Cass R. Sunstein

Bio: Cass R. Sunstein is an academic researcher from Harvard University. The author has contributed to research in topics: Supreme court & Constitution. The author has an hindex of 117, co-authored 787 publications receiving 57639 citations. Previous affiliations of Cass R. Sunstein include Brigham Young University & Indiana University.

Algorithmic Harm in Consumer Markets

Abstract: Machine learning algorithms are increasingly able to predict what goods and services particular people will buy, and at what price. It is possible to imagine a situation in which relatively uniform, or coarsely set, prices and product characteristics are replaced by far more in the way of individualization. Companies might, for example, offer people shirts and shoes that are particularly suited to their situations, that fit with their particular tastes, and that have prices that fit their personal valuations. In many cases, the use of algorithms promises to increase efficiency and to promote social welfare; it might also promote fair distribution. But when consumers suffer from an absence of information or from behavioral biases, algorithms can cause serious harm. Companies might, for example, exploit such biases in order to lead people to purchase products that have little or no value for them or to pay too much for products that do have value for them. Algorithmic harm, understood as the exploitation of an absence of information or of behavioral biases, can disproportionately affect members of identifiable groups, including women and people of color. Since algorithms exacerbate the harm caused to imperfectly informed and imperfectly rational consumers, their increasing use provides fresh support for existing efforts to reduce information and rationality deficits, especially through optimally designed disclosure mandates. In addition, there is a more particular need for algorithm-centered policy responses. Specifically, algorithmic transparency—transparency about the nature, uses, and consequences of algorithms—is both crucial and challenging; novel methods designed to open the algorithmic “black box” and “interpret” the algorithm’s decision-making process should play a key role. In appropriate cases, regulators should also police the design and implementation of algorithms, with a particular emphasis on exploitation of an absence of information or of behavioral biases. * William J. Friedman and Alicia Townsend Friedman Professor of Law and Economics, Harvard Law School. ** Robert Walmsley University Professor, Harvard Law School. For helpful comments and conversations, we thank Todd Baker, Omri Ben-Shahar, Ben Eidelson, Merritt Fox, Talia Gillis, Shafi Goldwasser, Zohar Goshen, Assaf Hamdani, Sharon Hannes, Howell Jackson, Louis Kaplow, Emiliano Katan, Avery Katz, Tamar Kricheli-Katz, Haggai Porat, Lucia Reisch, Ricky Revesz, Sarath Sanga, Alan Schwartz, Steve Shavell, Yonadav Shavit, Holger Spamann, Eric Talley, Rory Van Loo, and workshop and conference participants at Columbia, Harvard, Tel-Aviv University, [...] and at the 2022 Annual Meeting of the American Law and Economics Association. Ethan Judd, Rachel Neuburger and Davy Perlman provided excellent research assistance. *** Assistant Professor, Technion – Israel Institute of Technology, The Henry and Marilyn Taub Faculty of Computer Science. Electronic copy available at: https://ssrn.com/abstract=4321763

Libertarian paternalism is not an oxymoron

Abstract: The idea of libertarian paternalism might seem to be an oxymoron, but it is both possible and legitimate for private and public institutions to affect behavior while also respecting freedom of choice. Often people's preferences are ill-formed, and their choices will inevitably be influenced by default rules, framing effects, and starting points. In these circumstances, a form of paternalism cannot be avoided. Equipped with an understanding of behavioral findings of bounded rationality and bounded self-control, libertarian paternalists should attempt to steer people's choices in welfare-promoting directions without eliminating freedom of choice. It is also possible to show how a libertarian paternalist might select among the possible options and to assess how much choice to offer. Examples are given from many areas, including savings behavior, labor law, and consumer protection.

Unhelpful Abstractions and the Standard View

Abstract: It is not fruitful to puzzle over the question whether economists and others ‘favor’ or ‘lean’ toward the regulatory or welfare state; that is an unhelpful and confusing question, one that orients people in the wrong way. It is better to begin by emphasizing that the first should be designed to handle market failures, and that the second should be designed to respond to economic deprivation and unjustified inequality.

The Statements I Most Regret

Abstract: It would be a real problem for an academic to have said little or nothing that he regrets. I have said a lot of things that I regret—even that make me squirm—and in this essay I present the worst of the worst. But a main job of academics is to float ideas and take risks, and if they do not make mistakes, or learn enough to change their minds, then that’s really something to regret.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

The behaviour change wheel: a new method for characterising and designing behaviour change interventions.

Abstract: Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a 'behaviour system' involving three essential conditions: capability, opportunity, and motivation (what we term the 'COM-B system'). This forms the hub of a 'behaviour change wheel' (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health's 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence's guidance on reducing obesity. Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a 'behaviour system' at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions.

International Norm Dynamics and Political Change

Abstract: Norms have never been absent from the study of international politics, but the sweeping “ideational turn” in the 1980s and 1990s brought them back as a central theoretical concern in the field. Much theorizing about norms has focused on how they create social structure, standards of appropriateness, and stability in international politics. Recent empirical research on norms, in contrast, has examined their role in creating political change, but change processes have been less well-theorized. We induce from this research a variety of theoretical arguments and testable hypotheses about the role of norms in political change. We argue that norms evolve in a three-stage “life cycle” of emergence, “norm cascades,” and internalization, and that each stage is governed by different motives, mechanisms, and behavioral logics. We also highlight the rational and strategic nature of many social construction processes and argue that theoretical progress will only be made by placing attention on the connections between norms and rationality rather than by opposing the two.

Risk as Feelings

Abstract: Virtually all current theories of choice under risk or uncertainty are cognitive and consequentialist. They assume that people assess the desirability and likelihood of possible outcomes of choice alternatives and integrate this information through some type of expectation-based calculus to arrive at decision. The authors propose an alternative theoretical perspective, the risk-as-feelings hypothesis, that highlights the role of affect experienced at the moment of decision making. Drawing on research from clinical, physiological, and other subfield of psychology, they show that emotional reactions to risky situations often drive behavior. The risk-as-feelings hypothesis is shown to explain a wide range of phenomena that have resisted interpretation in cognitive-consequentialist terms.

A perspective on judgment and choice: Mapping bounded rationality.

Abstract: Early studies of intuitive judgment and decision making conducted with the late Amos Tversky are reviewed in the context of two related concepts: an analysis of accessibility, the ease with which thoughts come to mind; a distinction between effortless intuition and deliberate reasoning. Intuitive thoughts, like percepts, are highly accessible. Determinants and consequences of accessibility help explain the central results of prospect theory, framing effects, the heuristic process of attribute substitution, and the characteristic biases that result from the substitution of nonextensional for extensional attributes. Variations in the accessibility of rules explain the occasional corrections of intuitive judgments. The study of biases is compatible with a view of intuitive thinking and decision making as generally skilled and successful.