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.

Democracy and filtering

Abstract: The Web gives us the ability to filter out unwanted noise and to create our own personal echo chambers---but democracy itself means each of us should be exposed to new topics and contrary opinions.

On Discounting Regulatory Benefits: Risk, Money, and Ingergenerational Equity

Abstract: There is an elaborate debate over the practice of “discounting” regulatory benefits, such as environmental improvements and decreased risks to health and life, when those benefits will not be enjoyed until some future date. Economists tend to think that, as a general rule, such benefits should be discounted in the same way as money; many philosophers and lawyers doubt that conclusion on empirical and normative grounds. Both sides neglect a simple point: Once government has converted regulatory benefits into monetary equivalents, what is being discounted is merely money, not regulatory benefits as such. No one seeks to discount health and life—only the money that might be used to reduce threats to these goods. To be sure, cost-benefit analysis with discounting can produce serious problems of intergenerational equity; but those problems, involving the obligations of the present to the future, require an independent analysis. Failing to discount will often hurt, rather than help, future generations. Solutions to the problem of intergenerational equity should not be conflated with the question whether to discount. Suppose that a proposed regulation will not produce benefits for some period of years; suppose too that an agency is asked to engage in some form of cost-benefit analysis before it proceeds with the regulation. Costs will be discounted, on the theory that a dollar today is worth more than a dollar in twenty years. But what should the agency do about future benefits, such as improved health or averted deaths? Should these too be "discounted," or should a death in 2025 be treated the same as a death today? In terms of ultimate outcomes, the choice matters a great deal. If an agency chooses not to discount, the benefits calculation will shift dramatically from what it would be if the agency chose a discount rate of, for example, 10%. If a human life is valued at $8 million, and no discount rate is applied, a life saved 100 years from now is * Karl N. Llewellyn Distinguished Service Professor, Law School and Department of Political Science, University of Chicago. ** University of Chicago Law School, J.D. expected 2006. Thanks to Blake Roberts for excellent research assistance; to Matthew Adler, Robert Hahn, Bernard Harcourt, John Morrall, Eric Posner, Richard Posner, and David Weisbach for valuable comments; and to participants in an exceedingly helpful work-inprogress lunch at the University of Chicago Law School.

Discrimination in the Age of Algorithms

Abstract: The law forbids discrimination. But the ambiguity of human decision-making often makes it extraordinarily hard for the legal system to know whether anyone has actually discriminated. To understand how algorithms affect discrimination, we must therefore also understand how they affect the problem of detecting discrimination. By one measure, algorithms are fundamentally opaque, not just cognitively but even mathematically. Yet for the task of proving discrimination, processes involving algorithms can provide crucial forms of transparency that are otherwise unavailable. These benefits do not happen automatically. But with appropriate requirements in place, the use of algorithms will make it possible to more easily examine and interrogate the entire decision process, thereby making it far easier to know whether discrimination has occurred. By forcing a new level of specificity, the use of algorithms also highlights, and makes transparent, central tradeoffs among competing values. Algorithms are not only a threat to be regulated; with the right safeguards in place, they have the potential to be a positive force for equity.

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.