Jev's Paradox: The Hidden Cost of Cheap AI Decisions
Sophos, Tuesday, September 29th, 2026
Sophos examines how cheap classifier-style AI decisions could multiply total errors if accuracy and calibration fall short.
Using a SOC alert-triage example, Sophos examines Jev, a TypeSafe.ai model that returns probabilities over a fixed set of permitted answers rather than generating text, pitched as faster and cheaper than general LLMs.
Invoking Jevons paradox, the author argues that if automated decisions become cheap enough to run everywhere, any error rate above the current baseline will produce more total mistakes.
The post separates three properties often blurred: always returning a valid answer, choosing correctly and knowing when an answer is unreliable.