Anthropic has issued another warning about artificial intelligence. But this time, the concern is not job displacement or productivity.

It is the possibility that AI could soon begin improving itself.

In this episode of Leading Change in the Wild, I break down Anthropic’s latest report on recursive self-improvement and what it means if AI reaches a point where it can build, test, and improve future versions of itself with minimal human involvement.

But beyond the technology itself, this report raises some deeper questions.

Who should be leading these conversations? And what happens when the companies warning us about the risks are also the companies building the technology?

Here’s what I unpack:

• What recursive self-improvement actually means
• Why Anthropic believes we may be approaching a major AI inflection point
• The challenge of keeping humans in control of increasingly capable systems
• The “prisoner’s dilemma” at the center of AI development
• Whether AI companies can simultaneously be the warning system and the builder
• How regulation, competition, and incentives collide in the AI race
• The connection between recursive AI, model collapse, and the dead internet theory

The takeaway is not just about technology.

It is about incentives, accountability, and who gets to shape the future of AI.

Because if the people raising the alarm are also the people benefiting from the outcome, we need to ask harder questions about how these decisions are being made.

👇 Let’s discuss:

• Should AI companies be leading conversations about AI regulation and ethics?
• Are we approaching a point where AI can meaningfully improve itself?
• Is a global pause realistic, or are we already too far down the path?

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