Source: Harvard Journal of Law & Technology

The article explores the emerging field of AI auditing as a key mechanism for regulating artificial intelligence. With AI systems increasingly integrated into critical sectors, ensuring their transparency, accountability, and fairness has become a legal and ethical priority. AI auditing is being developed as a process to assess and validate AI models, ensuring compliance with regulatory standards and ethical guidelines.

One major challenge in AI regulation is the "black box" problem, where AI decision-making is opaque and difficult to interpret. AI audits aim to address this by examining how models function, whether they contain biases, and whether they comply with existing laws. The article highlights the importance of independent audits, as self-regulation by tech companies may not be sufficient to ensure compliance.

The discussion also covers recent policy proposals and legislative efforts that include AI auditing as a necessary component of future AI governance. Some governments and regulatory bodies are considering mandatory AI audits, especially in high-risk applications such as finance, healthcare, and criminal justice.

Overall, AI auditing is positioned as a critical first step toward effective AI regulation, bridging the gap between innovation and accountability. The legal landscape for AI governance is still evolving, but auditing is expected to play a central role in ensuring that AI operates within ethical and legal boundaries.