Advancing AI Audits for Enhanced AI Governance

Arisa Ema, Ryo Sato, Tomoharu Hase, Masafumi Nakano, Shinji Kamimura +1 more
11/26/2023
cs.CYcs.AIecon.GN

No confident code implementation found for this paper.

Abstract

As artificial intelligence (AI) is integrated into various services and systems in society, many companies and organizations have proposed AI principles, policies, and made the related commitments. Conversely, some have proposed the need for independent audits, arguing that the voluntary principles adopted by the developers and providers of AI services and systems insufficiently address risk. This policy recommendation summarizes the issues related to the auditing of AI services and systems and presents three recommendations for promoting AI auditing that contribute to sound AI governance. Recommendation1.Development of institutional design for AI audits. Recommendation2.Training human resources for AI audits. Recommendation3. Updating AI audits in accordance with technological progress. In this policy recommendation, AI is assumed to be that which recognizes and predicts data with the last chapter outlining how generative AI should be audited.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{ema2023advancing,
  title  = {Advancing AI Audits for Enhanced AI Governance},
  author = {Arisa Ema and Ryo Sato and Tomoharu Hase and Masafumi Nakano and Shinji Kamimura and Hiromu Kitamura},
  year   = {2023},
  eprint = {2312.00044},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.00044v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2312.00044.svg)](https://codeofpaper.com/paper/2312.00044)

Discussion