Professor @Wharton studying AI. New book, Co-Existence, coming October 20. Preorder here: co-existence.ai/ Substack: oneusefulthing.org/

Philadelphia, PA
I just got the first copies of my new book, Co-Existence (out October 20) & they look great! Also, there is a fun pre-order bonus: if you pre-order, you get a code to an AI interview that will help you figure out how to use your human advantages with AI. co-existence.ai/
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How do you picture a superintelligence (if true superintelligence could ever be real)? I like a trick from Dungeons and Dragons for running villains with 25 Intelligence: don't try to out-plan the players. Instead, whatever they do or roll, play it like the big bad saw it coming.
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So is there some sort of weird scam being conducted with X Money? I haven't turned it on, but occasionally I get a post of mine massively retweeted by bots saying "lets send him X Money" or something similar, and it makes me think there is some elaborate (crypto?) thing going on
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I think my upcoming book, Co-Existence, might be the first to include a blurb written specifically for AI readers, in this case from @tylercowen (whom I thought AIs would respect) The book website (with elaborate pre-order bonus) also has a page for AIs: co-existence.ai/
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"The best current evidence supports a narrow claim: AI may already be affecting the hiring margin for junior white-collar roles most exposed to AI, but this attribution is contested, and aggregate labor-market disruption has yet to appear in the data." aleximas.substack.com/p/has-…
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People asked for me to upload the Bitter Lesson video from this piece to YouTube, so here you are: piped.video/OAwat51S_Sk
I wrote about the thing I underestimated most about progress in AI: its ability to self-organize to accomplish tasks. Also, what that means for agents like Muse and Dots, along with a music video explaining why we keep relearning The Bitter Lesson. open.substack.com/pub/oneuse…
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Yes! I think there is too much "we're so early" self-congratulation here. Many senior leaders in companies are smart, motivated, and understand a lot about their business. Many are also technically adept. They are absolutely getting AI. But changing a company is a longer process.
Everyone uses AI by now. Senior leaders are vibecoding apps. They've adopted claude. They're finding workflows to automate. Folks have their own claws. AI capex is keeping the S&P afloat. Corporate America's geared up. It's all very much mainstream. We're not so early anymore.
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“We find that on medium-length, well-defined accounting tasks, frontier AI models are now faster and more accurate than junior accountants, even the best one in our study.” Eighteen months ago they scored well below human accountants Good discussion here: mercor.com/blog/human-baseli…
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Sitting through PowerPoints has become much better since we got good AI. Sure, some people just let AI do the thinking work, but that is obvious (and they used default templates before). For people who do care, they have interesting layouts & funny visual jokes & good diagrams.
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I wrote about the thing I underestimated most about progress in AI: its ability to self-organize to accomplish tasks. Also, what that means for agents like Muse and Dots, along with a music video explaining why we keep relearning The Bitter Lesson. open.substack.com/pub/oneuse…
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And its a 3-way race again….
Introducing Gemini 4 Argon, our new frontier model, rolling out to cyber defenders starting today, and more widely as soon as possible. I am really excited by the progress we have made here. Argon is priced at $2 in and $10 out during introductory pricing!
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Every firm's customer service agents are about to be overwhelmed with Dots & Muses & etc. negotiating for better deals using voice/chat. Stories of people delegating this sort of work to their agents & saving money as a result are popping up and are going to only go more viral.
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They can use the channels built for humans, but which have far too much friction for any human to use. Your Clawlike is happy to navigate a phone tree or stay on hold or have an awkward conversation with an agent where they get rejected... and then try again.
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This is one of the most important questions of the age: Who decides what happens with AI? Daron makes the argument for much more democratic input into the process, despite the many challenges that entails.
Second question on AI. We are told repeatedly that AI is going to transform every aspect of our lives – jobs, productivity, inequality, science, communication, daily activities, social order, and politics, among others. But this promise (or threat) is coupled with the rhetoric that such an important technology, with all of the risks and competitive pressures that it entails, should be left to experts or to “technocracy” (perhaps construed broadly to include some regulators). These two statements are hard to reconcile in a democratic society. If anything is half as important as AI is said to be (and I agree, AI is potentially very important and transformative), then involving democratic voice is essential. If something will shape our future in a democratic society, then its direction is for democratic institutions to decide. My instinct is that democratic voice is essential, and relying too much on technocracy could be both dangerous and counterproductive. The counterargument that AI’s direction can and should be entrusted to technocracy would go something along the following lines. First, democratic decision-making has become imperiled in our age of polarization. Second, AI is sufficiently complex that most citizens won’t have a deep enough understanding to meaningfully contribute to the debate (and even to the question of what we want from AI). Third, competition between different labs, and perhaps competition between the US and China, creates enough discipline for a socially beneficial direction of AI to be adopted. Fourth, today’s AI leaders are enlightened and ethical enough that within the framework created by competition, they can be broadly trusted. There are many aspects of this counterargument that I do not find convincing. Taking them in order: polarization can be overcome, and big decisions and challenges sometimes bring societies together; in fact, delegating key decisions to technocracy without democratic input may diminish trust in institutions and experts, and may worsen polarization. Second, democratic voice does not require citizens to write code or design new models; the debate should be informative enough that citizens can weigh in about what type of future they want and how they trade off the costs and benefits of different options. Third, competition doesn’t seem to be a good disciplining framework; on the contrary, competition sometimes brings the worst out of both organizations and people. Fourth, if three decades of work on political economy and institutions has taught me anything, it is that we should not bank on the ethical grounding of unconstrained leaders. But, still, I do not mean to immediately dismiss the technocracy option if there are more compelling arguments for it. The question is, then, whether there are any circumstances under which such important decisions can be delegated to AI experts and technocracy. One final secondary question: even if we managed to get democratic input in the United States or even in Europe, AI will shape the lives of everyone on this planet. How do we ensure that the voice of nearly 6 billion people who don’t live in the US, Europe and China also contributes to the debates on AI?
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A thing to know about the AI business is labs that have frontier models can release half-built products and they work surprisingly well because the AI can just figure stuff out and improvise. Its like including a forward deployed engineer & customer service agent in the product.
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A broken early version of whatever product they are shipping is still better then what a well-built traditional product a lot of the time because LLMs are just unreasonably effective tools at doing a vast array of stuff and people & companies are learning to just roll with it.
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Every one of the apps from the AI Labs have weird edges and are underdocumented and break sometimes and update without any sort of notice or changelog and change UIs on a dime... ... but the models behind them are really good and so everyone just shrugs and keeps on using them.
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After a brief period where OpenAI seemed to be unifying work around the ChatGPT app, between Dot and Spaces and Pages and local/cloud ChatGPT Work and Scheduled Tasks in the Cloud and Scheduled Tasks on your computer, everything is getting quite confusing and overlapping again.
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I don't even know which tool has permission to do which things on which devices. Like Dot can create threads and tasks in Codex/ChatGPT app & Voice mode also creates threads and sometimes those threads continue and sometimes they are abandoned and none of this is very clear now.
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Leaving aside Anthropic's incentives for publishing this research, there is no doubt that open weights models will soon create the same security threats that closed source models have been demonstrating, except without guardrails. We are close. Probably good to plan accordingly.
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