is arranged like a wheel. Each document is represented by a spoke of that wheel, and labeled with the sponsoring actors, date, and place of origin. The one exception is that the OECD and G20 documents are represented together on a single spoke, since the text of the principles in these two documents is identical. 3 The spokes are sorted first alphabetically by the actor type and then by date, from earliest to most recent.
Attempts to impose moral constraints on autonomous, artificial decision-making systems range from “human in the loop” requirements to specialized languages for machine-readable moral rules. Regardless of the approach, though, such proposals all face the challenge that moral standards are not universal. It is tempting to use lawfulness as a proxy for morality; unlike moral rules, laws are usually explicitly defined and recorded – and they are usually at least roughly compatible with local moral norms. However, lawfulness is a highly abstracted and, thus, imperfect substitute for morality, and it should be relied on only with appropriate caution. In this paper, we argue that law-abiding AI systems are a more achievable goal than moral ones. At the same time, we argue that it’s important to understand the multiple layers of abstraction, legal and algorithmic, that underlie even the simplest AI-enabled decisions. The ultimate output of such a system may be far removed from the original intention and may not comport with the moral principles to which it was meant to adhere. Therefore, caution is required lest we develop AI systems that are technically law-abiding but still enable amoral or immoral conduct.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.