AI, a Machine to Govern? Development, Operations and Trade-offs
summary
Examines how prescriptive systems—laws, procedures, and software—shape governance and what stance to take toward them. Argues from a DevOps perspective that DevOps’ core intuition (closing the loop between development and operations) can guide building systems that encode common good values into code. Discusses trade-offs and responsibilities when designing prescriptive technical and organizational systems.
AI-written summary · about
chapters (8)
- 0:00Introduction
- 1:05System limits
- 7:03Global rule system
- 11:58DevOps and separation
- 16:51Software as governance tool
- 22:53Law to code
- 28:51Trade-offs and energy
- 32:42Q&A
related talks
28mFrom the Trenches: Solving AI Governance Challenges
08mWhy AI Governance Matters More Than Ever
33mAI in the Security Stack
46mMaking AI Adoption Work: A Practical Structure for Modern Software Development
27m📙 AI as an Accountable Entity: Governing Risk When Machines Make Decisions ⚖️
37mAI Under Control: accelerating safely
15mThe AI Shift: Rethinking the Developer’s Role in a Machine-Driven World
30mAgentic AI in Action: From Framework to Deployment
