Hannah Hilligoss’s scientific contributions

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.

THIS IS THE RUSSIAN TRANSLATION OF ORIGINAL REPORT This report, Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI, is part of the Berkman Klein Center for Internet & Society research publication series. The report and its authors have significantly benefitted from more than two years of research, capacity building, and advocacy executed by the Berkman Klein Center as co-leader of the Ethics and Governance of Artificial Intelligence Initiative in partnership with the MIT Media Lab. Through the Initiative, the Center has worked on pressing issues raised by the development and deployment of AI-based systems – including groundbreaking research on automation’s impact on the online media landscape; fostering the growth of inclusive AI research and expertise in academic centers across the globe; and advocating for increased transparency surrounding the use of algorithms in criminal justice decision-making. Notably, the Center engages both private-sector firms and public policymakers in troubleshooting related legal, social, and technical challenges, and has consulted on the development of AI governance frameworks with national governments and intergovernmental bodies, such as the UN High-Level Committee on Programmes and the OECD’s Expert Group on AI. Principled Artificial Intelligence has been influenced by these collaborative, multistakeholder efforts, and hopes to contribute to their continued success.