Nudges, as characterized by Thaler and Sunstein (2008), aim to improve personal and societal welfare by steering our decision-making through insights from psychology and behavioral economics, without limiting freedom of choice. Nudges are designed to be easy and cheap to avoid. The nudge program is now global, with many governments adopting behavioral insights units in order to inform new social policies. So what’s the problem? Such an influential program of work has invited much debate, and so to push this into new directions this three-part series aims to communicate cutting edge insights on nudge, specifically concerning its evidential support, its theoretical basis, and its ethical acceptability.
The first part presented the foundations of the nudge programme in order to set up the second part of this piece which takes the form of a Q and A. In the second part three academics involved in the theory and practice of nudging describe their take on each of the three issues posed as questions to them. In this final part the aim is to summarize these answers and offer some ideas about how to move the nudge program ahead in ways that surmount some of the issues raised.
* * *
Building an evidence base: When it comes to assessing the effectiveness of a BCT, a practical solution offered by Weber is to have a publically accessible database of field trials that are being conducted globally. As all the contributors have indicated, a procedural assessment of BCTs is important, both for normative (Chater) and effectiveness evaluations (Grüne-Yanoff). Yet this requires prior procedural knowledge about the BCT. Could this actually be provided? The OECD has vast data-bases on ‘Social Protection and wellbeing’ (http://stats.oecd.org/), under which a record of BCT applications could be included, and updated annually. As it is, most field studies, by necessity should record basic experimental details (e.g., when it was conducted, how long it was implemented for, number of participants, context, outcome measures, see Halpern, 2015). These details are necessary for a data-base for which fruitful analyses could help to answer questions such as ‘if it could be scaled-up, which BCT would work best to improve x behavior at a population level?’. Though, for a data-base of this kind to be useful, there has to be a willingness to be transparent in providing details of proposed trials before they are carried out, and making the results public, whether the trials succeed or not. This will require some political courage, but this is important if progress is to be made.
It is often the case in field studies that more than one BCT is employed to tackle a problem (Dombrowski et al, 2007). This level of transparency would enable researchers, policy makers, and practitioners to have a better grasp of the potential additive, multiplicative, or inhibitory effects (Berman & Johnson, 2015) of combinations of nudges used at any one time. It would also facilitate assessing their relative success vis-à-vis other interventions and/or common policy tools, or providing an appropriate baseline for RCTs.
Developing a psychological process based theory: The successful application of BCTs seem to involve the understanding and utilization of psychological theory, in particular the basic principles of human motivation and cognitive function. That is, we process magnitudes in relative rather than absolute terms, which matters for some BCTs (e.g., sizing of products, relative social comparisons – e.g., awareness of weekly alcohol consumption of peers) as discussed by Chater. Mental effort reduction can enhance the likelihood of making good decisions (Shah & Oppenheimer, 2008), which matters significantly for the effectiveness of automatic defaults, as discussed by Grüne-Yanoff and Weber. While it is possible to point to success stories of such as these, each expert’s response makes some cautionary points, which are worth summarizing here. First, what is needed is an a priori account of the specific causal (psychological) mechanism that is supposed to explain the effect sizes of BCTs observed in lab or field experiments. This is still an ongoing problem, and without an account of the psychological processes that underlie them, the nudge program, and others like it, are not going to progress towards understanding what interventions work when, where, on who, and for how long (Grüne-Yanoff, 2015). Second, basic cognitive functions determine behavior along with individual differences in, for example, value systems (cultural, social, political), and motivational attitudes towards changing behavior will play a significant role in determining the efficacy of certain types of BCTs (Osman, 2014; Saghai, in prep). Therefore, what is needed, is to go beyond a naïve assumption that one single factor is at work when psychology tells us that multiple factors usually underpin a single behavioral outcome (Ouellette, & Wood, 1998), and as emphasized by Weber. So, theory development of BCT effectiveness would do well to exploit this insight.
Ethics: There is a robust evidence base to suggest that life style choices, environmental conditions, and urbanization are highly predictive of chronic health problems, which in turn are associated with several severe mental health conditions (Tost et al., 2015). This makes for a compelling justification to continue work in targeting, through BCTs, poor lifestyle choices that contribute to mental and physical health problems. But as the experts in this essay have highlighted, meddling in the way people conduct their day to day lives raises ethical concerns, even if the meddling is seemingly benign. What are the solutions? One that is borne out of recent survey work (Sunstein, 2016b), is that people prefer to know about the BCT, rather than have them implemented in an opaque manner. To add to this, both Grüne-Yanoff and Chater share the view that ethical issues could be addressed by collective support for a BCT, through transparency, not only of the implementation of BCT themselves, but the rationale for them being used. On the view that choice behavior is not always a reliable way of exposing “true preferences”, Weber makes the point that collective support might also be assessed by looking at the fit between the outcomes of BCTs, that is, what people end up choosing to do, and tracing that back to what they actually want (by asking them), and looking at the correspondence of the two. The more closely aligned behavioral change is to preferred behavior, the more likely it is that the BCT is going to be endorsed, and the less likely it is to be viewed as a breach of autonomy (Osman, 2016).
* * *
Bar-Gill, O., & Sunstein, C. R. (2015). Regulation as delegation. Journal of Legal Analysis, 7, 1-36.
Barton, Adrien & Grüne-Yanoff, Till (2015). From libertarian paternalism to nudging – and beyond. Review of Philosophy and Psychology 6, 341-359.
Benartzi, S., & Thaler, R. H. (2013). Behavioral economics and the retirement savings crisis. Science, 339(6124), 1152-1153.
Berman, E. R., & Johnson, R. K. (2015). The unintended consequences of changes in beverage options and the removal of bottled water on a university campus. American journal of public health, 105(7), 1404-1408.
Beshears, J., J.J. Choi, D. Laibson and B.C. Madrian. 2009. The importance of default options for retirement saving outcomes: Evidence from the United States. In Social security policy in a changing environment, ed. J.R. Brown, J.B. Liebman, and D.A. Wise, 167-195. Chicago: University of Chicago Press.
Brown, J. R., A. M. Farrell and S.J. Weisbenner. 2012. The downside of defaults (No. orrc12-05). National Bureau of Economic Research. (Accessed March 22, 2015) http://www.nber.org/aging/rrc/papers/orrc12-05.pdf
Cartwright, N. & Hardie. J.( 2012). Evidence-based policy: a practical guide to doing it better. Oxford: Oxford University Press.
Castelo, N., Reeck, C., Jachimowicz, J.M., Weber, E.U. & Johnson, E.J. (2016). Who gets nudged? Preferences moderate the influence of defaults on intertemporal choice. Working Paper, Center for Decision Sciences.
Dinner, I., Johnson, E.J., Goldstein, D. G., & Liu, K. (2011). Partitioning Default Effects: Why People Choose not to Choose. Journal of Experimental Psychology: Applied, 17, 332–341.
Dombrowski, S. U., Sniehotta, F. F., Avenell, A., & Coyne, J. C. (2007). Towards a cumulative science of behaviour change: Do current conduct and reporting of behavioural interventions fall short of best practice? Psychology & Health, 22, 869–874.
Garner, W. R. (1953). An informational analysis of absolute judgments of loudness. Journal of Experimental Psychology, 46, 373–380.
Garner, W. R. (1962). Uncertainty and structure and psychological concepts. New York: Wiley.
Gauthier, D. (1986). Morals by Agreement. Oxford: Oxford University Press.
Gigerenzer, G. (2015). On the supposed evidence for libertarian paternalism. Review of philosophy and psychology, 6(3), 361-383.
Grüne-Yanoff, T. (2015) Why Behavioural Policy Needs Mechanistic Evidence. Economics and Philosophy,
Grüne-Yanoff, T., & Hertwig, R. (2016) Nudge Versus Boost: How Coherent are Policy and Theory? Minds and Machines 26: 149-83.
Halpern, D. (2015). Inside the Nudge Unit: How small changes can make a big difference. Random House.
Hausman, D. M., & Welch, B. (2010). Debate: To Nudge or Not to Nudge. Journal of Political Philosophy, 18(1), 123‑136.
Jachimowicz, J. M., Duncan, S., & Weber, E. U. (2016) Default-switching: The hidden cost of defaults. Working Paper, Center for Decision Sciences and SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2727301.
Johnson, E.J., & Goldstein, D.G. (2003) Do defaults save lives? Science, 302, 1338–1339.
Johnson, E.J., (2017). Choice Architecture. [monograph]
Johnson, E.J., Shu, S.B., Dellaert, B.G.C., Fox, C., Goldstein, D.G., Haeubl, G., Larrick, R.P., Payne, J.W., Schkade, D., Wansink, B., & Weber, E.U. (2012). Beyond nudges: Tools of a choice architecture. Marketing Letters, 23, 487-504.
Laming, D. R. J. (1984). The relativity of “absolute” judgements. British Journal of Mathematical and Statistical Psychology, 37, 152–183.
Laming, D. R. J. (1997). The measurement of sensation. Oxford, UK: Oxford University Press.
Levitt, S.D. & List. J.A. (2009). Field experiments in economics: The past, the present, and the future. European Economic Review, 53(1): 1-18.
Lodge, M., & Wegrich, K. (2016). The rationality paradox of Nudge: rational tools of government in a world of bounded rationality. Law & Policy, 38, 250-267.
Misyak, J. B., Melkonyan, T., Zeitoun, H., & Chater, N. (2014). Unwritten rules: virtual bargaining underpins social interaction, culture, and society. Trends in Cognitive Sciences, 18, 512-519.
Oliver, A. (2015). Nudging, shoving, and budging: behavioural economic-informed policy. Public Administration. 93, 700-714.
Osman, M. (2014). Future-minded: The psychology of agency and control. Palgrave Macmillan.
Osman, M. (2016). Nudge: How Far Have We Come? Œconomia. History, Methodology, Philosophy, (6-4), 557-570.
Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: the multiple processes by which past behavior predicts future behavior .Psychological bulletin, 124(1), 54-74
Rebonato (2012). Taking Liberties: A Critical Examination of Libertarian Paternalism. Palgrave Macmillan.
Saghai, Y. (2013). Salvaging the concept of nudge. Journal of Medical Ethics, 39(8), 487-493.
Saghai, Y. (in prep). From research to action: The scalability and generalizability problem in evidence-based health policy.
Sawicki, N. (2016). Ethical Limitations on the State’s Use of Arational Persuasion. Law & Policy, 38, 211-233.
Shah, A. K., & Oppenheimer, D. M. (2008). Heuristics made easy: an effort-reduction
framework. Psychological bulletin, 134(2), 207-222.
Shu, S.B., Bang, M.H., & Weber, E.U. (2016). Informed consent to choice architecture: The role of transparency, intentions, and perceived effectiveness. Under review, Behavioral Science and Policy.
Simon, H. (1997) . Administrative Behavior, 4th ed. New York: Free Press.
Steel, D. (2008). Across the boundaries: Extrapolation in biology and social science. Oxford University Press.
Stewart, N., Brown, G. D., & Chater, N. (2005). Absolute identification by relative judgment. Psychological Review, 112, 881-911.
Stewart, N., Reimers, S., & Harris, A. J. L. (2015). On the origin of utility, weighting, and discounting functions: How they get their shapes and how to change their shapes. Management Science, 61, 687-705.
Sugden, R. (2008). Why incoherent preferences do not justify paternalism. Constitutional Political Economy, 19, 226-248.
Sunstein, Cass R. (2013). Simpler: The Future of Government. New York: Simon & Schuster.
Sunstein, C. R. (2014). Why Nudge?: The Politics of Libertarian Paternalism (The Storrs Lectures Series). Yale University Press.
Sunstein, C. R. (2016a). The ethics of influence: Government in the age of behavioral science. Cambridge Press. UK.
Sunstein, C. R. (2016b). Do People Like Nudges?. Administrative Law Review, Forthcoming.
Tost, H., Champagne, F. A., & Meyer-Lindenberg, A. (2015). Environmental influence in the brain, human welfare and mental health. Nature Neuroscience, 18(10), 1421-1431.
Weber, E. U. & Johnson, E. J. (2009). Mindful judgment and decision making. Annual Review of Psychology, 60, 53-86.
Weber, E. U. (2015). Climate change demands behavioral change: What are the challenges? Social Research: An International Quarterly, 82, 561-581.
Yeung, K. (2016). The Forms and Limits of Choice Architecture as a Tool of Government. Law & Policy, 38, 186-210.
* * *
Nick Chater: Nick Chater joined Warwick Business School in 2010, after holding chairs in psychology at Warwick and UCL. He has over 200 publications, and was elected a Fellow of the Cognitive Science Society in 2010 and a Fellow of the British Academy in 2012. Nick is co-founder of the research consultancy Decision Technology; and is on the advisory board of the Behavioural Insight Team (BIT), popularly known as the ‘Nudge Unit’.
Yashar Saghai: Yashar Saghai is currently a research scholar and associate faculty member at the Berman Institute Johm Hopkins University. His research in applied ethics, political philosophy, and philosophy of science focuses on possible food futures. He engages with several fields, such as: food and agriculture; futures/foresight studies and history; public health and medical research; behavioral economics and cognitive psychology.
Elke Weber: Elke Weber is Gerhard R. Andlinger Professor Princeton University after holding the Jerome A. Chazen Professor of International Business in the Management Division of Columbia Business School and a chair in psychology. She has over 200 publications, is past president of the Society for Mathematical Psychology, the Society for Judgment and Decision Making, and sit on advisory committees of the U.S. National Academy of Sciences.
Till Grüne-Yanoff: Till Grüne-Yanoff is Professor of philosophy at the Royal Institute of Technology (KTH) in Stockholm. He has over 60 publications on the topics of philosophy of science and decision theory, as well as formal models of preference consistency and preference change, and the evaluation of evidence in policy decision making. He is a member of the TINT Finnish Centre of Excellence in the Philosophy of Social Science in Helsinki.
Magda Osman: Magda Osman is Associate Professor of Experimental Psychology at Queen Mary University of London. She has over 60 publications and authored 3 books. Her research interests include dynamic decision-making, agency and control, and critical evaluations of dual-systems of thought. She is head of the Centre for Mind in Society, and sits on various advisory panels, consulting on banking regulation, food safety, and advertising.