Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-19T05:47:44.621Z Has data issue: false hasContentIssue false
  • English
  • Français

Recognize Everyone’s Interests: An Algorithm for Ethical Decision-Making about Trade-Off Problems

Published online by Cambridge University Press:  06 October 2020

Tobey K. Scharding
Tobey K. Scharding*
Affiliation:
Rutgers University
Get access Rights & Permissions [Opens in a new window]

Abstract

This article addresses a dilemma about autonomous vehicles: how to respond to trade-off scenarios in which all possible responses involve the loss of life but there is a choice about whose life or lives are lost. I consider four options: kill fewer people, protect passengers, equal concern for survival, and recognize everyone’s interests. I solve this dilemma via what I call the new trolley problem, which seeks a rationale for the intuition that it is unethical to kill a smaller number of people to avoid killing a greater number of people based on numbers alone. I argue that killing a smaller number of people to avoid killing a greater number of people based on numbers alone is unethical because it disrespects the humanity of the individuals in the smaller-numbered group. I defend the recognize-everyone’s-interests algorithm, which will probably kill fewer people but will not do so based on numbers alone.

Keywords

trade-off problemsalgorithmsautonomous vehiclesrespect for humanitytrolley problem
Type
Article
Information
Business Ethics Quarterly , Volume 31 , Issue 3 , July 2021 , pp. 450 - 473
Copyright
© The Author(s) 2020. Published by Cambridge University Press on behalf of the Society for Business Ethics

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

Ahlenius, H., & Tännsjö, T. 2012. Chinese and Westerns respond differently to the trolley dilemmas. Journal of Cognition and Culture, 12: 195–201.CrossRefGoogle Scholar
Arnold, D. G., & Bowie, N. E. 2003. Sweatshops and respect for persons. Business Ethics Quarterly, 1(2): 221–42.CrossRefGoogle Scholar
Arrigoni, S., Cheli, F., Manazza, S., Gottardis, P., Happee, R., Arat, M., & Kotiadis, D. 2016. Autonomous vehicle controlled by safety path planner with collision risk estimation coupled with a non-linear MPC. Proceedings of the 24th symposium of the International Association for Vehicle System Dynamics, Graz, Austria: 199–208. Boca Raton, FL: CRC Press.Google Scholar
Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J.-F., & Rahwan, I. 2018. The moral machine experiment. Nature, 563(7729): 59–64.CrossRefGoogle ScholarPubMed
Barry, B. 1995. Justice as impartiality. New York: Oxford University Press.Google Scholar
Bentham, J. 1789/1961. An introduction to the principles of morals and legislation. Garden City, NY: Doubleday.CrossRefGoogle Scholar
Bhargava, V., & Kim, T. W. 2017. Autonomous vehicles and moral uncertainty. In Lin, P., Abney, K., & Jenkins, R. (Eds.), Robot ethics 2.0: From autonomous cars to artificial intelligence: 5–19. New York: Oxford University Press.Google Scholar
Bonnefon, J.-F., Shariff, A., & Rahwan, I. 2016. The social dilemma of autonomous vehicles. Science, 352(6293): 1573–76.CrossRefGoogle ScholarPubMed
Brodsky, J. S. 2016. Autonomous vehicle regulation: How an uncertain legal landscape may hit the brakes on self-driving cars. Berkeley Technology Law Journal, 31(2): 851–878.Google Scholar
Colonna, K. 2012. Autonomous cars and tort liability. Journal of Law, Technology, and the Internet, 4(4): 81–131.Google Scholar
Colson, E. 2019. What AI-driven decision making looks like. Harvard Business Review, July. https://hbr.org/2019/07/what-ai-driven-decision-making-looks-like.Google Scholar
Corbett-Davies, S., Pierson, E., Feller, A., Goel, S., & Huq, A. 2017. Algorithmic decision making and the cost of fairness. Proceedings of KDD’17, Halifax, NS, Canada. DOI:10.1145/3097983.3098095.CrossRefGoogle Scholar
Cureton, A. 2009. Degrees of fairness and proportional chances. Utilitas, 21(2): 217–21.CrossRefGoogle Scholar
Duffy, S. H., & Hopkins, J. P. 2013. Sit, stay, drive: The future of autonomous car liability. Science and Technology Law Review, 16(3): 453–80.Google Scholar
Foot, P. 1967. The problem of abortion and the doctrine of the double effect. Oxford Review, 5: 5–15.Google Scholar
Gertken, J. 2016. Mixed feelings about mixed solutions. Ethical Theory and Moral Practice, 19: 59–69.CrossRefGoogle Scholar
Gold, N., Colman, A. M., & Pulford, B. D. 2014. Cultural differences in responses to real-life and hypothetical trolley problems. Judgment and Decision Making, 9: 65–76.Google Scholar
Goodall, N. J. 2016. Can you program ethics into a self-driving car? IEEE Spectrum, 53: 28–58.CrossRefGoogle Scholar
Greene, J., Sommerville, R., Nystrom, L., Darley, J., & Cohen, J. 2001. An fMRI investigation of emotional engagement in moral judgment. Science, 293: 2105–8.CrossRefGoogle ScholarPubMed
Gustafson, A. 2013. In defense of a utilitarian business ethic. Business and Society Review, 118(3): 325–60.CrossRefGoogle Scholar
Halstead, J. 2016. The numbers always count. Ethics, 126(3): 789–802.CrossRefGoogle Scholar
Henning, T. 2015. From choice to chance? Saving people, fairness, and lotteries. The Philosophical Review, 124(2): 169–206.CrossRefGoogle Scholar
Hill, T. 1992. Dignity and practical reason in Kant’s moral theory. Ithaca, NY: Cornell University Press.Google Scholar
Hirose, I. 2004. Aggregation and numbers. Utilitas, 16(1): 62–79.CrossRefGoogle Scholar
Hsieh, N.-H., Strudler, A., & Wasserman, D. 2006. The numbers problem. Philosophy and Public Affairs, 34(4): 352–72.CrossRefGoogle Scholar
Johnson, D. G. 2015. Technology with no human responsibility? Journal of Business Ethics, 127(4): 707–15.CrossRefGoogle Scholar
Kamm, F. M. 1985. Equal treatment and equal chances. Philosophy and Public Affairs, 14(2): 177–94.Google Scholar
Kant, I. 1785/2002. Groundwork for the metaphysics of morals. T. K. Abbot (Trans.). New York: Oxford University Press.Google Scholar
Kavka, G. S. 1979. The numbers should count. Philosophical Studies, 36(3): 285–94.CrossRefGoogle Scholar
Lanteri, A., Chelini, C., & Rizzello, S. 2008. An experimental investigation of emotions and reasoning in the trolley problem. Journal of Business Ethics, 83(4): 789–804.CrossRefGoogle Scholar
Lawlor, R. 2006. Taurek, numbers, and probability. Ethical Theory and Moral Practice, 9: 149–66.CrossRefGoogle Scholar
Lazenby, H. 2014. Broome on fairness and lotteries. Utilitas, 26(4): 331–45.CrossRefGoogle Scholar
Leicht-Deobald, U., Busch, T., Schank, C., Weibel, A., Schafheitle, S., Wildhaber, I., & Kasper, G. 2019. The challenges of algorithm-based HR decision-making for personal integrity. Journal of Business Ethics, 160: 377–92.CrossRefGoogle ScholarPubMed
Lin, P. 2016. Why ethics matters for autonomous cars. In Maurer, M., Gerdes, J. C., Lenz, B., & Winner, H. (Eds.), Autonomous driving: Technical, legal, and social aspects: 69–85. Berlin: Springer.Google Scholar
Lubbe, W. 2008. Taurek’s no worse claim. Philosophy and Public Affairs, 36(1): 69–85.CrossRefGoogle Scholar
Maitland, I. 2002. The human face of self-interest. Journal of Business Ethics, 38(1/2): 3–17.CrossRefGoogle Scholar
Martin, K. 2018. Ethical implications and accountability of algorithms. Journal of Business Ethics, 160(4): 835–50.CrossRefGoogle Scholar
Millar, J. 2017. Ethics settings for autonomous vehicles. In Lin, P., Abney, K., & Jenkins, R. (Eds.), Robot ethics 2.0: From autonomous cars to artificial intelligence: 20–34. New York: Oxford University Press.Google Scholar
Miller, R. W. 1998. Cosmopolitan respect and patriotic concern. Philosophy and Public Affairs, 27(3): 202–24.CrossRefGoogle Scholar
Muller, A. R., Pfarrar, M. D., & Little, L. M. 2014. A theory of collective empathy in corporate philanthropy decisions. Academy of Management Review, 39(1): 1–21.CrossRefGoogle Scholar
Nyholm, S., & Smids, J. 2016. The ethics of accident-algorithms for self-driving cars: An applied trolley problem? Ethical Theory and Moral Practice, 19(5): 1275–89.CrossRefGoogle Scholar
Otsuka, M. 2000. Scanlon and the claims of the many versus the one. Analysis, 60(3): 288–93.CrossRefGoogle Scholar
Parfit, D. 1978. Innumerate ethics. Philosophy and Public Affairs, 7(4): 285–301.Google Scholar
Parmar, B. L., & Freeman, R. E. 2016. Ethics and the algorithm. MIT Sloan Management Review, 58(1). https://sloanreview.mit.edu/article/ethics-and-the-algorithm/.Google Scholar
Scanlon, T. M. 1998. What we owe to each other. Cambridge, MA: Harvard University Press.Google Scholar
Segall, S. 2016. Why inequality matters. Cambridge: Cambridge University Press.Google Scholar
Sidgwick, H. 1907. The methods of ethics. 7th ed. London: Macmillan.Google Scholar
Sinnott-Armstrong, W. 2019. Consequentialism. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy. http://plato.stanford.edu/archives/sum2019/entries/consequentialism.Google Scholar
Taurek, J. M. 1977. Should the numbers count? Philosophy and Public Affairs, 6(4): 293–316.Google ScholarPubMed
Thomson, J. J. 1976. Killing, letting die, and the trolley problem. The Monist, 59(2): 204–17.CrossRefGoogle ScholarPubMed
Thomson, J. J. 1985. The trolley problem. Yale Law Journal, 94(6): 1395–1415.CrossRefGoogle Scholar
Thomson, J. J. 2008. Turning the trolley. Philosophy and Public Affairs, 36(4): 359–74.CrossRefGoogle Scholar
Timmerman, J. 2004. The individualist lottery: How people count, but not their numbers. Analysis, 64(2): 106–12.CrossRefGoogle Scholar
Unger, P. 1996. Living high and letting die: Our illusion of innocence. Oxford: Oxford University Press.CrossRefGoogle Scholar
Villasenor, J. 2014. Products liability and driverless cars: Issues and guiding principles for legislation. Washington, DC: Brookings Institution Press.Google Scholar
Williams, B. 1972. Morality: An introduction to ethics. New York: Harper and Row.Google Scholar
Williams, B. 1981. Moral luck. Cambridge: Cambridge University Press.CrossRefGoogle Scholar