Science and Technology

Context: looking for an alternative to a pause on AI development.

There’s some popular desire for software decisions to be explainable when used for decisions such as whether to grant someone a loan. That desire is not sufficient reason for possibly crippling AI progress. But in combination with other concerns about AI, it seems promising.

Much of this popular desire likely comes from people who have been (or expect to be) denied loans, and who want to scapegoat someone or something to avoid admitting that they look unsafe to lend to because they’ve made poor decisions. I normally want to avoid regulations that are supported by such motives.

Yet an explainability requirement shows some promise at reducing the risks from rogue AIs.

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Robin Hanson suggests, partly in response to calls for a pause in development of AGI, liability rules for risks related to AGI rapidly becoming powerful.

My intuitive reaction was to classify foom liability as equivalent to a near total ban on AGI.

Now that I’ve found time to think more carefully about it, I want to advocate foom liability as a modest improvement over any likely pause or ban on AGI research. In particular, I want the most ambitious AI labs worldwide to be required to have insurance against something like $10 billion to $100 billion worth of damages.

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I previously said:

I see little hope of a good agreement to pause AI development unless leading AI researchers agree that a pause is needed, and help write the rules. Even with that kind of expert help, there’s a large risk that the rules will be ineffective and cause arbitrary collateral damage.

Yoshua Bengio has a reputation that makes him one of the best people to turn to for such guidance. He has now suggested restrictions on AI development that are targeted specifically at agenty AI.

If turned into a clear guideline, that would be a much more desirable method of slowing the development of dangerous AI. Alas, Bengio seems to admit that he isn’t yet able to provide that clarity.

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Book review: Four Battlegrounds: Power in the Age of Artificial Intelligence, by Paul Scharre.

Four Battlegrounds is often a thoughtful, competently written book on an important topic. It is likely the least pleasant, and most frustrating, book fitting that description that I have ever read.

The title’s battlegrounds refer to data, compute, talent, and institutions. Those seem like important resources that will influence military outcomes. But it seems odd to label them as battlegrounds. Wouldn’t resources be a better description?

Scharre knows enough about the US military that I didn’t detect flaws in his expertise there. He has learned enough about AI to avoid embarrassing mistakes. I.e. he managed to avoid claims that have been falsified by an AI during the time it took to publish the book.

Scharre has clear political biases. E.g.:

Conservative politicians have claimed for years – without evidence – that US tech firms have an anti-conservative bias.

(Reminder: The Phrase “No Evidence” Is A Red Flag For Bad Science Communication.) But he keeps those biases separate enough from his military analysis that I don’t find those biases to be a reason for not reading the book.

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I encourage you to interact with GPT as you would interact with a friend, or as you would want your employer to treat you.

Treating other minds with respect is typically not costly. It can easily improve your state of mind relative to treating them as an adversary.

The tone you use in interacting with GPT will affect your conversations with it. I don’t want to give you much advice about how your conversations ought to go, but I expect that, on average, disrespect won’t generate conversations that help you more.

I don’t know how to evaluate the benefits of caring about any feelings that AIs might have. As long as there’s approximately no cost to treating GPT’s as having human-like feelings, the arguments in favor of caring about those feelings overwhelm the arguments against it.

Scott Alexander wrote a great post on how a psychiatrist’s personality dramatically influences what conversations they have with clients. GPT exhibits similar patterns (the Waluigi effect helped me understand this kind of context sensitivity).

Journalists sometimes have creepy conversations with GPT. They likely steer those conversations in directions that evoke creepy personalities in GPT.

Don’t give those journalists the attention they seek. They seek negative emotions. But don’t hate the journalists. Focus on the system that generates them. If you want to blame some group, blame the readers who get addicted to inflammatory stories.

P.S. I refer to GPT as “it”. I intend that to nudge people toward thinking of “it” as a pronoun which implies respect.

This post was mostly inspired by something unrelated to Robin Hanson’s tweet about othering the AIs, but maybe there was some subconscious connection there. I don’t see anything inherently wrong with dehumanizing other entities. When I dehumanize an entity, that is not sufficient to tell you whether I’m respecting it more than I respect humans, or less.

Spock: Really, Captain, my modesty…

Kirk: Does not bear close examination, Mister Spock. I suspect you’re becoming more and more human all the time.

Spock: Captain, I see no reason to stand here and be insulted.

Some possible AIs deserve to be thought of as better than human. Some deserve to be thought of as worse. Emphasizing AI risk is, in part, a request to create the former earlier than we create the latter.

That’s a somewhat narrow disagreement with Robin. I mostly agree with his psychoanalysis in Most AI Fear Is Future Fear.