Bridging Worlds: AI Governance & Software Engineering | Responsible AI Innovation
Everything AI & LawShow Notes
As AI rapidly evolves, how can we ensure transparency, accountability, and ethical innovation? In this episode of the Everything AI & Law Podcast, I (Tolulope Awoyomi) sit down with Lusine Petrosyan and Trung Lam, two AI experts from the National Fair Housing Alliance, to discuss the intersection of AI governance and engineering.
Key Discussion Topics: Textrify: AI vs. Human Content Detection – A tool bridging policy & engineering AI Detection & Accountability – The challenges of distinguishing AI-generated content The ‘Cat and Mouse’ Race – AI developers vs. detection systems Balancing AI Innovation & Regulation – Finding the right policy approach De-biasing AI Models – Technical & policy-driven solutions Interdisciplinary Collaboration in AI – Why policy & engineering must work together AI Ethics & Public Perception – Addressing fears & misconceptions The Future of AI & Policy – What’s next in AI governance?
Lusine, an AI governance researcher, and Trung, an AI engineer, share their collaborative journey developing Textrify, a tool designed to distinguish between AI-generated and human content. Our discussion highlights the importance of cross-disciplinary collaboration in ensuring ethical and responsible AI development. Whether you’re an AI enthusiast, policymaker, software engineer, or just curious about the future of AI accountability, this episode is packed with valuable insights!
Chapter Timestamps: 00:00 Snippet 01:21 Textrify: Bridging Policy & Engineering in AI 06:21 The Role of AI Detection Tools in Accountability 10:56 The 'Cat and Mouse' Race in AI Detection 13:51 Balancing Innovation & Regulation 21:36 De-biasing AI: Technical & Policy Approaches 27:31 Importance of Interdisciplinary Collaboration in AI 32:36 Ethics, Public Fear & AI’s Future 41:36 Exciting Prospects in AI & Policy 46:56 Closing Thoughts & Key Takeaways
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Connect with Us: Tolulope Awoyomi Lusine Petrosyan Trung Lam
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