Frontier AI should be deployed iteratively because harm thresholds are hard to spot ahead of time
_aidan_clark_ · x · 2026-07-21
The author argues that frontier model development should stay cautious because safety cannot be cleanly judged in hindsight. The core idea is iterative deployment: models may eventually create significant harm, but the exact threshold is hard to identify in advance, so teams should move carefully and keep updating their assumptions.
The post is a reply reinforcing that taking a retrospective “you were dumb to worry” stance misunderstands the uncertainty frontier labs are operating under.
Related event: GPT-OSS Open-Source Debate: Risk Assessment vs. Regulation(22 posts)→
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