aiqbench analysis
The article addresses the critical governance challenge of who holds the authority to validate AI safety, arguing that current self-regulatory models are insufficient without independent oversight and enforceable penalties. It highlights the tension between corporate self-policing and the need for a robust public policy regime to ensure AI systems remain aligned with deployment goals beyond mere demonstrations.
The AI control gap: Who gets to say ‘It’s safe’?
We see a control gap between what artificial intelligence can do and what the evidence supports trusting it to do. A great demo doesn’t prove that a system will stay within the limits of an intended deployment’s goals. The question is: Who gets to decide when the evidence is sufficient to declare AI is safe? […] The post The AI control gap: Who gets to say ‘It’s safe’? appeared first on SiliconANGLE.
We see a control gap between what artificial intelligence can do and what the evidence supports trusting it to do. A great demo doesn’t prove that a system will stay within the limits of an intended deployment’s goals. The question is: Who gets to decide when the evidence is sufficient to declare AI is safe? We believe that decision needs independent oversight and enforceable authority. Today, we draw on extensive conversations with Appian Corp. Chief Executive Matt Calkins, who helps us connect public policy to the agents acting inside a business, and the opportunity to make those systems dependable enough to receive more trusted authority. In this week’s episode, we explore the AI control gap and the starting point for addressing AI safety, namely alignment. We question prevailing narratives around China and propose a public policy regime that has more teeth than what has been put forth thus far. And we bring in customer data from our partner Qualitate to capture the buyer sentiment on these issues. Let’s start with: Who can actually say no? This tongue-in-cheek illustration below comes from Amit Govrin. He wrote a post last week called “Grading Other’s Homework.” Amit conceived a gathering at the White…
Excerpt shown under the publisher's RSS terms · 200 words · full text and figures are on the publisher's site
Related coverage
Untrusted advice for AI control: Short, strong advice significantly uplifts weak LLMs
LessWrong · Jul 27, 2026
Problems of Proliferation
LessWrong · Sep 29, 2026

Presentation: APIs for Agents: Rethinking API Programs in the MCP Era
InfoQ · Sep 23, 2026

I Did This Without Your Knowledge
LessWrong · Oct 17, 2026