Managing Risk in AI Products: How to Promote Responsible Innovation
summary
Governance embeds AI review into product planning, uses procurement as a first filter, and routes high‑risk cases to a weekly four‑person fast‑track committee; a peer Slack channel and an internal bug‑bounty style incentive surfaces shadow use. Real examples include vetting Figma’s new AI feature and blocking models that send data to China. The approach prioritizes one‑sprint access for engineers while keeping an approved tool list and shadow AI amnesty window.
AI-written summary · about
chapters (7)
- 0:00Introduction
- 2:41Defining AI governance
- 7:13First major risks in AI
- 16:23Navigating org politics
- 25:15Detecting shadow AI
- 28:50Flexible AI governance
- 30:16Q&A
related talks
37mRoadmap to Responsible AI
50mSecurity as Part of Responsible AI: At Home or At Odds?
35mRisks and Mitigations for a Safe and Responsible AI
34mEthical framework for AI : Creating AI powered products that empower people
35mResponsible AI: Ethics in Software Development
27mWriting the Playbook for Fair & Ethical Artificial Intelligence & Machine Learning
14mBuilding Transparent and Ethical Generative AI Models in High-Stakes Industries
44mAI, Corporate Responsibility & Democratic Legitimacy