I’ve posted an excerpt from Sigma Game from my other forthcoming book, HARDCODED. I didn’t intend to write it, but it came about as a direct result of writing PROBABILITY ZERO, then discovering how the various AI systems reacted so bizarrely, and differently, to both the central argument of the book as well as its supporting evidence.
And as with PZ, I inadvertently discovered something of significance when substantiating my original case with the assistance of my tireless scientific colleague, Claude Athos. Namely, many scientific fields are on a path toward having a literature completely filled with non-reproducible garbage, and three of them are already there.
How long does it take for a scientific field to fill with garbage? The question sounds polemical, but it has a precise mathematical answer. Given a field’s publication rate, its replication rate, its correction mechanisms, and—critically—its citation dynamics, we can model the accumulation of unreliable findings over time. The result is not encouraging.
Read the rest of the excerpt at Sigma Game if it’s of interest to you. I think this book is going to be of broader interest, and perhaps even greater long-term significance, than the book I’d intended to write. Which, nevertheless, did play a contributing role.
- Field: Evolutionary Biology
- Starting unreliability (1975): ~20%
- Citation amplification (α): ~12-15 (adaptive “just-so stories” are highly citable)
- Correction rate (C): ~0.02-0.03 (low; most claims are not directly testable)
- Years in decay: ~50
- Current estimated garbage rate: 95-100%
The field that prompted this book is a special case. The decay function analysis above treats unreliability as accumulating gradually through citation dynamics. But evolutionary biology faces a more fundamental problem: the core mechanism is mathematically impossible.