Social scientist's four questions expose the blind spot in agentic AI development
RexDouglass · x · 2026-10-23
RexDouglass presses on agentic AI from a social science angle with four questions most engineers skip:
- How do you know what to ask it?
- How do you know it told you the truth?
- When it outpaces your expertise, time, and attention, how does it guess what you would have wanted?
- How does it guess what you wish you had asked, or would ask next?
His core point: most of CS/engineering treats agent development as a closed blackbox that magically gets better, yet principal-agent research shows that even more expertise doesn't make principal-agent problems easier — this is social science's home turf.
Related event: 6,000 Meaningless Unit Tests Spark Reflection on AI Alignment(3 posts)→
More from AGI Musings
- Grady Booch revives Weinberg's 1971 quip: software so buggy one woodpecker could destroy civilization — Grady_Booch · 2026-10-23
- Why Netflix keeps losing to YouTube: UGC platforms professionalize easier than pro platforms go casual — ZeroStateReflex · 2026-10-23
- AI killed the coding moat: indie devs now compete on demand and distribution — sven_ai · 2026-10-23
- DynaVelo, a neural ODE model of single-cell dynamics, published in Nature Biotechnology — anshulkundaje · 2026-10-23
- Beff Jezos: Only frontier labs out-accelerating open source can secure systems — beffjezos · 2026-10-23
- 'I don't want to live in that world': a Redditor on why AGI utopia feels meaningless — peace_venerable · 2026-10-23