Toward Implementing the Agent-Deed-Consequence Model of Moral Judgment in Autonomous Vehicles

Abstract

Autonomous vehicles (AVs) and accidents they are involved in attest to the urgent need to consider the ethics of AI. The question dominating the discussion has been whether we want AVs to behave in a 'selfish' or utilitarian manner. Rather than considering modeling self-driving cars on a single moral system like utilitarianism, one possible way to approach programming for AI would be to reflect recent work in neuroethics. The Agent-Deed-Consequence (ADC) model [1-4] provides a promising account while also lending itself well to implementation in AI. The ADC model explains moral judgments by breaking them down into positive or negative intuitive evaluations of the Agent, Deed, and Consequence in any given situation. These intuitive evaluations combine to produce a judgment of moral acceptability. This explains the considerable flexibility and stability of human moral judgment that has yet to be replicated in AI. This paper examines the advantages and disadvantages of implementing the ADC model and how the model could inform future work on ethics of AI in general.