Statistics is More Like Auto-Formalization
roydanroy · x · 2026-07-16
The author argues that the field of statistics has not historically been organized around 'formalized open problems'. One reason is that the hardest part of many difficult problems isn't the proof itself, but clearly defining the problem in the first place.
Drawing an analogy to AI, he suggests that much of the truly impactful work in statistics is closer to auto-formalization than to theorem proving. In other words, the core challenge often lies in compressing ambiguous reality into a tractable problem representation.
More from AGI Musings
- Claude Code skill uses 10 Markdown rules to make outputs ADHD-friendly — alex_verem · 2026-07-22
- AI Power Demand Exposes US Energy Gap, Urging Shift from Scarcity to Abundance — bradneuberg · 2026-07-22
- ControlAI CEO says an international ban on superintelligence is needed to avert extinction risk — zetalyrae · 2026-07-22
- Gary Marcus says LLMs still cannot really do math on their own — GaryMarcus · 2026-07-22
- Gary Marcus says LLM math skills are like knowing only a car’s engine size — GaryMarcus · 2026-07-22
- AI may make digital work infinitely leveraged while offline life gets more human — illscience · 2026-07-22