Natural Law and its Implications for AI Governance

Abstract

With the recent emergences of AI technologies, our societies are facing regulatory challenges in terms of their design, manufacture, sale and use. In addition to the existing norms, many new ' AI laws' will be needed for early stage AI governance. However, when it comes to AI, there is a significant gap between hard laws and soft laws. Although we have witnessed the development of soft law from both public institutions and organisations like the EU and the IEEE in recent years, hard law has been less forthcoming. Answering the question of why this gap exists and whether or not 'natural law' can narrow is the chief purpose of this paper. To do so we will draw on two supplemental principles from the natural law tradition.

Coarse ethics: how to ethically assess explainable artificial intelligence

“…Such models include SHapley Additive exPlanations [33,36] or Local Interpretable Model-agnostic Explanation (LIME) [36,40]. This issue applies to human-robot interactions (HRI) too, as it has been consistently queried whether robots could share ethics or at least display ethical similarities with human beings since the annual IEEE RO-MAN series in 1992 [13] and whether their ethics could be easily comprehensible in the manner of Asimov's Three Laws of Robotics [52]. In addition, the study of the Law of Algorithms would also incorporate issues contemplating ethically acceptable standards to balance AI accuracy against interpretability [5].…”