GoKawiilOpenAI's Astra Model Reportedly Uses Opaque Reasoning, Worrying Safety Researchers
According to The Information, OpenAI's upcoming Astra model employs a technique called recurrent depth or opaque recurrence, letting it think outside the step-by-step chain-of-thought format used by most reasoning models. Reports indicate the technique's use in Astra is currently limited, but its introduction has drawn sharp criticism from AI safety researchers who worry about losing insight into model reasoning.
GoKawiil's interpretation of the reporting above, not reported fact.
Chain-of-thought transparency has been one of the few tools researchers rely on to catch dangerous or deceptive model behavior before it causes harm. If opaque recurrence scales up, models could eventually reason almost entirely in latent space, making their decision-making effectively unreadable and undermining a safety norm labs like OpenAI and Anthropic have tried to uphold.
- OpenAI's Astra reportedly uses 'opaque recurrence,' a non-sequential reasoning method that's harder to monitor.
- Safety experts like Buck Shlegeris and Ryan Greenblatt warn scaling this technique could eliminate visibility into AI reasoning.
- Zvi Mowshowitz suggests regulation may be needed to stop labs from racing toward less transparent AI architectures.
Nick Bostrom "Superintelligence" (book) — If the debate over unmonitorable chains of thought has you curious, Bostrom's Superintelligence is the classic deep dive into AI alignment and control problems that safety researchers keep referencing. It's a great way to understand why experts get rattled when a model's reasoning becomes opaque.
See Nick Bostrom "Superintelligence" (book) on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: it.slashdot.org, 2026-09-03
Published there as: “OpenAI's New Reasoning Technique Alarms AI Safety Experts”
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