientists have a role to play in developing software engineering for their own projects, and, Gurnis says, "Often these advances are quite brilliant." But, predictably, there are limitations. Learning software engineering on top of scientific theories and methods is a big lift. "It's not something you can learn in a month," remarks Chatziioannou. "It's a massive skillset."</p><p data-block-key="fcvpq">Beyond the question of skill is the fact that most labs at research universities such as Caltech have an intentionally high rate of turnover: One of their main goals is to train budding scientists, who are typically only in residence for three to five years. David Van Valen (PhD '11), assistant professor of biology and biological engineering and investigator at the Heritage Medical Research Institute, has hosted three Schmidt Scholars in his lab to date. He says one of the biggest roadblocks for scientists writing software is that "you have one science problem that requires analysis, so you do just enough to solve your one problem—and then the student in charge of that graduates. With each person, with each new problem, the wheel has to be reinvented."</p><p data-block-key="83ul">Rumph paints the picture this way: "Grad students or postdocs get their data. They write it up, they publish it, they get their degree, and they leave. Then some new grad student comes in and wants to extend that work. The PI [principal investigator] says, "Oh, Fred was working on something like that. You should just pick up where he left off. I think it was version 3, or maybe 3A?' There's no documentation, and it doesn't even work anymore. The new student spends a month or two trying to figure out how this software was supposed to work. They tear their hair out, and eventually they say, 'Forget it, I'm going to start over.' And they make all the same mistakes over again as they write new software, and it costs them six months."</p><p data-block-key="cids8">Even without changes in lab personnel, software crafted for a narrow purpose tends not to age well. "Software is not a stable thing," Pinkston explains. "It exists in an environment that's continually moving. The operating system changes, libraries get updated, hardware changes. And what happens is that the code that worked perfectly is useless two years later." Either the software stops working, Gurnis says, "or it is very sophisticated, but it can't be modified to do the latest and the greatest thing that the science needs it to do."</p><p data-block-key="9u64k">"If the software had been modular and acted more like a toolbox, if it was well documented and extensible and had tests in place that made sure it ran," Rumph says, "then they wouldn't have to waste that time." It is these "software engineering best practices," as they are known in the trade, that the Schmidt Academy teaches.</p><h3 data-block-key="oonc">What the Schmidt Academy Offers to Young Software Engineers</h3><p data-block-key="5m5bj">In its first four years of operation, the Schmidt Academy has successfully recruited all of the scholars needed to fill available positions at Caltech, but this is not a trivial undertaking. "Software engineers have many, many opportunities in business and big tech and government. Everyone wants these people," Gurnis says. "What we want to do is funnel some of them, at least temporarily, through research universities."</p><p data-block-key="bb551">Breeden concurs. "A lot of new positions are in areas like security and AI," she says. "Those folks are obviously excited to recruit our students, but there are so many other cool things that you can do with computing too." When recruiting for the Schmidt Academy, Breeden tells students, "If you make a tweak to Kindle software that rolls out to 10 million customers, you have a long lever that affects a ton of people a tiny amount. That's one way of measuring your impact. But with scientific software, you might be working on something more bespoke. Maybe there are only a hundred researchers in the world working in this specific area of, say, cosmology. You could be making a tool that completely transforms their workflow and has an enormous impact on the pace of scientific discovery or on the replicability of their work. It's amazing for somebody in their early 20s to be able to do that." Even more, Schneider says, "Schmidt Scholars are inventing the future of science. They are pioneering a way of doing science that will be common in a few decades."</p><h3 data-block-key="c4998">Matching Scholars to Projects</h3><p data-block-key="4a7si">The Schmidt Academy's steering committee, composed of Schmidt Academy personnel, select Caltech and Harvey Mudd faculty, and a physicist from the Carnegie Institution for Science, considers the matching of scholars and projects to be one of its most important tasks. A call goes out to faculty in November to find out who might be interested in hosting a Schmidt Scholar. Faculty must then apply for Schmidt Scholars by mid-December, and these applications are competitive.</p><p data-block-key="c91ia">Breeden explains that the committee takes several factors into consideration. For one, she says, "you have to have that kind of 'Goldilocks' project size. If it's too broad in scope, it might not be feasible for a scholar to complete the work in a year or two." Second, the lab must include appropriate liaisons: "Dave Rumph will go to the group, interview the PI, and figure out where the latent expertise lies in the lab, whether it's grad students, postdocs, or undergrads," she says. "He's looking for one or two people in the group who can be a bridge between the Schmidt Scholar and the group, because it's all about facilitating that communication." This is key, says Rumph, because "one of the challenges is how prepared the lab is for a software engineer as opposed to a new grad student." Finally, the nature of the project is a consideration. Says Breeden, "We're always looking for projects where it's like 'Wow! If we applied quality software engineering here, it would just be rocket boosters on what they're up to scientifically."</p><p data-block-key="4oto5">Selecting scholars is equally important to the success of the Schmidt Academy. One priority when reviewing applicants is ensuring that they have an adequate background in math and the sciences. "We need software engineers who understand physics, math, biology, chemistry, if that's what they're working on," says Schneider. "They're hard to hire." This is why the Schmidt Academy has so far included only graduates from Caltech and Harvey Mudd, since both colleges require all undergraduates to have a broad exposure to a full range of science disciplines. (There are plans afoot to bring Schmidt Scholars in from additional colleges if they have the necessary background.)</p><p data-block-key="d9tqo">Only then does the matching begin. "The available projects are introduced to the scholars, and they let us know which projects they would like to join," explains Pinkston. Pinkston and Rumph each take on one project after the scholars have been matched as part of their ongoing contribution to the Schmidt Academy. This way both scholars and instructors are going through the same process at the same time, though with reference to different projects.</p><h3 data-block-key="42v11">The Schmidt Academy on the Ground</h3><p data-block-key="35vt3">When new Schmidt Scholars arrive on campus in late July or early August, they have already been assigned to labs and made a commitment for a year's work with the option to continue for a second year. (Most scholars spend two years at Caltech.) The first thing they do is meet their fellow Schmidt Scholars and their mentors, Pinkston and Rumph. This is done via a boot camp run by Pinkston—an intensive version of Caltech's CS 130, a software engineering course offered during winter term. Scholars practice designing and testing small-scale projects. Grad students can also take the class, for credit or not, and those grad students who will be working closely with a Schmidt Scholar are especially encouraged to do so.</p><p data-block-key="enkb3">David Pitt, who just graduated from Harvey Mudd, was excited to begin his Schmidt Scholarship in this past August's boot camp. "I worked full time my senior year in addition to school, and I got a taste of working in industry, so I decided I wanted to try something else for a year," he says. Pitt will be working on an AI project involving "a new breed of neural networks called physics-informed neural networks."</p><p data-block-key="bc0bs">After boot camp is completed, Schmidt Scholars continue to meet every week, taking turns presenting progress on their projects. In addition, they meet individually with either Rumph or Pinkston every two weeks, or more often if needed. As an initial step, the scholars interview members of their lab to learn their software requirements. Then, says Breeden, "they build the scaffolding. They identify deliverables for the first year of work and map out a practical timeline."</p><p data-block-key="6ur0s">Because the Schmidt Scholars are embedded in the labs that will be using the software they develop, "the information exchanges happen on a daily basis," Van Valen says. "Within six months, they know enough about the science to be able to really move forward on the things they've been tasked with."</p><p data-block-key="7l37n">Schmidt Scholars do encounter some challenges that computer science grads rarely confront in industry. "A lot of the scholars are doing 'software archaeology,'" Breeden explains. "They're looking at scientific software packages that might have been written 20 or 30 years ago in languages that we don't teach anymore. They have to become proficient in FORTRAN, for example, or they need to read through flight software from a satellite launched decades ago."</p><p data-block-key="atuq">Schneider's CliMA lab has had four Schmidt Scholars to date, more than any other research group on campus. "We're building an Earth system model that consists of an atmosphere model and a land model, and an ocean model that is mostly being developed at MIT," he explains. These climate models are enormous. "They have millions of lines of code. Really, aside from nuclear codes, these are probably the most complex pieces of scientific software that exist. So, part of what we do is to try to reduce this complexity to what we really need."</p><p data-block-key="8jbcf">Julia Sloan, who graduated from Caltech in 2022 with a degree in computer science, is beginning her second year as a Schmidt Scholar in the CliMA lab. "I'm working on the land model and on the coupler, which is a component of the software that links together the individual pieces of the model—atmosphere, land, and ocean. Once this <a href="https://sase.caltech.edu/projects/climate.html">climate computing project</a> is completed, it will be used for fast and accurate predictions of the global climate for decades or even centuries into the future."</p><p data-block-key="a5d74">"CliMA was an amazing project to work on," says Ben Mackay, an alumnus of the Schmidt Academy. "It's a blend of software, mathematical, and physical problems all simultaneously being solved. It was an incredibly dynamic and collaborative workplace that I feel privileged to have been a part of. My time with the Schmidt Academy certainly confirmed my desire to pursue a PhD in climate science." Mackay is now a PhD student in climate science at the Scripps Institute of Oceanography at UC San Diego.</p><p data-block-key="bpr8d">Opportunities are diverse within the Schmidt Academy and give scholars the chance to pursue multiple interests. "I majored in computer science, but I also took physics classes during my time at Harvey Mudd," says second-year Schmidt Scholar Alex Hadley. "I'm interested in software engineering as a career, but I didn't want to turn away from my interest in physics." Hadley is working on a project called <a href="https://sase.caltech.edu/projects/softwareplatforms.html">Software Platforms for Quantum Experiments</a> that is supervised by Oskar Painter, the John G Braun Professor of Applied Physics and Physics.</p><p data-block-key="9jb4v">Schmidt Scholar Skylar Gering studied computer science and math at Harvey Mudd with an emphasis in environmental analysis. "I really wanted an opportunity to improve my software skills while working on a project that was meaningful to me," Gering says. "I interned with Pacific Northwest National Lab and the National Oceanic and Atmospheric Administration working on scientific software, but since Harvey Mudd is an undergraduate-only institution, I wanted to work in a graduate lab before deciding if I wanted to go to grad school myself."</p><p data-block-key="732bg">Gering's project is focused on <a href="https://sase.caltech.edu/projects/oceansea.html">ocean–sea ice coupling</a>. She explains, "We are seeing rapid decreases of sea ice globally. The biggest decreases are in the marginal ice zone around the edges of the pack. In those areas, the sea ice isn't one big sheet but rather lots of ice floes, which are distinct floating chunks of sea ice. We model these ice floes as polygons to better understand the dynamics in these areas."</p><h3 data-block-key="98kgm">The Contributions of the Schmidt Academy</h3><p data-block-key="5a8gd">Four years in, the Schmidt Academy is a success story, with more and more Caltech faculty eager to bring Schmidt Scholars into their labs. "We usually receive roughly twice as many proposals from faculty as we can support," Kaushik Bhattacharya, Caltech's vice provost and Howell N. Tyson, Sr., Professor of Mechanics and Materials Science, says.</p><p data-block-key="58id3">With several classes of alumni now out in the world, benefits for the Schmidt Scholars are clearly visible. Some have gone on to graduate school in fields ranging from resource management to business to computational biology. Others have moved into industry, and some have been hired on as permanent software engineers at Caltech or other research universities.</p><p data-block-key="druf1">Iman Wahle (BS '20) applied for graduate school at Princeton University directly out of college to study neuroscience. She was admitted but deferred for two years to be a Schmidt Scholar. "I learned so much about software development from the academy while simultaneously learning more about computational methods for analyzing high-dimensional neural data," she says.</p><p data-block-key="8uhti">The ambition of the Schmidt Academy is to transform the relationship between science and software. Over and over again, it has succeeded. "When people ask me about it," says Van Valen, "I say it lets you do a very different kind of science because the software engineering skill set is very enabling." The Van Valen lab has asked its Schmidt Scholars to train AI to recognize different types of cells in microscope images. "The AI is on a par with what humans are able to do," Van Valen says. The software developed by these Schmidt Scholars, called <a href="https://www.vanvalen.caltech.edu/software/">DeepCell</a>, is available for public use.</p><p data-block-key="86ji5">Professor of Philosophy Frederick Eberhardt has also overseen the development of software that can be used by others in the field outside Caltech. He has worked with two Schmidt Scholars on the <a href="https://sase.caltech.edu/projects/causal.html">Causal Feature Learning</a> project. "Together with Krysztof Chalupka [PhD '17], a former Caltech computer science student, and Pietro Perona [Allen E. Puckett Professor of Electrical Engineering], I had developed a proof-of-concept code in 2014–16," Eberhardt says. "The Schmidt Scholars then took this code draft and turned it into a Python package that includes proper documentation and tutorials, and is designed in a modular way so that researchers can easily adapt the code for their specific settings."</p><p data-block-key="5lb4g">The Schmidt Academy has become a living model of how good software can transform and accelerate science. It is not the only effort underway to engage software engineers in scientific research in university settings, but it is one of the first, say Rumph and Gurnis, and it is distinctive in the way it benefits both researchers and emerging software engineers. "It's a really unique experiment that Caltech and Schmidt Futures has launched," says Breeden. "I don't know of any other university that's running a program like this, and Caltech has been doing it for four years."</p>Peripheral Visual Information Affects Choice2023-10-26T20:44:00+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/peripheral-visual-information-affects-choice<p data-block-key="7idkv"></p><p data-block-key="3uloi">Researchers have known for some time that decision makers are more likely to select items that they look at more during the choice process—and, of course, packaging and placement can encourage this. This is called "attentional choice bias," and it means that you are more inclined to choose the item you're looking at, other factors being equal. One result of attentional choice bias is that at least some of the time you may end up choosing a less desired option simply because you were paying more attention to it.</p><p data-block-key="el163">Indeed, many experiments have shown that this is the case when individuals are scanning supermarket shelves or comparing items side by side. But what happens if the item a decision maker is not focused on is removed, so that it doesn't even appear in their peripheral vision? What if, for example, a consumer is shopping online and viewing only one choice at a time?</p><p data-block-key="1cd2p">This is the question that Caltech social science graduate student and Chen Graduate Fellow Brenden Eum, working with Stephanie Dolbier (BS '18) of UCLA and Antonio Rangel, Bing Professor of Neuroscience, Behavioral Biology, and Economics, sought to answer experimentally.</p><p data-block-key="7sa3p">Eum, Dolbier, and Rangel recruited 50 subjects who reported a liking for snack foods. First, they were shown images of 60 different snack foods on a computer screen and asked to rate, on a five-point scale, how much they like to eat each of these particular foods. Once their preferences were measured, the subjects were asked to make choices between two items shown on the screen. Under one condition, the "visible condition," they were presented with both items on the screen, one on the left side and the other on the right. Eye-tracking software measured the participants' visual fixations as they made their choices.</p><p data-block-key="543k0">Under another condition, the "hidden condition," subjects were presented with only the item they were focusing on, as registered by eye-tracking software, while the other item was removed, leaving only an empty box in its place.</p><p data-block-key="dl5pb">Under the visible condition, the participants' choices aligned with the outcomes expected from prior studies of attentional choice bias. That is, even when a participant said they liked chocolate bars more than salty peanuts, they were more likely to choose the peanuts if they spent relatively more time looking at them.</p><p data-block-key="9men2">In the hidden condition, which simulates a set-up often found in e-commerce, where one item is shown at a time, the researchers found that the same attentional choice biases were at work but that they were twice as strong as when both items were shown to decision makers.</p><p data-block-key="15i1i">"There are hundreds of papers about attentional choice bias," Rangel says. "We know that if you're indifferent between two things when you come into a store, you're more likely to choose an object if I can get you to pay more attention to it. This research shows that if I remove one option from your immediate visual field, you'll be twice as likely to choose the one you're looking at."</p><p data-block-key="3ul2r">The study further recorded the duration of visual fixations. "People typically look at the options about two or three times before making a choice," Eum says. "This back-and-forth is faster when both items are visible, and slower when you can only see items one at a time." Rangel speculates that "if there's information in the periphery, the visual system pulls your attention away, making your fixation shorter. When there's nothing in the periphery to pull your attention away, you fixate longer."</p><p data-block-key="1a7t2">"These phenomena are probably known to marketers already as tricks of the trade," Eum says. "But as neuroscientists, we are trying to understand how these techniques are grounded in the decision-making process."</p><p data-block-key="bitc5">This research is described in "Peripheral Visual Information Halves Attentional Choice Biases," and published in <i>Psychological Science.</i> Eum, Rangel, and Dolbier are co-authors. Funding was provided by the NOMIS Foundation.</p>Caltech's New Center for Science, Society, and Public Policy Hosts Research Conference on Conspiratorial Thinking2023-10-10T19:50:00+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/Caltech_Hosts_Conference_on_Conspiratorial_Thinking<p data-block-key="7idkv">The <a href="https://lindeinstitute.caltech.edu/research/csspp">Center for Science, Society, and Public Policy</a> (CSSPP) at Caltech mounted its first research conference on September 14–15, 2023, to address the phenomenon of conspiratorial thinking from disciplines as diverse as English literature, political science, economics, neuroscience, and psychiatry. Mike Alvarez, co-director of CSSPP and professor of political and computational social science, sees this initiative as characteristic of what CSSPP aims to do. "We keep trying to identify topics that connect with research that Caltech faculty are doing but that also connect to broader policy conversations that are going on outside," he says.</p><p data-block-key="4kc85">Caltech's interest in conspiratorial thinking has its intellectual roots in the COVID-19 pandemic. "The pandemic was a weird time when we were all sitting at home trying to figure out how we could do our work and what we might be able to do to help," Alvarez says. "Ralph Adolphs [PhD '93 and Bren Professor of Psychology, Neuroscience, and Biology] began a study called the <a href="https://coviddynamic.caltech.edu/">COVID-Dynamic</a> Longitudinal Study that put together these really fascinating batteries of questions to ask people about how they were doing emotionally during lockdown. This dovetailed with work that I was doing with two of my graduate students on vaccine acceptance back before covid vaccines were even available."</p><p data-block-key="8d4ef">What began with more narrowly focused questions related to the pandemic became more general concerns for Caltech faculty about misinformation and conspiratorial thinking. "I began a collaboration with Ramit Debnath, a sustainability fellow at the University of Cambridge, looking at misinformation on climate change and what leads to the dissemination of misleading information, especially on social media," Alvarez explains. "Meanwhile, John O'Doherty's lab [O'Doherty is Caltech's Fletcher Jones Professor of Decision Neuroscience] moved into researching the potential psychological determinants of people who might be susceptible to conspiratorial thought—things like aversion to ambiguity or being less willing to seek uncertainty."</p><p data-block-key="708er">"As we started to poke around the literature on conspiratorial thinking, we found a lot of fantastic research on this and decided to bring some of the leading scholars in humanities, social sciences, psychology, neuroscience, and political science to Caltech, under the auspices of CSSPP, so that we could let the Caltech community see the cutting-edge research on this topic," Alvarez says. "When we reached out to people to ask if they'd be interested in participating in a conference, they were all really excited to come to Caltech for this event. So, we assembled an amazing all-star cast."</p><p data-block-key="e5fpm">The conference kicked off on September 14 with a presentation by Elise Wang, assistant professor of English at Cal State Fullerton on medieval European blood libel conspiracies. (Blood libel is a belief that Jews use the blood of Christian children for ritual purposes. It is false, of course, but such charges led to the persecution of Jewish communities in Europe, and the belief is still found in anti-Semitic literature today.) Wang set the initial terms of discussion for the conference by asserting that conspiracy is its own narrative genre with a consistent set of characteristics that have persisted over time and across a very wide variety of conspiratorial theories. Key to this genre is a certain flexibility and resilience that allows believers to fill in details, connect the dots in various ways, and talk their way around even logical contradictions.</p><p data-block-key="49g15">Wang's talk was followed by a philosophical/epistemological take on conspiracy thinking, and then presentations of new research from Alvarez's group by Yimeng Li (PhD '22), now a postdoc at Florida State University, and Debnath.</p><p data-block-key="cp15m">In the afternoon, Adam Berinsky of MIT presented on "The Root of False Beliefs," a topic he has been working on for more than a decade and which is now gathered into his just-published book from Princeton University Press, <i>Political Rumors: Why We Accept Misinformation and How to Fight It.</i> Additional talks were given by political scientists Betsy Sinclair (MS '04, PhD '07) of Washington University in St. Louis and former student of Alvarez's, and Joanne Miller of the University of Delaware, both experts in conspiratorial thinking. Sinclair spoke about her research into identification with partisan political groups and the extent to which individuals are willing to adopt false beliefs if those beliefs preserve their partisan identity. Miller reviewed the secret plots that are so often the essential backdrop of conspiracy theories, calling back to Wang's notion of the narrative structure of conspiracies to better understand when and why "not seeing is believing."</p><p data-block-key="anm9c">The second day of the conference turned toward psychological questions that probe the precise dispositions of those who favor conspiracy theories. Nadia Brashier of UC San Diego began her talk by asking if conspiracy theorists think too much or too little, concluding that the answer is both: some supply incredible detail and craft intricate conspiratorial worldviews; others seem content to take a lot on faith, endorsing a conspiratorial worldview without worrying too much about the fine points. Gordon Pennycook, a professor of psychology at Cornell University, shared his results that show that conspiracy believers are "dispositionally overconfident" and greatly overestimate the number of those who agree with their views; often, he noted, these individuals claim that more than 50 percent of people share conspiratorial beliefs that are actually confined to 5–15 percent of the population. Lisa Kluen, who moved to the Laboratory for Brain and Cognitive Health Technology at McLean Hospital after a postdoctoral fellowship at Caltech in O'Doherty's lab, presented research on the "cognitive attributes" of those who most readily champion conspiracy theories. "What we found," Kluen says, "is that individuals who subscribe to conspiracy beliefs more readily attribute outcomes to the involvement of hidden agents. Also, they seem to seek less information before making decisions, and their decision-making seems less guided by reward."</p><p data-block-key="5rve4">Perspectives from clinical psychology and psychiatry rounded out the afternoon, with speakers offering additional thoughts on the cognitive traits of conspiracy believers and explaining the ways in which conspiracy belief can be clearly distinguished from delusional thinking and from the paranoia experienced by schizophrenics.</p><p data-block-key="ea93g">The conference closed with a presentation by Dutch social psychologist Sander van der Linden of the University of Cambridge, who researches fake news and seeks to "inoculate" people against conspiracy theories through a variety of online and interpersonal games and exercises. How to work against socially destructive conspiracy theories was a through line in the conference. "How do we prevent the spread of conspiracy theories? How can we help prevent them from going down the rabbit hole? And if they have gone down these rabbit holes, are there ways we can persuade them to at least be open to new information?" are all questions Alvarez hoped to raise when designing this conference.</p><p data-block-key="5udl9">"By having an event like this, we want to highlight the kind of research that we do [at Caltech] in the social sciences, ranging from the quantitative and more observational work to the really detailed psychological neuroscience work that John O'Doherty's group does, and frame it in the context of all the other work that's going on in the area of conspiratorial thinking," Alvarez says.</p>Preserving Natural Resources through Policy2023-09-15T06:33:22.483224+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/Hannah_Druckenmiller_Profile<p data-block-key="7idkv"><a href="https://www.hss.caltech.edu/people/hannah-druckenmiller">Hannah Druckenmiller</a> joins the Caltech faculty this year as an assistant professor of economics. An environmental economist, Druckenmiller focuses on governmental policies concerned with preserving natural resources: whether the policies succeed or fail, how their costs and benefits can be better conceptualized for decision-makers, and how the effects of climate change can best be ameliorated through improved regulation.</p><p data-block-key="3dou">Druckenmiller earned her PhD in economics at UC Berkeley and most recently worked for Resources for the Future (RFF), a nonprofit in Washington, D.C., focused on environmental economics and policy research.</p><p data-block-key="etkmp"><b>What environmental policies are you most interested in?</b></p><p data-block-key="4nqf7">Two of the most significant environmental regulations in the United States at the federal level are the Clean Water Act and the Clean Air Act. Although these regulations have been in place for more than 50 years, they're constantly being reassessed and reinterpreted. The scope of the Clean Water Act, for example, is repeatedly debated and redefined by the Supreme Court, presidential administrations, and state litigation. In fact, the Environmental Protection Agency has had different interpretation of which waters are regulated by the Clean Water Act under Presidents Obama, Trump, and Biden. And the change in the scope of environmental regulation is significant—we estimate that 30–40 percent of regulated waters lost federal protection when the Clean Water Act was reinterpreted by the Trump administration.</p><p data-block-key="8lfli"><b>How can the scope of the Clean Water Act change so dramatically?</b></p><p data-block-key="3t3od">The regulation is written in an ambiguous way. It's not clear exactly what is protected. The Clean Water Act protects the "Waters of the United States." This phrase clearly includes navigable waterways like the Mississippi River, and clearly excludes a small puddle in your backyard. Debates center around whether the law protects intermediate cases like isolated wetlands or ephemeral streams that flow a few days per year. In order to decide whether a water resource—like a lake or a river—is regulated, the government sends out an engineer from the Army Corps. These are case-by-case decisions, and we don't have even a ballpark figure for what percent of streams or wetlands in the United States are regulated. One of my projects is trying to use machine learning to map this. Basically, we're creating an algorithm trained on all these case-by-case decisions that have been made historically to decide what the possibility is of any particular resource being regulated. We're trying to understand what was originally regulated, how that scope changes when you get a narrower interpretation of what's protected, and then what the downstream consequences are.</p><p data-block-key="53n6f"><b>What types of downstream consequences have you looked at?</b></p><p data-block-key="6bd4s">I'm interested in how ecosystem services change when you alter environmental protections. Under the Trump administration's interpretation of the "Waters of the United States," a significant share of wetlands was deregulated. I wanted to understand how this would impact the flood protection services that wetlands provide. We found that converting 1 hectare of wetlands (roughly the size of 2.5 football fields) to built-up land increases property damages from flooding by more than $12,000 per year. These costs are rarely borne by the developer who converted the wetlands to another use—they are mostly borne by downstream community members who no longer benefit from the wetlands' ability to trap and slowly release water that would otherwise cause flooding.</p><p data-block-key="9eff5"><b>How do you look at effects of climate change?</b></p><p data-block-key="6sh1l">I recently did a project on how to disincentivize development in areas that are most likely to be affected by climate change. We already have high levels of development in places that are at risk from coastal flooding and sea level rise. One big question is, how can we manage retreat from those places? A second question is how we can stop future development in those risky places.</p><p data-block-key="1ecg5">A longstanding hypothesis in economics is that, intentionally or not, the government subsidizes development in environmentally fragile places by providing risk management tools like insurance, or funding for infrastructure such as roads, water lines, and sewage systems, and by providing disaster assistance when problems arise. When there's a hurricane and the federal government comes in and gives the locality or individuals money to recover, that's indirectly subsidizing them for living there in the first place.</p><p data-block-key="7c1m6">So our question was, if you got rid of government subsidies in these fragile places, could that alone prevent development there? Or are these such desirable places—they are along beautiful coastlines—that governmental subsidies, or their lack, wouldn't make a significant dent in the amount of development you see? We looked at this program from the 1980s called the Coastal Barrier Resources System, which was a policy that removed these types of subsidies for development in designated areas along the Atlantic and Gulf coasts. We wanted to see the long-term effect of the policy. Forty years later, do we see much lower levels of development in these places?</p><p data-block-key="b694p">The challenge to studying the Coastal Barrier Resources System is that designated areas were not randomly assigned along the coast. They were intentionally selected by land-use planners because they were considered risky or because the land was thought to have environmental value. We were able to find controls—similar places not affected by the Coastal Barrier Resources System program—by running a machine-learning procedure intended to mimic the process by which land-use planners designated target areas in the 1980s. This allowed us to find places that were statistically indistinguishable from treated areas in the 1980s, but which did not enter the program. Then we compared outcomes in the treatment and the control areas. What we found is that this policy did a lot to reduce development. On average, the protected areas had 85 percent lower development levels.</p><p data-block-key="6osuf">What I found most interesting is that we also found evidence that the areas without federal incentives for development created spillover benefits to surrounding communities. By conserving natural land, ensuring that it wasn't converted into built-up area, we saw flood-protection benefits in the areas surrounding wetlands. We even saw higher property values in those areas because they're next to a natural amenity: namely, these pristine coastal areas.</p><p data-block-key="2sfu4">That was interesting to me as an economist. It implies that federal programs to reduce disaster exposure don't need to conflict with local interests in maintaining the tax base. A lot of localities don't want these protected areas in their jurisdiction because they think that if they kill development it will lower their property tax revenue. But what we found is that restricting development in these coastal areas has no net effect on property tax revenue across the counties they're located in. There are higher property values in surrounding areas and lower property values in the designated protected area, so most often these two effects cancel each other out.</p><p data-block-key="3veoe"><b>Do you think removing subsidies for development in wildfire prone areas could work the same way?</b></p><p data-block-key="bgu6p">My coauthors at Resources for the Future and I are hoping to work more on this. Some of my collaborators do a lot of work on wildfires, and we're really interested to see if you could institute a similar policy in the wildland-urban interface. There are differences between coastal areas and wildland-urban interfaces, so it's not obvious that the same policy instrument would work, but that's something we're interested in looking at.</p><p data-block-key="373vf"><b>How did you become interested in environmental policy?</b></p><p data-block-key="7g24t">I grew up in New York, and we spent a lot of time by the ocean. I always wanted to do something related to marine biology. When I was in high school, I attended a program in the Bahamas called The Island School. You go there for a semester, and all of your academics are place-based: your science class is marine biology, your math class is focused on celestial navigation, and in the humanities all the literature we read was written by authors from the Caribbean.</p><p data-block-key="8gqi5">The Island School is an amazing place, and it really solidified my desire to study marine biology. So when I went to Stanford, I chose an interdisciplinary major in environmental science with a focus on oceans. The major required several classes in economics since economics is central to understanding environmental policy. I took my first economics class and fell in love with it as a framework for understanding why the environment is regulated, when regulation is successful, and when it's not.</p><p data-block-key="86ai8"><b>What are you looking forward to at Caltech?</b></p><p data-block-key="eaf23">The thing I'm most excited about is that people here really think differently. It seems like you're not constrained to your disciplinary box as much as you might be at other institutions. There's access at Caltech to world-class scientists who are interested in collaborating with social scientists. I hear ideas here that I haven't heard before.</p><p data-block-key="8pjqh"><b>Will you be participating in the Center for Science, Society, and Public Policy (CSSPP)?</b></p><p data-block-key="10u6q">Yes, the <a href="https://lindeinstitute.caltech.edu/research/csspp">CSSPP</a> was a big draw for me at Caltech. The center supports engagement between science and policy, with priority research areas including climate change and sustainability and artificial intelligence (AI). I'm increasingly interested in how we can use AI systems to improve the monitoring and enforcement of environmental regulations.</p><p data-block-key="5l94l">For example, the Clean Air Act is enforced based on a system of 900 ground-based monitors across the United States. That's less than one per county, so the law is not binding in many places that have noncompliant air quality where there simply isn't a monitor. I have a new project that asks whether there's a path to using satellite data directly for enforcement of the Clean Air Act. And if not, is there a path to using satellite data to at least inform the placement of new monitors?</p><p data-block-key="8t9il"><b>So there were no satellite monitors when the Clean Air Act was first written?</b></p><p data-block-key="eegm6">Correct, but it's more complicated than that. Satellites cannot directly measure chemicals or pollutants as you would ordinarily think of them. They measure things that are correlated with pollution, like aerosol optical depth. That's basically just a fancy word for how hazy the atmosphere is. Then you can use a statistical model to convert that into an estimate of a specific pollutant, like particulate matter. It's hard to enforce a regulation based on something this uncertain, especially when the regulation is very costly. I mean, if you're noncompliant with the Clean Air Act, your county has to curb pollution-generating activities like industrial production or traffic. This basically means less economic activity in your region.</p><p data-block-key="c8v15"><b>What are you going to be teaching at Caltech?</b></p><p data-block-key="5l8ds">I'm starting with environmental economics at the undergraduate level this year. I've met some of the PhD students in economics since I arrived. It seems like the students here are really bright and curious. I also hope to work with postdocs coming through CSSPP.</p>WAVE Alumni Return to Caltech for Grad School2023-09-11T15:04:00+00:00Caltech Communicationswww@caltech.eduhttps://divisions.caltech.edu/newspage-index/wave-alumni-return-to-caltech-for-grad-school<p data-block-key="rnuau">For seven new graduate students at Caltech, it won't be their first time conducting research at the Institute: they all had a head start in summer 2022, as members of the WAVE Fellows program.</p><p data-block-key="hidf">Launched in 2015, the <a href="https://sfp.caltech.edu/undergraduate-research/programs/wavefellows">WAVE Fellows program</a> is a 10-week summer research program for those undergraduates who have been significantly underrepresented in STEM and higher education. Although open to all applicants, the program aims to foster diversity by increasing the participation of students historically excluded from science and engineering PhD programs and making Caltech's graduate programs more visible and accessible to students not traditionally exposed to Caltech.</p><p data-block-key="6u1he">Since the start of the program, 35 former WAVE Fellows have matriculated to Caltech for their PhDs, and more than 90 percent have enrolled in graduate programs overall. After an <a href="https://www.caltech.edu/about/news/expanding-wave-pipeline">expansion of the program in 2021</a>, Caltech increased the number of WAVE Fellows from 25 to 80 students each summer. With that expansion, the program's success continues to grow.</p><p data-block-key="1h1h0">"The WAVE program has been a powerful way to attract talented scholars to Caltech," says Harry A. Atwater (Otis Booth Leadership Chair, Division of Engineering and Applied Science; Howard Hughes Professor of Applied Physics and Materials Science; and director, Liquid Sunlight Alliance), who worked with two WAVE Fellows in the incoming cohort.</p><p data-block-key="7461c">"I'm delighted that César [Lasalde Ramírez] and Holland [Frieling] discovered Caltech through the WAVE fellowship program, and then chose to join our vibrant and tightly knit community. I'm looking forward to exploring interdisciplinary graduate research with both of them in the coming years."</p><p data-block-key="198no">Get to know the former WAVE Fellows who will return to Caltech for graduate school this fall:</p><p data-block-key="rnuau"></p><embed alt="Holland Frieling" embedtype="image" format="LeftAlignMedium" id="33887"/><p data-block-key="bfl5v"></p><h3 data-block-key="cg9vg"><b>Holland Frieling</b></h3><p data-block-key="8tker">Former Kavli Nanoscience Institute (KNI) SURF-the-WAVE prize fellow</p><p data-block-key="qacr"><b>Graduate Option:</b> applied physics</p><p data-block-key="cdvv0"><b>Research Area:</b> "I knew I wanted to join Professor Atwater's group since meeting with him during the WAVE program, and I've actually been able to start research early over the summer. My general research interest is in quantum materials, but right now I'm training to work on two-dimensional black phosphorus, a van der Waals material with interesting optical and electronic properties."</p><p data-block-key="div9"><b>WAVE Faculty Mentor:</b> Nai-Chang Yeh, Thomas W. Hogan Professor of Physics</p><p data-block-key="9qss0"><b>WAVE Research Project:</b> "My research project title was ‘Scanning Tunneling Microscopy on Strain-Engineered Graphene,' which entailed working with my graduate mentor to rebuild a high-vacuum scanning tunneling microscope to image various samples including graphite, graphene, and strained graphene."</p><p data-block-key="9ckbs"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="4su92">"The opportunity to do research outside of my undergraduate institution helped me gain confidence in my scientific abilities and pushed me to apply to more-competitive graduate programs. I also enjoyed being a part of the Caltech community, with its emphasis on collaboration and inclusion, which ultimately helped me decide to pursue my graduate studies here."</p><p data-block-key="rnuau"></p><embed alt="Manuel Holguin" embedtype="image" format="LeftAlignMedium" id="33888"/><h3 data-block-key="5cv9i"><b>Manuel Holguin</b></h3><p data-block-key="1b4m8">Former Southern California Edison WAVE fellow</p><p data-block-key="f31ah"><b>Graduate Option:</b> biochemistry and molecular biophysics</p><p data-block-key="2d374"><b>Research Area:</b> "My current research interests remain within structural biology, where I plan to continue to develop my skills in cryo-EM [cryogenic electron microscopy]. This technique provides great opportunities to study my primary interest, protein evolution, of which there are many labs here at Caltech that are also interested in this."</p><p data-block-key="enpbs"><b>WAVE Faculty Mentor:</b> William Clemons, Arthur and Marian Hanisch Memorial Professor of Biochemistry</p><p data-block-key="ap0cc"><b>WAVE Research Project:</b> "I was utilizing cryo-EM to study MtMraY, a membrane protein in <i>Mycobacterium tuberculosis</i>. MtMraY was the target for a novel antibiotic drug under development that seemed capable of inhibiting the growth and even killing tuberculosis bacteria."</p><p data-block-key="865q"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="cr4jc">"Without WAVE, I don't think there is any chance I would have ended up at Caltech. Being a first-gen college student and growing up in the area, Caltech always had this incredible reputation, and before WAVE, it just wasn't somewhere I believed that I could succeed. I was shocked when I received my WAVE acceptance (which was initially a rejection, before being reconsidered and offered a spot nearly a month later), and even more so when I realized that I clicked so well with the research being done and the community. After WAVE, Caltech became my clear first choice, and I am thrilled to be back for my PhD."</p><p data-block-key="dihsl"></p><embed alt="César A. Lasalde Ramírez" embedtype="image" format="LeftAlignMedium" id="33889"/><p data-block-key="15noc"></p><h3 data-block-key="4ocn4"><b>César A. Lasalde Ramírez</b></h3><p data-block-key="35pss">Former Kavli Nanoscience Institute (KNI) SURF-the-WAVE prize fellow</p><p data-block-key="5nmrm"><b>Graduate Option:</b> materials science</p><p data-block-key="8p9dd"><b>Research Area:</b> "My research interests are in the areas of solar technology and artificial photosynthesis. My goal at Caltech is to integrate my background in electrical engineering with the diverse knowledge I have gained from my research experiences to design tools that contribute to mitigating climate change."</p><p data-block-key="bqsq0"><b>WAVE Faculty Mentor:</b> Harry Atwater, Otis Booth Leadership Chair, Division of Engineering and Applied Science; Howard Hughes Professor of Applied Physics and Materials Science; Director, Liquid Sunlight Alliance</p><p data-block-key="71a58"><b>WAVE Research Project:</b> "During the WAVE fellowship I studied how metal and semiconducting materials could convert carbon dioxide into useful products using the full spectrum of light in a project titled ‘Elucidating Structure-Property Relationships in Metal/Semiconductor Materials for Solar-Driven Carbon Dioxide Conversion.'"</p><p data-block-key="3urmv"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="9aln5">"As a Puerto Rican with little to zero in-person experience doing research at universities in the United States, I was very unsure of applying to graduate school. The WAVE fellowship not only gave me the confidence and skills necessary to apply, but it also showed me the amazing community at Caltech. Now I recommend the WAVE fellowship to every undergrad interested in science and graduate school."</p><p data-block-key="a80if"></p><embed alt="Noah Okoda" embedtype="image" format="LeftAlignMedium" id="33890"/><p data-block-key="6q4op"></p><h3 data-block-key="bn02m"><b>Noah Okada</b></h3><p data-block-key="54kvu">Former Chen Institute BrainWAVE fellow</p><p data-block-key="bgg5r"><b>Graduate Option:</b> social and decision neuroscience</p><p data-block-key="5rhcd"><b>Research Area:</b> "I'm interested in understanding the intricate interplay between the brain's fear and anxiety circuits and their profound impact on social behaviors. Specifically, I am interested in studying how interactions in digital and virtual environments may impact these emotional circuits. During my time at Caltech I hope to explore these questions by building gamified environments to study the brain."</p><p data-block-key="c6pqq"><b>WAVE Faculty Mentor:</b> Dean Mobbs, professor of cognitive neuroscience; Allen V. C. Davis and Lenabelle Davis Leadership Chair, Caltech Brain Imaging Center; director, Caltech Brain Imaging Center</p><p data-block-key="dfmo0"><b>WAVE Research Project:</b> "During the WAVE fellowship I worked on the development of a gamified virtual environment to study how the human brain computes escape and reward decisions in situations of threat. This work was part of a larger project focused on investigating how emotions such as fear and anxiety emerge from the brain."</p><p data-block-key="8j2er"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="67snk">"The WAVE program helped me to see what life as a graduate student could be like. Coming from a low-income family with limited exposure to academia, the WAVE program was pivotal in shaping my perspective and understanding of careers in research, as well as [exposing me to] the dynamic academic environment at Caltech."</p><p data-block-key="a80if"></p><embed alt="Tristan Villanueva" embedtype="image" format="LeftAlignMedium" id="33891"/><p data-block-key="5r4ta"></p><h3 data-block-key="en7f5"><b>Tristan Villanueva</b></h3><p data-block-key="a4kmv">Former Resnick Sustainability Institute WAVE fellow</p><p data-block-key="a9r8f"><b>Graduate Option:</b> mechanical engineering</p><p data-block-key="2kn6"><b>Research Area:</b> "Throughout my undergraduate studies at Cal [UC Berkeley] and UNAM [Universidad Nacional Autónoma de México], I grew to appreciate the math and theory that goes into solving problems within engineering and physics, which led to my interests in continuum mechanics and dynamics. During my PhD I hope to analyze fundamental problems that have an impact on sustainability by using theory and computation."</p><p data-block-key="5be41"><b>WAVE Faculty Mentor:</b> Kaushik Bhattacharya, Howell N. Tyson, Sr., Professor of Mechanics and Materials Science; vice provost</p><p data-block-key="bhaph"><b>WAVE Research Project:</b> "The title of my project was ‘Crack Nucleation in Lithium-Ion Battery Particles Utilizing a Phase Field Approach.' During my project I formulated equations for simple diffusion-induced crack nucleation using a variational approach, solved two-dimension crack induced by diffusion problems numerically, and analyzed the impact of anisotropic diffusion on symmetric geometries."</p><p data-block-key="i6o1"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="18nk1">"Making a decision on which graduate school I attended was difficult. Ultimately, I knew that I could develop myself academically at Caltech, and my experience through the WAVE program reassured me that I have a home in Pasadena with a community of people that share values I have. I truly had a fantastic time throughout my WAVE experience and made fond memories working out problems on chalkboards, being excited to learn from my postdoc Jean-Michel Scherer and adviser Kaushik Bhattacharya, and spending time with my lab group and WAVE cohort."</p><p data-block-key="bm8jn"></p><embed alt="Audrey Washington" embedtype="image" format="LeftAlignMedium" id="33892"/><p data-block-key="e0as7"></p><h3 data-block-key="fuv8o"><b>Audrey Washington</b></h3><p data-block-key="40tj6">Former Liquid Sunlight Alliance (LiSA) WAVE fellow</p><p data-block-key="11gh"><b>Graduate Option:</b> chemistry</p><p data-block-key="c4rq9"><b>Research Area:</b> "My current research interest is studying mechanisms in photo and electrocatalysis facilitated by novel materials. I have previously studied photochemical and electrochemical reduction of carbon dioxide and would like to develop projects that are aimed at understanding the exact chemical changes that occur in such reactions. Such studies may reveal interesting activity that could guide future development of photo and electrocatalytic materials."</p><p data-block-key="1l35h"><b>WAVE Faculty Mentor:</b> Scott Cushing, assistant professor of chemistry</p><p data-block-key="ev9h4"><b>WAVE Research Project: "</b>My project during the WAVE fellowship was entitled ‘Integrating an Ultra High Vacuum Cryostat in Ultrafast XUV Spectroscopy for Charge-carrier Dynamics Analysis.' We utilized the short pulses employed by the ultrafast optical-pump and the XUV probe to study photoactive materials and their charge-carrier dynamics. This provides element-specific information that is normally difficult to obtain in traditional spectroscopy tools. Incorporating a cryostat allows us to study materials that have novel properties at extremely low temperatures."</p><p data-block-key="26mf"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="7ko13">"The WAVE program heavily influenced my decision to attend Caltech. After spending the summer with the Cushing Lab, I developed relationships that were lasting. When visiting different universities, I could not forget how at home I felt at Caltech, and the WAVE program allowed me to feel comfortable and seen in a rigorous academic environment."</p><p data-block-key="hi1ff"></p><embed alt="Spencer Winter" embedtype="image" format="LeftAlignMedium" id="33893"/><p data-block-key="t22n"></p><h3 data-block-key="e3ecs"><b>Spencer Winter</b></h3><p data-block-key="cshfd">Former Information Science and Technology (IST) WAVE fellow</p><p data-block-key="4eo62"><b>Graduate Option:</b> biology</p><p data-block-key="aeboo"><b>Research Area:</b> "I'm hoping to continue in the field of molecular programming, designing soft materials with robotic behaviors that are controlled via programmable molecular interactions. The work I already started during my WAVE Fellows experience will be relevant for this long-term goal."</p><p data-block-key="cku1u"><b>WAVE Faculty Mentor:</b> Lulu Qian, professor of bioengineering</p><p data-block-key="62d4k"><b>WAVE Research Project:</b> "I was working on a new design for DNA-based circuits. Specifically, I was working to reduce ‘leak' [unintended chemical reactions] in catalytic DNA circuits. My project was titled ‘Allosteric Leak Reduction in Catalytic Strand-Displacement Circuits.'"</p><p data-block-key="6va81"><b>How did your experience in the WAVE program influence your decision to pursue graduate research and/or attend Caltech?</b></p><p data-block-key="8h4fp">"My experience as a WAVE fellow was extremely important to my decision to attend Caltech. The WAVE Fellows program gave me the opportunity to explore a field I was curious about but inexperienced with while feeling like I was making a meaningful contribution. The WAVE Fellows program helped ease me, as someone from a disadvantaged background, into the world of Caltech. The level of community, academic rigor, and support directly contributed to my decision to apply and attend Caltech, and I'm very excited to be back."</p><p data-block-key="ug98r"></p><hr/><p data-block-key="f1u7m"></p><p data-block-key="u96a">The WAVE program is generously supported by on-campus partners, including the Kavli Nanoscience Institute; Resnick Sustainability Institute; Tianqiao and Chrissy Chen Institute for Neuroscience; Information Science and Technology initiative; Center for Environmental Microbial Interactions; Institute for Quantum Information and Matter; Division of the Humanities and Social Sciences; and the Liquid Sunlight Alliance; as well as off-campus partners, including the Braun Foundation, Edison International, Facebook, Genentech Foundation, Google, and individual donors.</p><h3 data-block-key="13jqt"><a href="https://sfp.caltech.edu/support-us">Learn more about how to support the WAVE Fellows program</a>.</h3>Experimental Economics in Theory and Practice2023-07-24T03:06:39.694113+00:00Cynthia Ellerceller@caltech.eduhttps://divisions.caltech.edu/newspage-index/Experimental-Economics-Theory-and-Practice<p data-block-key="7idkv">The social sciences have to face a notoriously difficult challenge that begins with their very name. Just what sort of science are these "social" sciences? Can they really help us study and understand human society in the same way the natural sciences promise to improve our understanding of the natural world? Certainly it seems that they should. Why should we not be able to observe, analyze, and even quantify human behavior if we already feel comfortable doing the same for volcanoes and rivers, marigolds and fruit flies?</p><p data-block-key="qodq">In practice, things have often been much dicier. From the Book of Genesis on, we humans have demonstrated a somewhat (entirely?) overblown assessment of our own singularity perched atop the natural world. And yet, the quest to find experimentally verifiable answers about human behavior continues. How could it not? If there is one thing that would be extremely profitable for us to understand, it would be ourselves. It is this quest to construct hypotheses about human behavior, test them, and share the results that motivates Caltech's summer program in theory-driven experimental economics, now in its second year.</p><p data-block-key="2vhsh">"When I was considering moving to Caltech," Professor of Economics Charlie Sprenger, who is also executive officer for the social sciences, explains, "[Professor of Economics] Marina Agranov and I brainstormed some ideas for creating educational opportunities for graduate students who are interested in the intersection between structured theories of choice and experimental tests. It was Marina's idea to develop a visiting student summer program on the topic as a way to help students build their networks, get feedback on their own projects, and inspire each other."</p><p data-block-key="drpgp">The summer program reaches out to graduate students and other interested scholars in experimental economics via professors and researchers in the field. This year's summer program brought students from UC Santa Barbara, University of Michigan, UC San Diego, Ohio State University, Columbia University, Princeton University, and UC Berkeley to the Caltech campus. "This is the first opportunity we've had where we can meet grad students from the same department at different universities," said Jack Adeney, a doctoral student in the social sciences who came to study at Caltech by way of NYU Abu Dhabi and the University of Cambridge, and who attended the program.</p><p data-block-key="efbqm">This year's weeklong intensive ran from June 20–24 in Dabney Lounge. It began with lectures and presentations given by Caltech faculty, including Sprenger, Agranov, Antonio Rangel, Kirby Nielsen, and Thomas Palfrey, and Doug Bernheim of Stanford University. Students learned how to formulate theories about human decision-making and then construct controlled economic environments to test these in a way that reasonably matches real-world situations. They were also exposed to new data-collection tools such as tracking visual fixations, neural activity, and decision times that enhance standard laboratory experiments on subjects' economic choices.</p><p data-block-key="fiplk">The last two days of the summer program gave students the opportunity to present their own research and get feedback from professors and fellow students alike. This, as much as anything else, is the motivation for the program.</p><p data-block-key="3j1bs">"Marina and I are quite blunt on this point," says Sprenger. "We want students to be inspired to conduct theory-driven experimental research, write wonderful job market papers, and receive offers for postdoctoral positions and assistant professorships that will inspire the next generation to follow their path."</p>New Caltech Center Sheds Light on the Future of Generative AI, Innovation, and Regulation2023-05-19T20:22:00+00:00Emily Velascoevelasco@caltech.eduhttps://divisions.caltech.edu/newspage-index/generative-ai-regulation-kevin-roose<p data-block-key="o08ft">From weather forecasts and disease diagnosis to chatbots and self-driving cars, new applications of <a href="https://scienceexchange.caltech.edu/topics/artificial-intelligence-research/artificial-intelligence-definition?utm_source=caltechnews&utm_medium=web&utm_campaign=cseai">artificial intelligence</a> (AI) continue to multiply. More recently, the widespread availability of tools that can create content—whether code, text, images, audio, or video—such as ChatGPT and DALL-E, has thrust "generative AI" into the spotlight.</p><p data-block-key="bh852">As applications proliferate, so do complex questions about how to ensure responsible use of generative AI. To explore the societal implications of AI technology and how policymakers might approach regulating it, the Caltech <a href="https://lindeinstitute.caltech.edu/research/csspp">Center for Science, Society, and Public Policy</a> (CSSPP) <a href="https://lindeinstitute.caltech.edu/research/csspp/csspp-events/csspp-roundtable-conversation-may-5-2023">hosted</a> a conversation among researchers, industry representatives, and the public on Caltech's campus. The CSSPP was <a href="https://www.caltech.edu/about/news/new-center-aims-to-help-shape-public-science-policy">established</a> in early 2023 to examine the intersection of science and society, provide a forum for the discussion of scientific ethics, and help shape public science policy. The center is affiliated with <a href="https://lindeinstitute.caltech.edu/">The Ronald and Maxine Linde Institute of Economic and Management Sciences</a>.</p><p data-block-key="20ejd">"We believe that scientific knowledge and technological prowess are essential to any meaningful evaluation of the impacts of AI on society," said Caltech president Thomas F. Rosenbaum, the Sonja and William Davidow Presidential Chair and professor of physics. "This is true for the positives and for the negatives: whether it be lifesaving improvements to health screening, powerful tools for artistic creation, and new ways of approaching science or potential upheavals in the job market, propagation of false information, and new weapons of war. Only through this type of informed evaluation can we amplify the salutary aspects of technological development and counter its dehumanizing capacity."</p><p data-block-key="9hm5g">The event featured an introduction on the state of generative AI from <i>New York Times</i> technology columnist <a href="https://www.nytimes.com/by/kevin-roose">Kevin Roose</a> (who famously had an <a href="https://www.nytimes.com/2023/02/16/technology/bing-chatbot-transcript.html">unnerving conversation</a> with Microsoft's Bing chatbot).</p><p data-block-key="5b9rc">In his keynote, Roose reminded the audience of the power of shared responsibility and knowledge. "One of the advantages that AIs have over humans is that they have networked intelligence: When one node in a neural network learns something or makes a connection, it propagates it through to all the other nodes in the neural network. When one self-driving car in a fleet learns about a new kind of obstacle, it feeds that information back into the system," he said. "Humans don't do that, by and large. We silo information, we hoard it, we keep it to ourselves. And I think that if we want a realistic shot at competing and thriving and succeeding, and maintaining our agency and our relevance in this new era of generative AI, we really need to do it together." While on campus, Roose also participated in a Q&A session with nearly 50 Caltech students.</p><p data-block-key="74blb">In a subsequent panel discussion moderated by R. Michael Alvarez, professor of political and computational social science and co-director of the CSSPP, experts in law, gaming and technology, and academic research shared thoughts on the positive and negative potential of generative AI.</p><p data-block-key="ct8ij">The optimistic outlook centers on AI's power to advance science and engineering, for example, by making it possible to predict genome sequences of new COVID-19 variants before they appear in nature, design better medical equipment, and mitigate climate change.</p><p data-block-key="59gn0">"How do we capture CO2 and store it underground? How do we plan for the right reservoir and the right amount of CO2 to store? These are the kinds of complex processes that our human minds can't even grapple with," said Anima Anandkumar, Bren Professor of Computing and Mathematical Sciences and co-leader of the <a href="https://www.ai4science.caltech.edu/index.html">AI4Science</a> initiative at Caltech. "We are using [generative] AI, and we are doing it much faster. Along with it comes the benefit of being able to come up with new discoveries, new inventions."</p><p data-block-key="6ndj8">Speaking from a more skeptical perspective, panelists raised concerns over intellectual property and copyright, bias, and large-scale misinformation.</p><p data-block-key="c7se0">Additionally, when generative AI technologies are coupled with the massive amount of personal data consumers share with social media algorithms, our own biases can become vulnerable to manipulation, Carly Taylor, a data scientist and security strategist at Activision Publishing pointed out. "All of us are capable of being bamboozled," Taylor said. "Everyone has confirmation biases, and in many cases across social media, we have spent every single day for years telling Facebook, Instagram, and LinkedIn exactly what we are biased toward by what we search, what content we consume, or with whom we engage … As a risk, that can become completely exploitable."</p><p data-block-key="774c0">Justin Levitt, Gerald T. McLaughlin Fellow and professor of law at Loyola Law School, shared his pessimism about AI's impact on democracy in the United States, including the ability to rapidly spread election misinformation. "Democracy depends on a set of different opinions and a set of common facts, and generative AI is going to be great for giving us an infinite array of disparate facts," he said. "That's a disaster for democracy."</p><p data-block-key="3hl60">Sean Comer, an applied researcher at Activision and its Infinity Ward development studio, saw a silver lining in recent anxiety over generative AI. "Maybe it gives us the elephant in the room to address the attention economy, which a lot of misinformation tends to stem from," he said. "Maybe it's a necessary evil that can force us to deal with these things."</p><p data-block-key="9sqfg">Importantly, speakers addressed the role of research institutions like Caltech. For example, avoiding biases in new AI models will take the kind of critical thinking and rigorous testing for which academia is known. The CSSPP will continue to foster these types of conversations by bringing policymakers to campus for lectures, colloquia, discussion panels, and workshops in addition to developing undergraduate and graduate courses that cover issues in scientific ethics and policy, and consider how policy may be augmented by scientific ethics and expertise.</p><h5 data-block-key="o08ft">Learn more about the <a href="https://lindeinstitute.caltech.edu/research/csspp">Caltech Center for Science, Society, and Public Policy (CSSPP).</a></h5>No Magic Number for Time It Takes to Form Habits2023-04-17T19:00:00+00:00Whitney Clavinwclavin@caltech.eduhttps://divisions.caltech.edu/newspage-index/no-magic-number-for-time-it-takes-to-form-habits<p data-block-key="ktcf2">Putting on your workout clothes and getting to the gym can feel like a slog at first. Eventually, you might get in the habit of going to the gym and readily pop over to your Zumba class or for a run on the treadmill. A new study from social scientists at Caltech now shows how long it takes to form the gym habit: an average of about six months.</p><p data-block-key="3tdqc">The same study also looked at how long it takes health care workers to get in the habit of washing their hands: an average of a few weeks.</p><p data-block-key="4ecqm">"There is no magic number for habit formation," says Anastasia Buyalskaya (PhD '21), now an assistant professor of marketing at <a href="https://www.hec.edu/en/faculty-research/faculty-directory/faculty-member/buyalskaya-anastasia">HEC Paris</a>. Other authors of the study, which appears in the journal <i>Proceedings of the National Academy of Sciences,</i> include Caltech's <a href="https://www.hss.caltech.edu/people/colin-f-camerer">Colin Camerer</a>, Robert Kirby Professor of Behavioral Economics and director and leadership chair of the T&C Chen Center for Social and Decision Neuroscience, and researchers from the University of Chicago and the University of Pennsylvania. Xiaomin Li (MS '17, PhD '21), formerly a graduate student and postdoctoral scholar at Caltech, is also an author.</p><p data-block-key="d0jpl">"You may have heard that it takes about 21 days to form a habit, but that estimate was not based on any science," Camerer says. "Our works supports the idea that the speed of habit formation differs according to the behavior in question and a variety of other factors."</p><p data-block-key="9htrk">The study is the first to use machine learning tools to study habit formation. The researchers employed machine learning to analyze large data sets of tens of thousands of people who were either swiping their badges to enter their gym or washing their hands during hospital shifts. For the gym research, the researchers partnered with 24 Hour Fitness, and for the hand-washing research, they partnered with a company that used radio frequency identification (RFID) technology to monitor hand-washing in hospitals. The data sets tracked more than 30,000 gymgoers over four years and more than 3,000 hospital workers over nearly 100 shifts.</p><p data-block-key="4asci">"With machine learning, we can observe hundreds of context variables that may be predictive of behavioral execution," explains Buyalskaya. "You don't necessarily have to start with a hypothesis about a specific variable, as the machine learning does the work for us to find the relevant ones."</p><p data-block-key="99roa">Machine learning also let the researchers study people over time in their natural environments; most previous studies were limited to participants filling out surveys.</p><p data-block-key="dsfor">The study found that certain variables had no effect on gym habit formation, such as time of day. Other factors, such as one's past behavior, did come into play. For instance, for 76 percent of gymgoers, the amount of time that had passed since a previous gym visit was an important predicator of whether the person would go again. In other words, the longer it had been since a gymgoer last went to the gym, the less likely they were to make a habit of it. Sixty-nine percent of the gymgoers were more likely to go to the gym on the same days of the week, with Monday and Tuesday being the most well attended.</p><p data-block-key="6hjke">For the hand-washing part of the study, the researchers looked at data from health care workers who were given new requirements to wear RFID badges that recorded their hand-washing activity. "It is possible that some health workers already had the habit prior to us observing them, however we treat the introduction of the RFID technology as a ‘shock' and assume that they may need to rebuild their habit from the moment they use the technology," Buyalskaya says.</p><p data-block-key="3vf53">"Overall, we are seeing that machine learning is a powerful tool to study human habits outside the lab," Buyalskaya says.</p><p data-block-key="44jl0">The study titled "<a href="https://www.pnas.org/doi/10.1073/pnas.2216115120">What can machine learning teach us about habit formation? Evidence from exercise and hygiene</a>" was funded by the Behavior Change for Good Initiative, the <a href="https://lindeinstitute.caltech.edu/">Ronald and Maxine Linde Institute of Economics and Management Sciences</a> at Caltech, and the <a href="https://neuroscience.caltech.edu/">Tianqiao and Chrissy Chen Institute for Neuroscience</a> at Caltech.</p>New Center Aims to Help Shape Public Science Policy2023-03-30T16:38:00+00:00Emily Velascoevelasco@caltech.eduhttps://divisions.caltech.edu/newspage-index/new-center-aims-to-help-shape-public-science-policy<p data-block-key="ix9rj">Sometimes it seems as though scientific advancement occurs at such a rapid pace that its effects on society are barely considered until they have already happened. A new center established at Caltech seeks to examine this intersection of science and society, provide a forum for the discussion of scientific ethics, and help shape public science policy.</p><p data-block-key="68f5l">The <a href="https://lindeinstitute.caltech.edu/research/csspp">Center for Science, Society, and Public Policy</a> (CSSPP) will be affiliated with <a href="https://lindeinstitute.caltech.edu/">The Ronald and Maxine Linde Institute of Economic and Management Sciences</a> in the Division of the Humanities and Social Sciences (HSS), and it counts two of the division's faculty members as its co-directors. They are <a href="https://www.hss.caltech.edu/people/r-michael-alvarez">R. Michael Alvarez</a>, professor of political and computational social science; and <a href="https://www.hss.caltech.edu/people/frederick-eberhardt">Frederick Eberhardt</a>, professor of philosophy. The center has also hired two postdoctoral scholars.</p><p data-block-key="595eh">"We represent different aspects of HSS in an initiative like this," Alvarez says. "I come from the social sciences, and in the social sciences, we've had a long history of faculty who have been directly involved in various types of public policy over the years. That includes me, in particular when it comes to elections and election administration. I've got some experience and a little bit of academic understanding about how politics and the public policy process works."</p><p data-block-key="fj7h7"></p><embed alt="A portrait of R. Michael Alvarez. He stands in front of a book case and smiles." embedtype="image" format="RightAlignSmall" id="32208"/><p data-block-key="e45ab"></p><p data-block-key="1caq1">Eberhardt, whose own work has examined the philosophy of science, says he began to consider science's responsibility to the public several years ago when he realized that although Caltech had courses on artificial intelligence (AI), it had none on the ethics of AI.</p><p data-block-key="dh6hl">"I was very concerned that this is something we needed to teach our students," Eberhardt says. "This is something they need to know and think about, especially nowadays. So, I put that course together. It has been extremely well received over the years.</p><p data-block-key="66a8k"></p><embed alt="A portrait of Frederick Eberhardt. He smiles and is outdoors." embedtype="image" format="LeftAlignSmall" id="32209"/><p data-block-key="2dra"></p><p data-block-key="8ejpd">"I think there's a feeling of responsibility among the philosophers at Caltech that we need to do our part in helping people consider these issues," Eberhardt adds. "What brings me to the table is this obligation that something needs to be done, quite apart from the fact that there is a wealth of tricky and interesting topics to work on in this space."</p><p data-block-key="66bbi">Eberhardt's experience with the ethics of AI may be helpful as the center launches. <a href="https://scienceexchange.caltech.edu/topics/artificial-intelligence-research?utm_medium=web&utm_campaign=cseai&utm_source=caltechnews&utm_content=&utm_term=">Artificial intelligence</a> has been a topic of interest lately because of the release of ChatGPT, a chatbot with advanced linguistic abilities that often produces factually incorrect material. Besides its lack of veracity, ChatGPT's ability to "write" lengthy papers and essays from a prompt has caused concern among educators who say it may enable students to produce assignments without doing the work themselves.</p><p data-block-key="85v3s">"The whole debate around ChatGPT and the large language models has people in academia asking what do we do with this? What <i>can</i> we do with this? And how will it change the way students can and should write papers? It's obviously a difficult discussion to have, and it's not obvious what the solutions are."</p><p data-block-key="1mdgd">Eberhardt adds that concerns about <a href="https://scienceexchange.caltech.edu/topics/artificial-intelligence-research/trustworthy-ai?utm_medium=web&utm_campaign=cseai&utm_source=caltechnews&utm_content=&utm_term=">how AI is used</a> go beyond its potential for abetting plagiarism. These AI systems have also found a home in the legal system, where they have been criticized for automatically providing harsher sentences for Black people convicted of crimes than white people convicted of similar crimes.</p><p data-block-key="1cuc2">"These automated decision processes are being used in incarceration and for granting parole," he says. "We didn't have a discussion about them in time as a society, and now we're scrambling to find out what sort of recourse we have for decisions made by these automated procedures."</p><p data-block-key="94bg1">Similar discussions should be held, Eberhardt and Alvarez say, about when and how biological tools like gene editing are used, and about other ethical issues regarding biomedical research.</p><p data-block-key="c75jm">For those kinds of conversations to happen before a new technology becomes entrenched, perhaps in an irresponsible way, Eberhardt and Alvarez say scientists and researchers need to understand the process of how scientific results are translated into policy. Having such conversations with policy makers would also help the public understand why research is important, and in turn, it would help the policy makers decide what kind of rules or priorities to lay out.</p><p data-block-key="8hpdv">"There's this huge gap between doing the scientific research, considering the impact of that sort of scientific research, communicating that scientific research out to the public, understanding what the regulations are, and how to shape those sorts of regulations," Eberhardt says. "The underlying goal of this center is to make students, postdocs, and faculty literate in this disconnect and make them able to bridge it. I think the hope is that we might actually have some influence on policymaking."</p><p data-block-key="a1lnu">Alvarez says students will be a vital part of that effort.</p><p data-block-key="c4q80">"It's very clear that there are a lot of Caltech students who want to make a difference in the world. They want their science to matter," he says. "What we hope is that, through public events, connecting students with policy makers, and helping them understand how to communicate their research in policy-relevant and public-relevant ways, more students will get involved directly in policy making and be better equipped to be consumers of policy information. Whatever career path they pursue, we hope they will be better able to make their science relevant to the world around them."</p><p data-block-key="6t9sg">Eventually, the center will offer courses for students, a discussion forum for Summer Undergraduate Research Fellowship (SURF) students on science policy careers, as well as research projects for students and faculty members. The center's public programming efforts will begin May 5 with <a href="https://www.hss.caltech.edu/news-and-events/calendar/csspp-workshop-panel">a panel discussion on generative AI</a>.</p>