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Exploring moral algorithm preferences in autonomous vehicle dilemmas: an empirical study.

¹Department of Philosophy, Peking University, Beijing, China.

Frontiers in Psychology

|December 13, 2023

Summary

Participants prefer hybrid ethical algorithms for autonomous vehicles (AVs), balancing self-sacrifice and harm reduction. Many rejected AVs prioritizing owner safety (egoism) or requiring self-sacrifice (utilitarianism).

Keywords:

Egoism Hybrid approach Rawlsianism Utilitarianism autonomous vehicle experimental philosophy is-ought problem moral algorithm

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Area of Science:

Ethics in Artificial Intelligence
Human-Computer Interaction
Autonomous Vehicle Technology

Background:

Autonomous vehicles (AVs) present complex ethical challenges, particularly in programming decision-making algorithms.
The "Trolley Problem" highlights the need for moral algorithms grounded in ethical principles for AVs.
Understanding public perception of AV ethical algorithms is crucial for development and adoption.

Purpose of the Study:

To assess public inclination towards different ethical algorithms for AVs in China.
To investigate participant preferences for Utilitarianism, Rawlsianism, Egoism, and Hybrid approaches.
To analyze the ethical considerations influencing the purchase decisions of autonomous vehicles.

Main Methods:

An online survey adapted from Joshua Greene's trolley dilemma was administered to 460 participants in China.
Participants responded to scenarios using Yes/No options for choices and Likert scales for moral acceptance.
The study evaluated preferences for four distinct algorithmic strategies: Utilitarianism, Rawlsianism, Egoism, and a Hybrid approach.

Main Results:

A significant difference was observed between preferences for AV design and purchase decisions.
Over 50% of participants were reluctant to purchase AVs with an "egoism" algorithm (prioritizing owner safety).
Rejection rates for "egoism" and "utilitarianism" (requiring self-sacrifice) were notably similar.

Conclusions:

A hybrid ethical algorithm, balancing Utilitarianism and Egoism, received the highest endorsement.
Balancing self-sacrifice and harm minimization is key for developing acceptable AV moral algorithms.
These findings are vital for the ethical and practical advancement of autonomous vehicle technology.