Computerweekly iconComputerweeklySep 18, 2026 ~6 min source read

Pacing the AI Frontier: Why the immediate risk is artificial unintelligence

A recent call to ‘pace the frontier’ shifts the debate from runaway superintelligence to the practical harms caused by powerful but unreliable systems, and proposes concrete steps labs and enterprises can take now.

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Useful takeaways from this story.

Anthropic proposes concrete measures including third-party, employee-level evaluation access to verify safety policies during development and production.

Closing the gap between capability and trustworthiness — not slowing capability per se — is the operational challenge for the coming decade.

The useful part

Pacing the AI Frontier: the risk of artificial unintelligence | Computer Weekly Home IT risk management Sandwish. stock.adobe.com By Peter van der Putten Published: 18 Sep 2026 "We must pace the frontier," Anthropic CEO Dario Amodei argued in a blog post published last weekend that quickly went viral. He called for "pacing the rate of capabilities advancement so that risk prevention has time to keep up" and Elon Musk, Sam Altman and Satya Nadella swiftly announced their support at least of the general idea.

How it works

  • Many of the same companies now warning about frontier risks have spent years emphasising the transformative potential of AGI, sometimes alongside predictions of existential consequences.
  • While it is fair to question the timing of these warnings, dismissing them as mere positioning ahead of IPOs, fundraising rounds or data-center expansion plans would be too easy.
  • Yet the same systems still hallucinate facts, invent sources, overlook obvious context, fail unpredictably and can be manipulated in surprisingly simple ways.
  • Enterprises build applications, workflows and decision processes on top of foundation models, creating risks and responsibilities that extend far beyond the model provider itself.
  • Is Europe is behind in AI, as critics frequently argue, or ahead when it comes to developing an agreed regulatory framework?

What to take from it

How to make AI better at defense The agentic AI playing field was heavily tilted toward offense, so researchers began using red team agents to help teach their... Search Data Management HR makes major strides toward improving employee engagement Cloud vs. Amodei lists a range of risks Anthropic has been talking about previously, such as cybersecurity or bioterrorist attacks, as well as more recent developments such as OpenAI agents hacking into HuggingFace, and the accelerating capabilities for AI to build even more intelligent AI systems, such as 'recursive self-improvement'.

Example or evidence

  • As Microsoft CEO Satya Nadella also noted on X, model-level safeguards are only part of the picture.
  • New research shows how security scanners embedded in the software supply chain can be attacked to serve as a foothold for...
  • AI's energy and latency demands are driving infrastructure toward the edge -- closer to users,...
  • A cynical view is that some of the recent incidents were even seen as marketing opportunities.

Details worth keeping

The timing does, however, raise legitimate questions. Concerns about AI systems designing increasingly capable successors are also not new. The intellectual roots of the debate stretch back at least sixty years.

Related coverage

  • Forrester: Anthropic CEO Dario Amodei's essay this past weekend, "We Must Pace the Frontier," argues that the AI industry should slow the pace of frontier model advancement until safety, oversight, and alignment...
  • Latterdaysaintmag: Usually, these articles are not about the extremes surrounding artificial intelligence.
  • Computerweekly: The danger is not a conscious machine, but a dazzling prediction engine that moves faster than we can supervise. The real risk is that we hand over the controls too easily

More context around this story.

The Risks of AI: Is the Sky Really Falling?
Latterdaysaintmag iconLatterdaysaintmagSep 24, 2026

The Risks of AI: Is the Sky Really Falling?

Usually, these articles are not about the extremes surrounding artificial intelligence. I have been more interested in the practical middle ground—how AI can be used thoughtfully to speed up research, sharpen ideas, reduce wasted effort, and help us get more useful work done. Lately, however, the headlines have taken a

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