Judith Jarvis Thomson; Killing, Letting Die, and The Trolley Problem, The Monist, Volume 59, Issue 2, 1 April 1976, Pages 204–217, https://doi.org/10.5840/monis.

Previous edition, 1st, published in 1971.

The recent progress in the development of autonomous cars has seen ethical questions come to the forefront. In particular, life and death decisions regarding the behavior of self-driving cars in trolley dilemma situations are attracting widespread interest in the recent debate. In this essay we want to ask whether we should implement a mandatory ethics setting for the whole of society or, whether every driver should have the choice to select his own personal ethics setting. While the consensus view seems (...) to be that people would not be willing to use an automated car that might sacrifice themselves in a dilemma situation, we will defend the somewhat contra-intuitive claim that this would be nevertheless in their best interest. The reason is, simply put, that a PES regime would most likely result in a prisoner’s dilemma. (shrink)

Self-driving cars hold out the promise of being safer than manually driven cars. Yet they cannot be a 100 % safe. Collisions are sometimes unavoidable. So self-driving cars need to be programmed for how they should respond to scenarios where collisions are highly likely or unavoidable. The accident-scenarios self-driving cars might face have recently been likened to the key examples and dilemmas associated with the trolley problem. In this article, we critically examine this tempting analogy. We identify three important ways (...) in which the ethics of accident-algorithms for self-driving cars and the philosophy of the trolley problem differ from each other. These concern: the basic decision-making situation faced by those who decide how self-driving cars should be programmed to deal with accidents; moral and legal responsibility; and decision-making in the face of risks and uncertainty. In discussing these three areas of disanalogy, we isolate and identify a number of basic issues and complexities that arise within the ethics of the programming of self-driving cars. (shrink)

How should autonomous vehicles be programmed to behave in the event of an unavoidable accident in which the only choice open is one between causing different damages or losses to different objects or persons? This paper addresses this ethical question starting from the normative principles elaborated in the law to regulate difficult choices in other emergency scenarios. In particular, the paper offers a rational reconstruction of some major principles and norms embedded in the Anglo-American jurisprudence and case law on the (...) “doctrine of necessity”; and assesses which, if any, of these principles and norms can be utilized to find reasonable guidelines for solving the ethical issue of the regulation of the programming of autonomous vehicles in emergency situations. The paper covers the following topics: the distinction between “justification” and “excuse”, the legal prohibition of intentional killing outside self-defence, the incommensurability of goods, and the legal constrains to the use of lethal force set by normative positions: obligations, responsibility, rights, and authority. For each of these principles and constrains the possible application to the programming of autonomous vehicles is discussed. Based on the analysis, some practical suggestions are offered. (shrink)

Autonomous vehicles must be programmed with procedures for dealing with trolley-style dilemmas where actions result in harm to either pedestrians or passengers. This paper outlines a Rawlsian algorithm as an alternative to the Utilitarian solution. The algorithm will gather the vehicle’s estimation of probability of survival for each person in each action, then calculate which action a self-interested person would agree to if he or she were in an original bargaining position of fairness. I will employ Rawls’ assumption that the (...) Maximin procedure is what self-interested agents would use from an original position, and then show how the Maximin procedure can be operationalized to produce unique outputs over probabilities of survival. (shrink)