Machina Ratiocinatrix

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

The brain is a dynamic complex physical system. Every effectively realizable physical system is computable (the Church-Turing thesis). Ergo, the brain is computable. QED

💯A lot of AI hate is thinly veiled gatekeeping.

Hot take: machine learning and AI did more to understand the nature of knowledge, and our relation to reality than 20 centuries of philosophy. I am ready to kind of defend this hill.

There will be no AI jobpocalypse. The story that AI will lead to massive unemployment is stoking unnecessary fear. AI — like any other technology — does affect jobs, but telling overblown stories of large-scale unemployment is irresponsible and damaging. Let’s put a stop to it. I’ve expressed skepticism about the jobpocalypse in previous posts. I’m glad to see that the popular press is now pushing back on this narrative. The image below features some recent headlines. Software engineering is the sector most affected by AI tools, as coding agents race ahead. Yet hiring of software engineers remains strong! So while there are examples of AI taking away jobs, the trends strongly suggest the net job creation is vastly greater than the job destruction — just like earlier waves of technology. Further, despite all the exciting progress in AI, the U.S. unemployment rate remains a healthy 4.3%. Why is the AI jobpocalypse narrative so popular? For one thing, frontier AI labs have a strong incentive to tell stories that make AI technology sound more powerful. At their most extreme, they promote science-fiction scenarios of AI “taking over” and causing human extinction. If a technology can replace many employees, surely that technology must be very valuable! Also, a lot of SaaS software companies charge around $100-$1000 per user/year. But if an AI company can replace an employee who makes $100,000 — or make them 50% more productive — then charging even $10,000 starts to look reasonable. By anchoring not to typical SaaS prices but to salaries of employees, AI companies can charge a lot more. Additionally, businesses have a strong incentive to talk about layoffs as if they were caused by AI. After all, talking about how they’re using AI to be far more productive with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus. To be clear, I recognize that AI is causing a lot of people’s work to change. This is hard. This is stressful. (And to some, it can be fun.) I empathize with everyone affected. At the same time, this is very different from predicting a collapse of the job market. Societies are capable of telling themselves stories for years that have little basis in reality and lead to poor society-wide decision making. For example, fears over nuclear plant safety led to under-investment in nuclear power. Fears of the “population bomb” in the 1960s led countries to implement harsh policies to reduce their populations. And worries about dietary fat led governments to promote unhealthy high-sugar diets for decades. Now that mainstream media is openly skeptical about the jobpocalypse, I hope these stories will start to lose their teeth (much like fears of AI-driven human extinction have). Contrary to the predictions of an AI jobpocalypse, I predict the opposite: There will be an AI jobapalooza! AI will lead to a lot more good AI engineering jobs, and I’m also optimistic about the future of the overall job market. What AI engineers do will be different from traditional software engineering, and many of these jobs will be in businesses other than traditional large employers of developers. In non-AI roles, too, the skills needed will change because of AI. That makes this a good time to encourage more people to become proficient in AI, and make sure they’re ready for the different but plentiful jobs of the future! [Original text in The Batch newsletter.]

It is hard to overstate how disappointing I think this new paper from Oxford, OpenAI, Anthropic, and Google (et al) is. I can't take it seriously as academic work, just as propaganda. It also has some very bad scholarship and questionable adherence to research ethics. Having the title and author list that it has is not a great start, but I think that the actual content of the paper is also much worse than it could have been. The paper's content is a series of sections that mostly just list things with discussions that I think are generally vapid. For example, section 3.2 is titled "New and technical approaches to positive alignment" and has a collection of paragraphs on things like "goal setting and evaluations", "memory and in-context learning," and other general research topics of the LLM era. It overall strikes me as a paper built from the top down -- the authors wanted to make a certain point up top, and the paper's content ended up as filler. I think of this paper as a mechanism of corporate capture of concepts from academic research on AI and society. It discusses topics like pluralism, liberty, and education, and frames them as solvable problems whose solution is the right tech integrated in the right way. I think that when this paper says "pluralism", "liberty", and "accountability", it means them in a way that is profoundly vapid and structurally ignorant. For example, there is a list of papers out there arguing against this paper's perspective, saying that pluralistic alignment is not a model property or a technical problem at all. None of them were mentioned. Relatedly, the paper talks about some things that would be genuinely great if the authors' companies were not actively contributing to the problem. For example, section 5.1 is about the decentralization of power in the AI ecosystem. Great, but come on. To listen to this stuff from OpenAI, Anthropic, and Google employees, I need more than just a disclaimer at the end saying, "This research paper represents the author’s own views and conclusions." This is how big companies launder their reputations through research. The first author of the paper posted about it yesterday saying, "In a rare collaboration between top universities and 3 frontier labs..." So which is it? For a paper like this with this kind of author list to honestly and ethically engage in this kind of politics, it would need to seriously confront the question of how much these authors' institutions are actively working against goals like this. If not, the big tech company authors should not have worked on this paper in their formal capacity as representatives of their companies.