Darby Vickers

To implement an Aristotelian virtue ethics framework to live well with artificial intelligence (as described in Smith & Vickers, 2024), we need teachers who can serve as mentors and role models for the next generation. Finding mentors who can teach both technical expertise and model ethical deployment of that expertise is challenging, and Aristotle provides few hints on how to uncover such mentors. The account of expertise in Plato’s Gorgias seems to align with Aristotle’s vision and provides additional detail. The upshot of the conversation between Socrates and his interlocutors is that an expert should have three capacities: (1) to consistently produce excellent products of their expertise, (2) to replicate their skillset in the next generation, and (3) to use that expertise ethically. A doctor serves as a paradigm case of an expert in Gorgias—while a doctor has the technical ability to both heal and poison, the doctor also has good judgment that will prevent them from using their powers for harm. In Plato’s day, expertise was transmitted through apprentice learning, and so a doctor would also train subsequent generations of doctors. In Gorgias, Plato establishes these criteria for a trustworthy expert who can pass on dangerous skills responsibly. While the dangerous skill in Plato’s day was oratory, we can apply the same criteria to another dangerous form of expertise: artificial intelligence. By corollary, expert engineers should possess the technical skills, understand how to use those technical skills ethically (and actually use them ethically), and be able to replicate both of these skill sets in the next generation of engineers. We can use this account of expertise to develop a clearer picture of the ideal faculty we would hire to teach in all disciplines, but particularly technical disciplines, with the capacity to shape artificial intelligence for good or ill. Plato’s criteria provide us with the criteria required to pick out mentors for a robust virtue ethics-based training of the designers (and even the users) of technology: (1) technical ability, (2) teaching ability, and (3) ethical practices (at least in the scope of their technical domain).

Artificial intelligence technologies have become a ubiquitous part of human life. This prompts us to ask, ‘how should we live well with artificial intelligence?’ Currently, the most prominent candidate answers to this question are principlist. According to these approaches, if you teach people some finite set of principles or convince them to adopt the right rules, people will be able to live and act well with artificial intelligence, even in an evolving and opaque moral world. We find the dominant principlist approaches to be ill-suited to providing forward-looking moral guidance regarding living well with artificial intelligence. We analyze some of the proposed principles to show that they oscillate between being too vague and too specific. We also argue that such rules are unlikely to be flexible enough to adapt to rapidly changing circumstances. By contrast, we argue for an Aristotelian virtue ethics approach to artificial intelligence ethics. Aristotelian virtue ethics provides a concrete and actionable guidance that is also flexible; thus, it is uniquely well placed to deal with the forward-looking and rapidly changing landscape of life with artificial intelligence. However, virtue ethics is agent-based rather than action-based. Using virtue ethics as a basis for living well with artificial intelligence requires ensuring that at least some virtuous agents also possess the relevant scientific and technical expertise. Since virtue ethics does not prescribe a set of rules, it requires exemplars who can serve as a model for those learning to be virtuous. Cultivating virtue is challenging, especially in the absence of moral sages. Despite this difficulty, we think the best option is to attempt what virtue ethics requires, even though no system of training can guarantee the production of virtuous agents. We end with two alternative visions – one from each of the two authors – about the practicality of such an approach.

As artificial intelligence becomes ubiquitous, it will be increasingly involved in novel, morally significant situations. Thus, understanding what it means for a machine to be morally responsible is important for machine ethics. Any method for ascribing moral responsibility to AI must be intelligible and intuitive to the humans who interact with it. We argue that the appropriate approach is to determine how AIs might fare on a standard account of human moral responsibility: a Strawsonian account. We make no claim that our Strawsonian approach is either the only one worthy of consideration or the obviously correct approach, but we think it is preferable to trying to marry fundamentally different ideas of moral responsibility into a single cohesive account. Under a Strawsonian framework, people are morally responsible when they are appropriately subject to a particular set of attitudes—reactive attitudes—and determine under what conditions it might be appropriate to subject machines to this same set of attitudes. Although the Strawsonian account traditionally applies to individual humans, it is plausible that entities that are not individual humans but possess these attitudes are candidates for moral responsibility under a Strawsonian framework. We conclude that weak AI is never morally responsible, while a strong AI with the right emotional capacities may be morally responsible.