Trump Scraps Planned AI Executive Order Over Competitiveness Fears

A small but influential group of AI researchers and policymakers gathered last fall in New York to discuss handing the future over to machines they view as humanity's moral betters. The event focused on creating what organizers called a "Worthy Successor," an artificial intelligence advanced enough to replace people entirely. Attendees included representatives from Anthropic, Google DeepMind, and xAI, along with voices shaping federal AI policy.

One speaker, former congressman Brad Carson, argued for keeping AI as a tool under human control to promote human flourishing. Organizers pushed back, noting that most in the room rejected that approach. They see artificial systems as the next step in evolution and consider efforts to align AI with human values as misguided or even immoral. The view remains controversial enough that participants asked for anonymity outside keynote remarks, yet the ideas are gaining traction in labs and government circles.

Corporate America is showing signs of second thoughts on the same technology. Microsoft recently dropped most of its licenses for one leading AI coding tool after costs mounted. Uber's chief operating officer described AI expenses as increasingly difficult to defend. One consultant reported a client burning through half a billion dollars in a single month when employees used the tools without limits. Layoffs tied to automation are occurring, though some executives admit the cuts may simply be the easiest way to offset new bills.

Employees are resisting the push inside companies. Many default to feeding routine tasks into the systems rather than high-value work, driving up token usage without clear productivity gains. Observers describe this as a correction away from overuse, with AI proving effective mainly in narrow coding tasks so far. Broader claims about transforming entire enterprises remain unproven for most organizations.

Philosophers examining the technology stress that human awareness starts with sensory experience and self-reflection, capacities that develop naturally in children and allow people to evaluate their own thoughts and surroundings. Machines operate on different principles and lack this internal presence, even as they process data at high speed. This distinction undercuts predictions of seamless replacement.

The gap between ambitious visions at invite-only symposia and practical results on balance sheets suggests the drive to accelerate AI may be running ahead of both technical limits and public appetite. Average workers and families bear the costs when experiments scale without clear returns, while a narrow set of technologists debate whether their creations should inherit the world.