Nearly a book review: Situational Awareness, by Leopold Aschenbrenner.
“Situational Awareness” offers an insightful analysis of our proximity to a critical threshold in AI capabilities. His background in machine learning and economics lends credibility to his predictions.
The paper left me with a rather different set of confusions than I started with.
His extrapolation of recent trends culminates in the onset of an intelligence explosion:
Back in 2008, I criticized the book Predictocracy for proposing prediction markets whose contracts would be resolved without reference to ground truth.
Recently, Srinivasan, Karger, and Chen (SKC) published more scholarly paper titled Self-Resolving Prediction Markets for Unverifiable Outcomes.
Continue Reading[I mostly wrote this to clarify my thoughts. I’m unclear whether this will be valuable for readers. ]
I expect that within a decade, AI will be able to do 90% of current human jobs. I don’t mean that 90% of humans will be obsolete. I mean that the average worker could delegate 90% of their tasks to an AGI.
I feel confused about what this implies for the kind of AI long-term planning and strategizing that would enable an AI to create large-scale harm if it is poorly aligned.
Is the ability to achieve long-term goals hard for an AI to develop?
Continue ReadingI’ve been hearing vague claims that automated theorem provers are able to, or will soon be able to prove things about complex software such as AIs.
Max Tegmark and Steve Omohundro have now published a paper, Provably Safe Systems : The Only Path To Controllable AGI, which convinces me that this is a plausible strategy to help with AI safety.
Continue ReadingBook review: The Coming Wave: Technology, Power, and the Twenty-first Century’s Greatest Dilemma, by Mustafa Suleyman.
An author with substantial AI expertise has attempted to discuss AI in terms that the average book reader can understand.
The key message: AI is about to become possibly the most important event in human history.
Maybe 2% of readers will change their minds as a result of reading the book.
A large fraction of readers will come in expecting the book to be mostly hype. They won’t look closely enough to see why Suleyman is excited.
Continue ReadingContext: 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.
Continue ReadingI’m wondering how selection effects will influence the first serious attempt by an AGI to take over the world.
My question here is inspired by thoughts about people who say AGI couldn’t conquer the world because it will depend on humans to provide electricity, semiconductors, etc.
Continue ReadingI participated last summer in Tetlock’s Existential Risk Persuasion Tournament (755(!) page paper here).
Superforecasters and “subject matter experts” engaged in a hybrid between a prediction market and debates, to predict catastrophic and existential risks this century.
Continue ReadingRobin 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.
Continue ReadingI 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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