Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-14T22:46:54.061Z Has data issue: false hasContentIssue false

Valuation mechanisms in moral cognition

Published online by Cambridge University Press:  11 September 2019

Julia Haas*
Affiliation:
Department of Philosophy, Rhodes College, Memphis, TN 38112. Haasj2@rhodes.eduwww.juliashaas.com

Abstract

May cites a body of evidence suggesting that participants take consequences, personal harm, and other factors into consideration when making moral judgments. This evidence is used to support the conclusion that moral cognition relies on rule-based inference. This commentary defends an alternative interpretation of this evidence, namely, that it can be explained in terms of domain general valuation mechanisms.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ayars, A. (2016) Can model-free reinforcement learning explain deontological moral judgments? Cognition 150:232–42.Google Scholar
Berns, G. S., Bell, E., Capra, C. M., Prietula, M. J., Moore, S., Anderson, B., Ginges, J. & Atran, S. (2012) The price of your soul: Neural evidence for the non-utilitarian representation of sacred values. Philosophical Transactions of the Royal Society B 367(1589):754–62.Google Scholar
Bloom, P. (2013) Just babies: The origins of good and evil. Crown.Google Scholar
Crockett, M. J. (2013) Models of morality. Trends in Cognitive Sciences 17(8):363–66.Google Scholar
Crockett, M. J. (2016a) Computational modeling of moral decisions. In: The social psychology of morality, ed. Forgas, J. P., Jussim, L. & Van Lange, P. A. M., pp. 87106. Psychology Press.Google Scholar
Crockett, M. J. (2016b) How formal models can illuminate mechanisms of moral judgment and decision making. Current Directions in Psychological Science 25(2):8590.Google Scholar
Cushman, F. (2013) Action, outcome and value: A dual-system framework for morality. Personality and Social Psychology Review 17(3): 273–92.Google Scholar
Cushman, F. (2015) From moral concern to moral constraint. Current Opinion in Behavioral Sciences 3:5862.Google Scholar
Dayan, P. & Abbott, L. F. (2001) Theoretical neuroscience: Computational and mathematical modeling of neural systems. MIT Press.Google Scholar
Dayan, P. & Niv, Y. (2008) Reinforcement learning: The good, the bad and the ugly. Current opinion in neurobiology 18(2):185–96.Google Scholar
Fehr, E., Fischbacher, U. & Kosfeld, M. (2005) Neuroeconomic foundations of trust and social preferences: Initial evidence. American Economic Review 95(2):346–51.Google Scholar
Glimcher, P. W., Camerer, C. F., Fehr, E. & Poldrack, R. A. (2009) Neuroeconomics: Decision making and the brain. Elsevier.Google Scholar
Huebner, B. (2016) Implicit bias, reinforcement learning, and scaffolded moral cognition. In: Implicit bias and philosophy: Vol. 1, Meta- physics and epistemology, ed. Brownstein, M. & Saul, J., pp. 4779. Oxford University Press.Google Scholar
Mackintosh, N. J. (1983) Conditioning and associative learning. Oxford University Press.Google Scholar
May, J. (2018) Regard for reason in the moral mind. Oxford University Press.Google Scholar
Montgomery, M. A., Kappes, A. & Crockett, M. J. (2017) Compassion is not always a motivated choice: A multiple decision systems perspective. Moral psychology: Vol. 5, Virtue and character, ed. Sinnott-Armstrong, W. & Miller, C. B., pp. 409–18. MIT Press.Google Scholar
Rangel, A., Camerer, C. & Montague, P. R. (2008) A framework for studying the neurobiology of value-based decision making. Nature reviews neuroscience 9(7):545.Google Scholar
Shenhav, A. & Greene, J. D. (2010) Moral judgments recruit domain-general valuation mechanisms to integrate representations of probability and magnitude. Neuron 67(4):667–77.Google Scholar
Sutton, R. S. & Barto, A. G. (1998) Introduction to reinforcement learning, vol. 135. MIT Press.Google Scholar