Institutionalising Ethics in AI through Broader Impact Requirements

TL;DR

This paper analyzes the implementation of broader impact statements in AI research at NeurIPS, exploring its challenges, benefits, and implications for responsible AI governance and community engagement.

Contribution

It provides a detailed analysis of the NeurIPS impact requirement, offering insights into effective governance practices and community responsibilities in AI research.

Findings

Identified challenges include lack of best practices and transparency.

Potential benefits include improved impact anticipation and norm strengthening.

Recommendations for transparency, guidance, and public engagement.

Abstract

Turning principles into practice is one of the most pressing challenges of artificial intelligence (AI) governance. In this article, we reflect on a novel governance initiative by one of the world's largest AI conferences. In 2020, the Conference on Neural Information Processing Systems (NeurIPS) introduced a requirement for submitting authors to include a statement on the broader societal impacts of their research. Drawing insights from similar governance initiatives, including institutional review boards (IRBs) and impact requirements for funding applications, we investigate the risks, challenges and potential benefits of such an initiative. Among the challenges, we list a lack of recognised best practice and procedural transparency, researcher opportunity costs, institutional and social pressures, cognitive biases, and the inherently difficult nature of the task. The potential benefits, on the other hand, include improved anticipation and identification of impacts, better communication with policy and governance experts, and a general strengthening of the norms around responsible research. To maximise the chance of success, we recommend measures to increase transparency, improve guidance, create incentives to engage earnestly with the process, and facilitate public deliberation on the requirement's merits and future. Perhaps the most important contribution from this analysis are the insights we can gain regarding effective community-based governance and the role and responsibility of the AI research community more broadly.