Today we delve into the intricate world of AI assessment, review and audit methodologies, focusing on international frameworks and regulatory approaches. The discussion features experts from the City Bar Presidential Task Force on Artificial Intelligence and Digital Technologies, including Azish Filabi (American College McGuire Center for Ethics and Financial Services), Rim Belaoud (Forensic Risk Alliance), Nikhil Aggarwal (Deloitte Anti Money-Laundering), Lenka Molins (Oxford Internet Institute) and Jerome Walker (Task Force Co-Chair). They explore the definitions, methodologies, and challenges of AI audits across different jurisdictions such as the US, EU, Canada, and the UK, providing perspectives on issues related to methodologies, bias, transparency, and accountability. The episode also covers practical approaches for organizations to review AI models and highlights the importance of robust AI governance in various sectors, including financial services, AML, CFT, fraud, and export controls.



00:00 Introduction to the Podcast
00:50 Overview of AI Assessments, Reviews, and Audits
02:20 Key Definitions and Concepts in AI
05:44 Panelist Introductions
08:39 Discussion on Responsible and Trustworthy AI
18:33 Training AI Models and Explainability
22:33 Challenges in AI Assessments and Reviews
27:09 Global Perspectives on AI Audits
39:10 Practical Approaches for AI Model Reviews
53:57 Key Skills for AI Model Audits
59:27 Introduction and Areas of Practice
01:01:31 AI in Anti-Money Laundering and Counter-Terrorist Financing
01:07:36 AI Models in Fraud Detection
01:14:41 Export Control on AI Models
01:21:35 International AI Audit Methodologies
01:27:42 Challenges in AI Audits
01:42:10 Accountability in AI Audits
01:46:13 Conclusion and Final Thoughts