Keynote Panel: Gen AI: Opportunites & risks
summary
Panelists compare real deployments and real gaps they see today: a hospital pharmacy using smarter inventory management and two in‑use AI algorithms to predict demand and recommend personalized dosing for blood thinners, SAP promoting a conversational product called jeel, and Microsoft offering Azure AI Foundry with configurable filters and metrics. Risks named include prompt injection attacks, copyright litigation over training data, biased training sets, and the need for human‑in‑the‑loop validation and developer training.
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chapters (11)
- 0:00Keynote panel intro
- 1:43AI in healthcare
- 9:59AI in supply chain
- 13:13AI in finance
- 16:04Balancing innovation and risks
- 21:02AI governance
- 22:50Healthcare data bias
- 26:00AI’s future beyond hype
- 27:26Lessons from tech revolutions
- 29:13Ethical boundaries for AI
- 30:16Closing remarks & Q&A
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