Local Differences, Global Lessons: Insights from Organisation Policies for International Legislation

• URL: http://arxiv.org/abs/2503.05737v1
• Date: Wed, 19 Feb 2025 15:59:09 GMT
• Title: Local Differences, Global Lessons: Insights from Organisation Policies for International Legislation
• Authors: Lucie-Aimée Kaffee, Pepa Atanasova, Anna Rogers,
• Abstract summary: This paper examines AI policies in two domains, news organisations and universities, to understand how bottom-up governance approaches shape AI usage and oversight.<n>We identify key areas of convergence and divergence in how organisations address risks such as bias, privacy, misinformation, and accountability.<n>We argue that lessons from domain-specific AI policies can contribute to more adaptive and effective AI governance at the global level.
• Score: 22.476305606415995
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid adoption of AI across diverse domains has led to the development of organisational guidelines that vary significantly, even within the same sector. This paper examines AI policies in two domains, news organisations and universities, to understand how bottom-up governance approaches shape AI usage and oversight. By analysing these policies, we identify key areas of convergence and divergence in how organisations address risks such as bias, privacy, misinformation, and accountability. We then explore the implications of these findings for international AI legislation, particularly the EU AI Act, highlighting gaps where practical policy insights could inform regulatory refinements. Our analysis reveals that organisational policies often address issues such as AI literacy, disclosure practices, and environmental impact, areas that are underdeveloped in existing international frameworks. We argue that lessons from domain-specific AI policies can contribute to more adaptive and effective AI governance at the global level. This study provides actionable recommendations for policymakers seeking to bridge the gap between local AI practices and international regulations.

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