Abstract
This independent study examines possible options for programming self-driving cars in cases of moral dilemmas. Option 1 is to program morality respecting people's wishes, examined through the Moral Machine Experiment Survey Dataset. Initial analysis reveals a level of consensus, but further analysis through hierarchical clustering reveals groups of countries divided by cultural differences. We then explore the field of moral intuitions. We examine three objections to trusting intuitions as reflections of moral truth. Intuitions are difficult to accurately collect, affected by factors that aren't morally relevant, and their origin is unknown. The survey responses in the Moral Machine survey are intuitions, which shouldn't be viewed as reflections of morality, leading to a rejection of option 1. Our second option is to respect a moral theory, explored by presenting a possible argument for Utilitarianism, which holds the simple rule that the moral outcome is the one that maximizes utility. We present six tenets explaining this rule, respond to objections, examine flaws, and present practical uses, noting that Utilitarianism requires belief in the initial premise that maximizing utility is good. This belief is characterized as an intuition, and leads to a realization that all three branches of moral theories are dependent on belief in intuitions. Therefore, in the same way as option 1, we reject option 2. We conclude by recommending an option 3, which begins with a modified survey similar to option 1, then uses the method of wide reflective equilibrium to ensure that preferences included are the result of rational thinking rather than biases. While this option is also not objectively true, we believe it is the most practical.
Advisor
Schiltz, Elizabeth
Second Advisor
Horr, Christina
Department
Philosophy; Statistical and Data Sciences
Recommended Citation
Schwartz, Isaac, "How Should Self-Driving Cars be Programmed: Exploring Intuition, Utilitarianism, and the Moral Machine Experiment" (2023). Senior Independent Study Theses. Paper 10507.
https://openworks.wooster.edu/independentstudy/10507
Disciplines
Data Science | Philosophy
Keywords
Self-Driving Cars, Autonomous Vehicles, Programming Ethics, Utilitarianism, Intuition, Experimental Philosophy
Publication Date
2023
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2023 Isaac Schwartz