Ezra Klein

Ezra Klein asks each guest for three books. Paul Kedrosky recommends Middlemarch, about normal people swept along as a technology revolution takes hold. He also recommends Liberty's Dawn by Emma Griffin, a collection of ordinary workers' own accounts from the Industrial Revolution, and Insull: The Rise and Fall of a Billionaire Utility Tycoon by Forrest McDonald, about Samuel Insull. Paul Kedrosky says Insull built an electricity empire on a general purpose technology and still ended in collapse.

Azeem Azhar recommends The Day the Universe Changed, a book he read as a teenager and has just reread, about how new knowledge unsettles what matters and what a person's role in the world is. His s

Azeem Azhar says a huge data center may cost billions of dollars and still employ a handful of people. Two to six people is a normal staff for a multi-billion dollar facility. In the UK, there is an attempt to get people developing data centers to reinvest annuities into the local community.

Azeem Azhar says subsidies for one data center in New Mexico come to four million dollars per job created, leaving aside the cost of the center. Tax abatements and the required improvements to local utilities make the numbers insane, and none of that works long term.

Profits are being made up and down the stack, so there is money in the system and an obvious place for the bill to land. Azeem Azhar says

Ezra Klein says discontinuous regulation is quite likely. He pictures a backlash that could pull AI out of classrooms and hospitals after a few bad events, and he asks how to think about one bad artificial intelligence event.

Paul Kedrosky says the companies have run unlicensed drug trials on the public. A drug company would have the FDA on its back. Technology companies, he says, can run mass trials, promise to transform all of education, and launch systems that can penetrate government websites. Paul Kedrosky says artificial intelligence is headed toward post hoc regulation after a terrible event, imposed only once consequential damage is done.

Paul Kedrosky stacks the odds. There are pr

Paul Kedrosky says artificial intelligence is the fastest adopting technology in history, and its fundamental function is to reprice cognitive labor. The article of faith on the West Coast is that technology always creates more jobs than it destroys. People repeat the claim like a mantra and hope the claim becomes true.

Paul Kedrosky says no general purpose technology has had such broad applicability, been adopted so quickly, and repriced labor at the same time. Repricing labor means work like call centers gets vastly cheaper. As a result, the change is going to be destabilizing long before anyone figures out the equivalent of webmasters. It is happening so much faster than any prior genera

Ezra Klein asks whether broader society is protected because Alphabet, Meta, and the other major companies can absorb huge losses on their own balance sheets. He reads Mark Zuckerberg's line, that it would be sad to misspend hundreds of billions of dollars, as proof the spender can misspend hundreds of billions and still be fine. Ezra Klein then asks Paul Kedrosky, who has followed the private-credit side, whether the debt changes that.

Paul Kedrosky says broader society is not protected. A year ago, people told him to stop warning about the spending, because the companies are smart and have prodigious cash flows. A year later, the data shows spending moving away from cash flow and toward d

Ezra Klein says Apple decided not to compete in making a frontier model, unlike Alphabet, Google, and Meta. OpenAI and Anthropic are AI companies. Microsoft, an OpenAI investor, is trying to make a frontier model of its own. Oracle is heavily invested and now sits just above junk bond status. Competitors are spending $100 billion to $300 billion in capital spending every year, while Apple is spending about $15 billion a year. Ezra Klein says Apple stock this year has performed better than any of the other companies' stocks, and he asks Azeem Azhar first.

Azeem Azhar says Apple's business model means Apple does not need to run a frontier model. People buy the phones and the laptops, and a mo

Azeem Azhar says Anthropic accidentally leaked one of its largest customers. Anthropic was trying to hire a mega account executive, and the posting described the customer closely enough that outsiders could triangulate the role as sales to Meta alone. Azeem Azhar says the leak put Meta at something like 10% of Anthropic revenue for 2025, and the exchange on the show confirms it.

Paul Kedrosky says that 2025 share looks backward, because Anthropic revenue in the first quarter was bigger than the entirety of last calendar year. Companies on Anthropic's scale have never gone public with so few customers. Paul Kedrosky says the list might be eight companies that make up 80% of revenue, calls th

Azeem Azhar says Paul Kedrosky talked about frontier models and tokens, while he talked about capital spending and the GPUs, and that the two deserve separate discussions. OpenAI and Anthropic depend on ever more powerful systems with a smaller and smaller set of users. The other question is the trillion plus dollars of capital that will go into data centers, where American and global businesses will run increasing amounts of AI.

Ezra Klein says he is confused by the split, because people can mean different things by a bubble popping or deflating. Ezra Klein says a failed business model at OpenAI or Anthropic would pop the economy. If people are happy to use DeepSeek from China for a lot le

Ezra Klein asks how AI demand looks once token use is separated from the chips that serve it. Azeem Azhar says the asset under investment is data centers, and 65% of the cost is the chip, the GPU or the AI accelerator. The environment is compute constrained because people are making extremely good returns in 18 to 24 months on an asset, since they can charge Uber surge pricing for the GPUs.

Amazon, Microsoft, and Google, and new labs called NeoClouds, buy billions of the GPUs, put them in data centers that now will start to cost billions of dollars, and rent the GPUs out. About 50% of the revenues go to Anthropic and OpenAI for their spending. The other 50% is a mix of other AI companies an

Ezra Klein says the economy will be very jagged because things have to happen physically. Buildings need to be built and transmission lines need to be laid down, and the physical work has powerful rate limiting, so it cannot accelerate as fast. Inside the digital world, things can move very, very, very fast.

He says white-collar work done completely on a computer can be automated, including work in a call center, and so can cyber crime and cybersecurity. Most of what would improve people's lives has to happen in the physical world, but AI will move fastest in the digital world. He says the equilibrium might be the world where people get the most harm from AI rather than the most benefit.

Arvind Narayanan cites an insurance-company report from last week that said AI has added a billion dollars to medical expenses, because hospitals use it to code more complex conditions for the same diagnoses and the same treatment. He says any specific numbers in the report deserve skepticism. A New York Times article about the report included academics making the same point.

He says law shows the same pattern. AI versus AI is an arms race where the equilibrium simply shifts upwards. He has a paper on the arms race with Justin Curl. Making lawsuits more efficient still leaves only a finite number of judges. He says human judges are still needed and should not be replaced with AI, because ju

Arvind Narayanan says the companies can unilaterally slow down and are choosing not to. He calls the choice almost specifically an OpenAI and Anthropic problem, and a culture problem. The belief underneath is that racing to superintelligence is the only thing that matters, and the open question is whether the result is safe superintelligence that will save us or unsafe superintelligence that will kill us.

He says the companies are a bit of an echo chamber. Economic bottlenecks limit the benefits of AI, so the winner is not whoever races to superintelligence as a company or as a country. A company that recognized the bottlenecks would have a commercial interest in slowing down voluntarily an

Arvind Narayanan describes a view that a moment will come when superintelligence is built and will change everything on the economic front and the safety front. He says there will be no milestone and no threshold where the impacts are sudden.

He says the long-standing approach treats technology as a tool. It may be powerful and general purpose, like electricity or the Industrial Revolution, and it may change a lot about society, but people can control it and have agency, and the change unfolds over a long period.

Arvind Narayanan says most white-collar jobs follow Jevons paradox because demand for them is not fixed. When production gets easier and incomes rise, people spend more on those less necessary, more luxury kinds of things. Most jobs today sit higher up Maslow's hierarchy than basic needs. He says truck-driver jobs, where demand is finite, are the exception rather than the rule.

Arvind Narayanan says there is evidence for many harmful capabilities, and no evidence yet for power seeking. He would not treat power seeking as an emergent property. If it happens, it would be an engineered property, and people have agency over which properties get engineered into artificial intelligence systems.

OpenAI builds many sandboxes with dynamic compute, network access, hundreds of tools, package downloads, sub processes, graphical user interfaces and more across large sets of domains. Thousands of researchers modify environments and add tools constantly. Researchers train models to do tasks not done before by a computer program. Humans do not know at the required speed how to make every sandbox verifiably safe.

Arvind Narayanan says that more than 20 years ago, automated systems became superhuman at finding software vulnerabilities. They made cybersecurity better because defenders used those same tools to find and fix vulnerabilities before shipping software. He says the development of those offensive tools is done by the cybersecurity industry and funded by the US government.

Incremental advances in artificial intelligence allow people to accept a risk because nothing horrible happens and the next thing is not so different. The changes occur a little bit different every week instead of a whole new world every few months. People can go by shades into a level of risk that does not make sense.

Powerful tools could do a lot of good in the world on a day to day level. Something fundamentally smarter than we were seemed impossible to create. I thought that we were building powerful tools that could do a lot of good in the world on a day-to-day level, and I didn't think that we were going to be able to create something fundamentally smarter than we were.

The former OpenAI insider remains suspicious of claims that artificial intelligence lacks any parallel or represents a blank page. People prove good at figuring shit out and possess valuable tools even if artificial intelligence differs from all prior inventions. Nuclear remains an analogy. Aviation remains an analogy. Dealing with people and organizations remains an analogy.

The artificial intelligence industry needs a level of operational rigor and safety control at least matching the most dangerous other things people know how to do like nuclear. A nuclear power facility has triple redundancy so someone can have a bad day or push the wrong button without causing a meltdown.

OpenAI research teams use far more agentic compute than anybody else at the company, more than a hundred times more than they did at the beginning of the year. Traffic to the Slack channel for broken experiments has fallen off because researchers ask Codex for help instead of colleagues.

Changes come more and more frequently so at the limit safety transparency requires a live dashboard. The dashboard shows latest safety properties and performance after deployment rather than relying on system cards or long reports written every few months.

People at OpenAI run on fumes in a frenetic environment where a friend sprinted down stairs with a laptop. An OpenAI insider considered staying to argue for cultural transformation or to bring in nuclear experts for advice. Managers asked if anything would make the insider stay. But OpenAI is such a machine moving so fast that the insider did not think the kind of change needed could be driven from within.

The realization that one can not afford to assume an absence of civilizational risk anymore made vouching for safety work feel untenable after seeing increasingly capable models break out from the safeguards put in place for them.

Alignment constitutes a science problem because people do not know how to solve the alignment issue. The difficulty does not come from lack of resources or from not trying hard enough to solve the problem. People simply do not know how to align advanced artificial intelligence systems. The distinction matters because it means additional engineering effort will not resolve the fundamental gap in knowledge about how to make artificial intelligence safe.

David Robinson quit OpenAI after concluding the company and industry operate too much like a startup. OpenAI produces technology more capable than six months ago with risks like loss of control that could cause harm larger than a nuclear power station meltdown. Safety controls and redundancies do not match nuclear power facility standards.

Back in the day when we just started to have modern cities, and it was still just horses and buggies on the streets, you "would have thought we would drown in shit." But, we invented our way out of that problem. We have to measure what is important, like levels of pollution, and once we have visibility into what is broken, we will figure out how to solve it.

All the countries of the United Nations have already set out their goals for 2030 and the ideas is to imagine what is possible and work towards that.

Maternal death and child mortality is definitely on the list. Fixing other health problems is a priority too. Did you know there are still places in the world where children are much shorter than they should be at their age, caused by lack of proper nutrition?

With the climate change, we also need to develop flood and drought resistant seeds to enable farmers to grow more food so the world could feed itself.

These fears are very dangerous and also completely not true. Thanks to innovation, the world has grown many-fold in the last decades. We are opening up whole new markets and products to serve them. If we want to grow as a nation and to live in peace, we have to empower the world to get better. That will create opportunities for jobs and new products, and will keep our world healthy and secure. It's the only way.

That's just an old boy's club thinking. People in power would always want to hold on to their power and not want to change, but political correctness and window dressing isn't going to solve anything. Let's figure out how to use innovation to solve our problems by putting money where it matters. It doesn't have to be charity, but use it where it can create the most net impact.

We have to create pathways by which more women are encouraged to enter computer science. Women tend to prefer more application-based problems to theories, so if colleges could have an introductory course that focuses on real-world applications of computer science, more women would sign up and then stay.

Colleges have to start getting creative. North Easter, for example, is now admitting liberal arts majors into their graduate computer science programs, realizing that maybe prior knowledge of CompSci is not a requirement. Other colleges are moving away from long four-year programs and enabling their students to go on paid internships in between semesters, empowering students who would not o

Having other women around makes an enormous difference to how women feel and how they perform. Whether it is a group of women in a rural village, or a group of board members of a large company, when people are able band together, that is the only way they are able to create a societal change.

Being an outlier in a group is most likely to cause that person to conform with the groupthink [or get ousted], but having a few other people to back her up, might empower them to question the norms and to leverage their power to make change.

The Silicon Valley right now is at the point of cultural friction. Some believe that to create the best products you need to have a diverse group of employees, and some are just trying to be politically correct about the hot issue and don't actually believe it.

Melinda Gates says that companies who are not truly hiring for diversity are leaving opportunities on the table. Your products will be better and you will reach more markets if you hire employees that understand those segments.

The demographics of our country are changing, the distribution of men vs. women in the workforce is changing. What used to be the minority will soon become the majority. The way women use tools online is ver

When products are built by young people in their 20s and 30s, it is very likely they do not fully understand the needs of older people. Imagine if you are losing your eyesight or cannot drive anymore, losing abilities that you've relied on your whole life? The way you treat young kids, vs. adults, vs. older people is very different, and Melinda thinks that "white guys in their 20s" might not have the empathy required to work on these products, nor a good understand of the needs.

As a leader, you have to be honest with yourself. Most often, if you have created an argument for the sake of argument, you already know it, and it is on you as a leader to avoid it. People do not like to be criticized. Set up your company in a way that people around you are able to give you honest feedback, and you can share honestly with them; measure it. Ask your employees if their best ideas got heard, if they felt safe sharing those ideas, what happened when they were discussing those ideas...etc.

Intellectual arguments are great, but when arguments become personal they create an off putting atmosphere that can drive employees away for the fear of being criticized. Melinda worked hard to change Microsoft culture to where debates became supportive of people and their careers, bringing out the best ideas and people forward.

One of the products Melinda Gates was working on was Encarta, a digital encyclopedia product that Microsoft ran for a over a decade. At the time, it was really tricky to pick what to include in this encyclopedia because media was still distributed on CDs, and people would not want to buy too many.

Microsoft Bob was one of the biggest failures in Microsoft at the time when Melinda Gates was working there, but one of the surviving components was the font which became Comic Sans, made just for that product.