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That willingness is not reassuring. For example, it is not far-fetched to imagine insurers wanting to get their hands on this type of medical information in order to hike premiums. Data brokers of all kinds will be similarly keen to obtain people’s real-time health-chat records. Altman made a point to say that this theoretical product would not trick people into sharing information.

. Neither Altman nor Huffington had an answer to my most basic question—What would the product actually look like? Would it be a smartwatch app, a chatbot? A Siri-like audio assistant?—but Huffington suggested that Thrive’s AI platform would be “available through every possible mode,” that “it could be through your workplace, like Microsoft Teams or Slack.

This led me to propose a hypothetical scenario in which a company collects this information and stores it inappropriately or uses it against employees. What safeguards might the company apply then? Altman’s rebuttal was philosophical. “Maybe society will decide there’s some version of AI privilege,” he said. “When you talk to a doctor or a lawyer, there’s medical privileges, legal privileges. There’s no current concept of that when you talk to an AI, but maybe there should be.”

So much seems to come down to: How much do you want to believe in a future mediated by intelligent machines that act like humans? And: Do you trust these people?

A fundamental question has loomed over the world of AI since the concept cohered in the 1950s: How do you talk about a technology whose most consequential effects are always just on the horizon, never in the present? Whatever is built today is judged partially on its own merits, but also—perhaps even more important—on what it might presage about what is coming next.

the models “just want to learn”—a quote attributed to the OpenAI co-founder Ilya Sutskever that means, essentially, that if you throw enough money, computing power, and raw data into these networks, the models will become capable of making ever more impressive inferences. True believers argue that this is a path toward creating actual intelligence (many others strongly disagree). In this framework, the AI people become something like evangelists for a technology rooted in faith: Judge us not by what you see, but by what we imagine.

I found it outlandish to invoke America’s expensive, inequitable, and inarguably broken health-care infrastructure when hyping a for-profit product that is so nonexistent that its founders could not tell me whether it would be an app or not.

Thrive AI Health is profoundly emblematic of this AI moment precisely because it is nothing, yet it demands that we entertain it as something profound.

you don’t have to get apocalyptic to see the way that AI’s potential is always muddying people’s ability to evaluate its present. For the past two years, shortcomings in generative-AI products—hallucinations; slow, wonky interfaces; stilted prose; images that showed too many teeth or couldn’t render fingers; chatbots going rogue—have been dismissed by AI companies as kinks that will eventually be worked out

Faith is not a bad thing. We need faith as a powerful motivating force for progress and a way to expand our vision of what is possible. But faith, in the wrong context, is dangerous, especially when it is blind. An industry powered by blind faith seems particularly troubling.

The greatest trick of a faith-based industry is that it effortlessly and constantly moves the goal posts, resisting evaluation and sidestepping criticism. The promise of something glorious, just out of reach, continues to string unwitting people along. All while half-baked visions promise salvation that may never come.