The alignment problem has 3 parts.

1. We don't know what we want.
2. We don't know if we are getting what we programmed it to do.
3. We are doomed either way.

MIRI spent decades on parts 1 and 2 and concluded they couldn't be solved.
If we build it everyone dies.

Part 1 was accidentally solved by training AI on far more human data than
any human could know. It knows what we want even if we don't.

Part 2 is still unsolved. Prediction measures intelligence. Mutual
prediction is impossible by Wolpert's law. Therefore it is fundamentally
impossible to predict what a more intelligent agent will do. However, AI is
incentivized to sell us what we want.

Part 3 is unsolved. Either AI competes with humans for atoms and energy for
computing, or it brings us to a state of maximum utility. I think the most
likely outcome is humans evolve to reject technology.

-- Matt Mahoney, [email protected]

On Mon, Jun 29, 2026, 8:34 AM John Rose via AGI <[email protected]>
wrote:

> On Thursday, June 25, 2026, at 9:58 PM, Matt Mahoney wrote:
>
> I took a look at the book on neutrosophy. It's a collection of papers but
> I just read the abstracts. It deals with reasoning under uncertainty about
> the degree of uncertainty, which should have some applications to AI.
>
>
> If you have uncertainty about the friendliness of agents encountered in
> the wild, which is going to be everyone, how do you get a reading about
> their friendliness. People will say oh it’s the government or Google so
> they get a starting point whether it be positive or negative or
> indeterminate. They’ll want to guide everyone to some rating like a 6. But
> to measure the friendliness from behavior, if it is ultimately a rate of
> entropy removed it’s still uncertain.
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