AI Governance and Accountability: An Analysis of Anthropic's Claude

TL;DR

This paper analyzes Anthropic's Claude within AI governance frameworks, emphasizing transparency, benchmarking, and ethical considerations to promote responsible AI development and deployment.

Contribution

It provides a detailed assessment of Claude using NIST and EU AI frameworks, proposing strategies for improved governance and accountability.

Findings

Identification of potential risks and threats to AI safety

Recommendations for transparency and benchmarking practices

Discussion on social and ethical implications of AI governance

Abstract

As AI systems become increasingly prevalent and impactful, the need for effective AI governance and accountability measures is paramount. This paper examines the AI governance landscape, focusing on Anthropic's Claude, a foundational AI model. We analyze Claude through the lens of the NIST AI Risk Management Framework and the EU AI Act, identifying potential threats and proposing mitigation strategies. The paper highlights the importance of transparency, rigorous benchmarking, and comprehensive data handling processes in ensuring the responsible development and deployment of AI systems. We conclude by discussing the social impact of AI governance and the ethical considerations surrounding AI accountability.