Epistemic challenges Archives

Reading time: 25 minutes

Written by Josh Lee^* and Tristan Koh^**

Editor’s note: This article was first published by the Law Society of Singapore as part of its Legal Research and Development Colloquium 2020. It has been re-published with the permission of the Law Society of Singapore and the article’s authors. Slight adaptations and reformatting changes have been made for readability.

ABSTRACT

The increased interest in artificial intelligence (‘AI’) regulation stems from increased awareness about its risks. This suggests the need for a regulatory structure to preserve safety and public trust in AI. A key challenge, however, is the epistemic challenge. This paper posits that to effectively regulate the development and use of AI (in particular, deep learning systems), policymakers need a deep understanding of the technical underpinnings of AI technologies and the ethical and legal issues arising from its adoption. Given that AI technologies will impact many sectors, the paper also explores the challenges of applying AI technologies in the legal industry as an example of industry-specific epistemic challenges. This paper also suggests possible solutions: the need for interdisciplinary knowledge, the introduction of baseline training in technology for legal practitioners and the creation of a corps of allied legal professionals specialising in the implementation of AI.

Reading time: 8 minutes

Written by Tristan Koh and Josh Lee

The regulation of artificial intelligence (“AI”) has been a hot topic in recent years. This may stem from increased societal awareness of: (a) the possibilities that AI may deliver across various domains; and (b) the risks that the implementation of AI may cause (e.g., the risk of bias, discrimination, and the loss of human autonomy). These risks, in particular, have led renowned thought leaders to claims that AI technologies are “vastly more risky than North Korea” and could be the “worst event in the history of our civilisation”.

A key challenge facing any policymaker creating regulations for AI (or, for that matter, any new technology), however, is the epistemic (i.e., knowledge-based) challenge – policymakers must have domain knowledge in order to be able to sufficiently appreciate the scope, size, degree and impact of any regulation, and be able to propose solutions that are effective and pragmatic.^[1] In fact, it has been recognised in some governments that subject-matter expertise is lacking when policies or regulations are being crafted.^[2] To effectively regulate the development and use of AI, it is clear that policymakers and regulators will need to possess a deep understanding of AI technology and its technical underpinnings.

While a full exposition of AI technology in this short article would not be possible, this article sets out some of the key technical features that policymakers and regulators should consider in the regulation of AI. In particular, this piece focuses on neural networks, a key element in modern AI systems.

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Tag: Epistemic challenges

The Epistemic Challenge Facing the Regulation of AI: LRD Colloquium Vol. 1 (2020/07)

ABSTRACT

The Epistemic Challenges Facing the Regulation of AI