randomwalker

Yes, we're aware! Fortunately our book is not a broad indictment of AI :) And none of our claims are premised on tasks people can do remaining out of reach for AI. More here: https://www.normaltech.ai/p/faq-about-the-book-and-our-writi...

Our more recent essay (and ongoing book project) "AI as Normal Technology" is about our vision of AI impacts over a longer timescale than "AI Snake Oil" looks at https://www.normaltech.ai/p/ai-as-normal-technology

I would categorize our views as techno-optimist, but people understand that term in many different ways, so you be the judge.

Thanks! HN was part of the origin story of the book in question.

In 2018 or 2019 I saw a comment here that said that most people don't appreciate the distinction between domains with low irreducible error that benefit from fancy models with complex decision boundaries (like computer vision) and domains with high irreducible error where such models don't add much value over something simple like logistic regression.

It's an obvious-in-retrospect observation, but it made me realize that this is the source of a lot of confusion and hype about AI (such as the idea that we can use it to predict crime accurately). I gave a talk elaborating on this point, which went viral, and then led to the book with my coauthor Sayash Kapoor. More surprisingly, despite being seemingly obvious it led to a productive research agenda.

While writing the book I spent a lot of time searching for that comment so that I could credit/thank the author, but never found it.

Thanks for the comment! I agree — it's important to remain fluid. We've taken steps to make sure that predictively speaking, the normal technology worldview is empirically testable. Some of those empirical claims are in this paper and others in coming in follow-ups. We are committed to revising our thinking if it turns out that our framework doesn't generate good predictions and effective prescriptions.

We do try to admit it when we get things wrong. One example is our past view (that we have since repudiated) that worrying about superintelligence distracts from more immediate harms.

We do not assume a status quo or equilibrium, which will hopefully be clear upon reading the paper. That's not what normal technology means.

Part II of the paper describes one vision of what a world with advanced AI might look like, and it is quite different from the current world.

We also say in the introduction:

"The world we describe in Part II is one in which AI is far more advanced than it is today. We are not claiming that AI progress—or human progress—will stop at that point. What comes after it? We do not know. Consider this analogy: At the dawn of the first Industrial Revolution, it would have been useful to try to think about what an industrial world would look like and how to prepare for it, but it would have been futile to try to predict electricity or computers. Our exercise here is similar. Since we reject “fast takeoff” scenarios, we do not see it as necessary or useful to envision a world further ahead than we have attempted to. If and when the scenario we describe in Part II materializes, we will be able to better anticipate and prepare for whatever comes next."

I appreciate the concern, but we have a whole section on policy where we are very concrete about our recommendations, and we explicitly disavow any broadly anti-regulatory argument or agenda.

The "drastic" policy interventions that that sentence refers to are ideas like banning open-source or open-weight AI — those explicitly motivated by perceived superintelligence risks.