Roadmap to Responsible AI
summary
A practical roadmap that claims an integrated data and AI governance framework with measurable KPIs and a maturity assessment and a start-small-scale-fast rollout. Examples include a European automotive AI ethics policy, an Asian logistics rollout of decision forums and upskilling, and building agents to automate profiling and rule generation that output code. Discusses specific risks: Shadow AI (ChatGPT leaks, Samsung incident) and regulatory touchpoints like the EU AI Act and secure Co‑Pilot deployments.
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chapters (14)
- 0:00Responsible AI governance intro
- 1:12Why AI governance now
- 3:20AI in business operations
- 5:54Risks of ungoverned AI
- 6:34Core AI governance principles
- 11:33Data and AI governance framework
- 15:56Framework practical apps
- 22:45Building AI literacy programs
- 25:16AI for governance enhancement
- 26:19Key takeaways and call to action
- 27:23Q&A: Discriminatory AI and legal risks
- 29:09Q&A: Shadow AI and data security
- 31:14Q&A: Framework adoption and enforcement
- 33:42Q&A: Use case governance in large orgs
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