Abstract

Artificially intelligent systems are nowadays presented as systems that should, among other things, be explainable and ethical. In parallel, both in the popular culture and within the scientific literature, there is a tendency to anthropomorphize Artificial Intelligence (AI) and reify intelligent systems as persons. From the perspective of machine ethics and ethical AI, this has resulted in the belief that truly autonomous ethical agents (i.e., machines and algorithms) can be defined, and that machines could, by themselves, behave ethically and perform actions that are justified (explainable) from a normative (ethical) standpoint. Under this assumption, and given that utilities and risks are generally seen as quantifiable, many scholars have seen consequentialism (or utilitarianism) and rational choice theory as likely candidates to be implemented in automated ethical decision procedures, for instance to assess and manage risks as well as maximize expected utility. While some see this implementation as unproblematic, there are important limitations to such attempts that need to be made explicit so that we can properly understand what artificial autonomous ethical agents are, and what they are not. From the perspective of explainable AI, there are value-laden technical choices made during the implementation of automated ethical decision procedures that cannot be explained as decisions made by the system. Building on a recent example from the machine ethics literature, we use computer simulations to study whether autonomous ethical agents can be considered as explainable AI systems. Using these simulations, we argue that technical issues with ethical ramifications leave room for reasonable disagreement even when algorithms are based on ethical and rational foundations such as consequentialism and rational choice theory. By doing so, our aim is to illustrate the limitations of automated behavior and ethical AI and, incidentally, to raise awareness on the limits of so-called autonomous ethical agents.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call