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What can Neuroscience Contribute to the Debate Over Nudging?

Review of Philosophy and Psychology volume 6, pages 469–479 (2015)Cite this article

Abstract

Strategies for improving individual decision making have attracted attention from a range of disciplines. Surprisingly, neuroscience has been largely absent from this conversation, despite the fact that it has recently begun illuminating the neural bases of how and why we make decisions, and is poised for further such advances. Here we address empirical and normative questions about “nudging” through the lens of neuroscience. We suggest that the neuroscience of decision making can provide a framework for understanding how nudges work, and how they can be improved. Towards this end, we first examine how nudges can be incorporated into a leading model of decision making supported by neurobiological data, and use the model to make predictions about the relative effectiveness of different classes of nudges. We then use the model to demonstrate how nudges can both infringe upon and promote autonomy. Finally, we explore the normative implications of the converging consensus from neuroscience and related fields that many everyday decisions are susceptible to covert external influences.

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Fig. 1

Notes

  1. For simplicity of description and display we consider only two possible options and assume that one must be chosen; key features of the model can be extended to explain decisions among multiple alternatives (Bogacz et al. 2007).

  2. A nudge is one example of an external influence on decisions, other forms of which (e.g., recent trial history) have been shown to result in a similar shift in the starting position of the DV (Bode et al. 2012). Equivalently, any such influence (including nudges) can be thought to decrease the distance to the preferred bound or increase the distance to the “non-preferred bound.” As discussed below, nudges can also be modeled as a change in the drift rate of the DV towards the preferred bound.

  3. This prediction has been tested in the framework of the neurobiological experiments described above: Stimulating neurons in the medial temporal lobe, which represent stimulus motion and therefore increases the drift rate of the DV, has an even larger effect on choice than stimulating lateral intraparietal neurons, which adds an offset to the DV (Ditterich et al. 2003; Hanks et al. 2006).

  4. While a nudge may not be exclusively covert or overt, it may still exert its influence more covertly than overtly, or vice versa.

References

  • Badre, D. 2008. Cognitive control, hierarchy, and the rostro-caudal organization of the frontal lobes. Trends in Cognitive Sciences 12(5): 193–200.

    Article  Google Scholar 

  • Berker, S. 2009. The normative insignificance of neuroscience. Philosophy and Public Affairs 37(4): 293–329.

    Article  Google Scholar 

  • Blumenthal-Barby, J.S. 2013. Choice architecture: improving choice while preserving liberty? In Paternalism: theory and practice, ed. C. Coons and M. Weber, 178–196. Cambridge: Cambridge University Press.

    Chapter  Google Scholar 

  • Bode, S., C. Murawski, C.S. Soon, P. Bode, J. Stahl, and P.L. Smith. 2014. Demystifying “free will”: the role of contextual information and evidence accumulation for predictive brain activity. Neuroscience & Biobehavioral Reviews 47: 636–645.

    Article  Google Scholar 

  • Bode, S., D.K. Sewell, S. Lilburn, J.D. Forte, P.L. Smith, and J. Stahl. 2012. Predicting perceptual decision biases from early brain activity. The Journal of Neuroscience 32(36): 12488–12498.

    Article  Google Scholar 

  • Bogacz, R., M. Usher, J. Zhang, and J.L. McClelland. 2007. Extending a biologically inspired model of choice: multi-alternatives, nonlinearity and value-based multidimensional choice. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 362(1485): 1655–1670.

    Article  Google Scholar 

  • Bovens, L. 2009. The ethics of nudge. In Preference change: Approaches from Philosophy, Economics and Psychology, ed. T. Grüne-Yanoff and S.O. Hansson, 207–219. Dordrecht: Springer.

  • Camerer, C., S. Issacharoff, G. Loewenstein, T. O’Donoghue, and M. Rabin. 2003. Regulation for conservatives: behavioral economics and the case for “asymmetric paternalism.”. University of Pennsylvania Law Review 151(3): 1211–1254.

    Article  Google Scholar 

  • Carandini, M., and A.K. Churchland. 2013. Probing perceptual decisions in rodents. Nature Neuroscience 16(7): 824–831.

    Article  Google Scholar 

  • Carpenter, R.H.S., and M.L.L. Williams. 1995. Neural computation of log likelihood in control of saccadic eye movements. Nature 377(6544): 59–62.

    Article  Google Scholar 

  • Custers, R., and H. Aarts. 2010. The unconscious will: How the pursuit of goals operates outside of conscious awareness. Science 329(5987): 47–50.

    Article  Google Scholar 

  • DasGupta, S., C.H. Ferreira, and G. Miesenböck. 2014. FoxP influences the speed and accuracy of a perceptual decision in Drosophila. Science 344(6186): 901–904.

    Article  Google Scholar 

  • De Martino, B., D. Kumaran, B. Seymour, and R.J. Dolan. 2006. Frames, biases, and rational decision-making in the human brain. Science 313(5787): 684–687.

    Article  Google Scholar 

  • Deppe, M., W. Schwindt, H. Kugel, H. Plassmann, and P. Kenning. 2005. Nonlinear responses within the medial prefrontal cortex reveal when specific implicit information influences economic decision making. Journal of Neuroimaging 15(2): 171–182.

    Article  Google Scholar 

  • Ditterich, J., M.E. Mazurek, and M.N. Shadlen. 2003. Microstimulation of visual cortex affects the speed of perceptual decisions. Nature Neuroscience 6(8): 891–898.

    Article  Google Scholar 

  • Downs, J.S., G. Loewenstein, and J. Wisdom. 2009. Strategies for promoting healthier food choices. American Economic Review 99(2): 159–164.

    Article  Google Scholar 

  • Dworkin, G. 1988. The theory and practice of autonomy. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Felsen, G., and P.B. Reiner. 2011. How the neuroscience of decision making informs our conception of autonomy. American Journal of Bioethics Neuroscience 2(3): 3–14.

    Google Scholar 

  • Frankfurt, H. 1971. Freedom of the will and the concept of a person. The Journal of Philosophy 68: 5–20.

    Article  Google Scholar 

  • Gilaie-Dotan, S., A. Tymula, N. Cooper, J.W. Kable, P.W. Glimcher, and I. Levy. 2014. Neuroanatomy predicts individual risk attitudes. The Journal of Neuroscience 34(37): 12394–12401.

    Article  Google Scholar 

  • Gold, J.I., and M.N. Shadlen. 2007. The neural basis of decision making. Annual Review of Neuroscience 30: 535–574.

    Article  Google Scholar 

  • Graybiel, A.M. 2008. Habits, rituals, and the evaluative brain. Annual Review of Neuroscience 31(1): 359–387.

    Article  Google Scholar 

  • Greene, J. 2003. From neural “is” to moral “ought”: what are the moral implications of neuroscientific moral psychology? Nature Reviews Neuroscience 4(10): 846–850.

    Article  Google Scholar 

  • Greene, J.D. 2014. Beyond point-and-shoot morality: Why cognitive (neuro)science matters for ethics. Ethics 124(4): 695–726.

    Article  Google Scholar 

  • Grüne-Yanoff, T. 2012. Old wine in new casks: libertarian paternalism still violates liberal principles. Social Choice and Welfare 38(4): 635–645.

    Article  Google Scholar 

  • Hanks, T.D., J. Ditterich, and M.N. Shadlen. 2006. Microstimulation of macaque area LIP affects decision-making in a motion discrimination task. Nature Neuroscience 9(5): 682–689.

    Article  Google Scholar 

  • Hikosaka, O., H.F. Kim, M. Yasuda, and S. Yamamoto. 2014. Basal ganglia circuits for reward value–guided behavior. Annual Review of Neuroscience 37(1): 289–306.

    Article  Google Scholar 

  • Hill, T. 1989. The Kantian conception of autonomy. In The inner citadel: essays on individual autonomy, ed. J.P. Christman, 91–108. New York: Oxford University Press.

    Google Scholar 

  • Insel, T.R., S.C. Landis, and F.S. Collins. 2013. The NIH BRAIN initiative. Science 340(6133): 687–688.

    Article  Google Scholar 

  • Jolls, C., and C.R. Sunstein. 2006. Debiasing through law. The Journal of Legal Studies 35(1): 199–242.

    Article  Google Scholar 

  • Jolls, C., C.R. Sunstein, and R. Thaler. 1998. A behavioral approach to law and economics. Stanford Law Review 50(5): 1471–1550.

    Article  Google Scholar 

  • Jucker, M. 2010. The benefits and limitations of animal models for translational research in neurodegenerative diseases. Nature Medicine 16(11): 1210–1214.

    Article  Google Scholar 

  • Kahneman, D. 2011. Thinking, fast and slow. New York: Farrar, Straus, and Giroux.

    Google Scholar 

  • Kamm, F.M. 2009. Neuroscience and moral reasoning: a note on recent research. Philosophy and Public Affairs 37(4): 330–345.

    Article  Google Scholar 

  • Levy, D.J., and P.W. Glimcher. 2012. The root of all value: a neural common currency for choice. Current Opinion in Neurobiology 22(6): 1027–1038.

    Article  Google Scholar 

  • Mattler, U., and S. Palmer. 2012. Time course of free-choice priming effects explained by a simple accumulator model. Cognition 123(3): 347–360.

    Article  Google Scholar 

  • Mazurek, M.E., J.D. Roitman, J. Ditterich, and M.N. Shadlen. 2003. A role for neural integrators in perceptual decision making. Cerebral Cortex 13(11): 1257–1269.

    Article  Google Scholar 

  • Mitchell, G. 2004. Libertarian paternalism is an oxymoron. Northwestern University Law Review 99: 1245–1277.

    Google Scholar 

  • Mulder, M.J., E.-J. Wagenmakers, R. Ratcliff, W. Boekel, and B.U. Forstmann. 2012. Bias in the brain: a diffusion model analysis of prior probability and potential payoff. The Journal of Neuroscience 32(7): 2335–2343.

    Article  Google Scholar 

  • Murawski, C., P.G. Harris, S. Bode, D.J.F. Domínguez, and G.F. Egan. 2012. Led into temptation? rewarding brand logos bias the neural encoding of incidental economic decisions. PLOS ONE 7(3): e34155.

    Article  Google Scholar 

  • Newsome, W.T., K.H. Britten, and J.A. Movshon. 1989. Neuronal correlates of a perceptual decision. Nature 341(6237): 52–54.

  • Ratcliff, R., and J.N. Rouder. 1998. Modeling response times for two-choice decisions. Psychological Science 9(5): 347–356.

    Article  Google Scholar 

  • Roitman, J.D., and M.N. Shadlen. 2002. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. The Journal of Neuroscience 22(21): 9475–9489.

    Google Scholar 

  • Roskies, A.L. 2010. How does neuroscience affect our conception of volition? Annual Review of Neuroscience 33(1): 109–130.

    Article  Google Scholar 

  • Schlaghecken, F., and M. Eimer. 2004. Masked prime stimuli can bias ‘free’ choices between response alternatives. Psychonomic Bulletin & Review 11(3): 463–468.

    Article  Google Scholar 

  • Schüür, F., and P. Haggard. 2011. What are self-generated actions? Consciousness and Cognition 20(4): 1697–1704.

    Article  Google Scholar 

  • Shadlen, M.N., and R. Kiani. 2013. Decision making as a window on cognition. Neuron 80(3): 791–806.

    Article  Google Scholar 

  • Shadlen, M.N., and A.L. Roskies. 2012. The neurobiology of decision-making and responsibility: reconciling mechanism and mindedness. Frontiers in Decision Neuroscience 6: 56.

    Google Scholar 

  • Sinclair, S.E., M. Cooper, and E.D. Mansfield. 2014. The influence of menu labeling on calories selected or consumed: a systematic review and meta-analysis. Journal of the Academy of Nutrition and Dietetics 114(9): 1375–1388.

    Article  Google Scholar 

  • Singer, P. 2005. Ethics and intuitions. The Journal of Ethics 9(3–4): 331–352.

    Article  Google Scholar 

  • Smith, P.L., and R. Ratcliff. 2004. Psychology and neurobiology of simple decisions. Trends in Neurosciences 27(3): 161–168.

    Article  Google Scholar 

  • Sunstein, C.R. 2011. Empirically informed regulation. The University of Chicago Law Review 78(4): 1349–1429.

    Google Scholar 

  • Sunstein, C.R. 2014. Why nudge?: the politics of libertarian paternalism. New Haven: Yale University Press.

    Google Scholar 

  • Sunstein, C.R., and R.H. Thaler. 2003. Libertarian paternalism is not an oxymoron. University of Chicago Law Review 70: 1159–1202.

    Article  Google Scholar 

  • Thaler, R.H., and C.R. Sunstein. 2008. Nudge: improving decisions about health, wealth, and happiness. New Haven: Yale University Press.

    Google Scholar 

  • Tom, S.M., C.R. Fox, C. Trepel, and R.A. Poldrack. 2007. The neural basis of loss aversion in decision-making under risk. Science 315(5811): 515–518.

    Article  Google Scholar 

  • White, M.D. 2013. The manipulation of choice: ethics and libertarian paternalism. New York: Palgrave Macmillan.

    Book  Google Scholar 

  • Wisdom, J., J.S. Downs, and G. Loewenstein. 2010. Promoting healthy choices: information versus convenience. American Economic Journal: Applied Economics 2(2): 164–178.

    Google Scholar 

  • Yu, R., D. Mobbs, B. Seymour, and A.J. Calder. 2010. Insula and striatum mediate the default bias. The Journal of Neuroscience 30(44): 14702–14707.

    Article  Google Scholar 

  • Zhang, Y., J. Xu, Zixi Jiang, and S.C. Huang. 2011. Been there, done that: the impact of effort investment on goal value and consumer motivation. Journal of Consumer Research 38(1): 78–93.

    Article  Google Scholar 

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Acknowledgments

We thank the editors and two anonymous reviewers for their constructive suggestions. This work was supported by the Greenwall Foundation’s Faculty Scholars Program in Bioethics (G. F.).

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Authors and Affiliations

  1. Department of Physiology and Biophysics, University of Colorado School of Medicine, 12800 E. 19th Ave., Mail Stop 8307, Aurora, CO, 80045, USA

    Gidon Felsen

  2. Center for Bioethics and Humanities, University of Colorado, 13080 E. 19th Ave., Mail Stop B137, Aurora, CO, 80045, USA

    Gidon Felsen

  3. National Core for Neuroethics, University of British Columbia, 2211 Westbrook Mall, Vancouver, BC, V6T 2B5, Canada

    Gidon Felsen & Peter B. Reiner

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  1. Gidon Felsen
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Felsen, G., Reiner, P.B. What can Neuroscience Contribute to the Debate Over Nudging?. Rev.Phil.Psych. 6, 469–479 (2015). https://doi.org/10.1007/s13164-015-0240-9

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Keywords

  • Decision Variable
  • Starting Position
  • Drift Rate
  • External Influence
  • Choice Architect