Show notes
What does trustworthy AI look like when its behavior isn't deterministic? This conversation connects practical software delivery decisions with their wider impact on users and society.
Topics include:
- Bridging AI's trust gap through evaluations, guardrails, monitoring and clear routes to human intervention.
- Planning for mistakes with reversible actions and compensating transactions.
- Why faster code generation can shift bottlenecks to problem framing, testing, release and maintenance.
- Managing token costs and communication overhead in agentic workflows.
- Protecting user experience through research and testing rather than treating more features as more value.
- Digital sovereignty, AI regulation and the case for collaboration and federated infrastructure.
- Digital inclusion across connectivity, age and socioeconomic circumstances.
Jeff's closing takeaway: engineers should take more interest in the humanities to better understand the people and societies their systems affect.
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