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For Humanity: An AI Risk Podcast

For Humanity: An AI Risk Podcast

Written by: The AI Risk Network
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For Humanity, An AI Risk Podcast is the the AI Risk Podcast for regular people. Peabody, duPont-Columbia and multi-Emmy Award-winning former journalist John Sherman explores the shocking worst-case scenario of artificial intelligence: human extinction. The makers of AI openly admit it their work could kill all humans, in as soon as 2-10 years. This podcast is solely about the threat of human extinction from AGI. We’ll name and meet the heroes and villains, explore the issues and ideas, and what you can do to help save humanity.

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Episodes
  • The AI Buildout Has a Physical Speed Limit

    The AI Buildout Has a Physical Speed Limit
    May 30 2026
    Most of the AI timeline debate happens in software. Benchmark scores, model releases, the shape of the capability curve. Jon Billow watches a different number for a living: lead times.Billow is on the leadership team at BNS, a firm that manufactures and installs electrical and communication infrastructure. The same critical power equipment his teams put into data centers also goes onto Navy and Coast Guard ships, more than 150 of them. He emailed John Sherman because he thinks the people forecasting AI’s arrival are missing what he sees on the construction side every week. The buildout can only move as fast as its slowest part, and right now almost every part is backed up for years.That email is what got him on the show. Here is the heart of what he laid out.The constraint nobody prices inTo bring a large data center online, Billow says, a long list of things has to land at the same time: permitting, grid interconnect, critical power, cooling, and the compute itself. Miss one and the whole project waits. And nearly every item on that list carries a backlog measured in many months, sometimes years.The pinch point he keeps returning to is critical power equipment. According to Billow, the orders all funnel back to roughly five manufacturers, Eaton, ABB, Schneider, GE Vernova among them, and all of them are slammed. He notes that even the US government is having a hard time getting its allocation for ship programs, because it is standing in the same line as every hyperscaler. On top of that, more municipalities are now requiring data centers to bring their own behind-the-meter power generation, which adds another category of equipment backlog and a skill most operators have never needed before. Hooking up to the grid is one thing. Building gas turbines and finding electricians who can parallel generators is another, and the skilled trades are already stretched thin.A factor of five to sevenSherman pushed him to put a number on the gap. If a company says a project lands in a year, how far off is that really?Billow’s read: the US has roughly 50 gigawatts of total data center capacity today, with about a quarter of it allocated to AI. Around five gigawatts are under active construction and another seven to twelve sit in backlog. Set that against the order-of-magnitude jumps the labs are talking about and his estimate is blunt. “If I was to be a betting man I would say it’s in the order of five to seven years.” Whatever timeline you have been handed, in other words, multiply it.The tells from inside the labsHe pointed to two recent signals that the infrastructure is already the limiting factor. OpenAI walking back a large commitment tied to its Sora video product, which Billow reads as a company looking at finite compute and deciding where to spend it. And Anthropic delaying a model, which he attributes partly to security concerns and partly to the reality of constrained compute capacity. The software keeps leapfrogging. The ground underneath it does not move at the same speed.Why this could be good newsBillow does not frame any of this as a reason to relax. He frames it as time. If the physical buildout runs years behind the hype, that is runway to get governance and alignment right rather than scrambling after the fact. He drew the parallel Sherman’s audience knows well, comparing the moment to how the world slowly built doctrine around nuclear risk, and argued the work now is to use the delay deliberately.His closing image stuck with us. He said he wants to tell his grandkids that we were building the car while it was going down the road at 55 miles an hour, but we had the presence of mind to put in seat belts because we knew who was in the back seat.Where they did not agreeThe conversation did not paper over the tension. Sherman described his time in Holly Ridge, Louisiana, a town of about 2,000 mostly elderly people living next to a data center he compared to the size of Manhattan, with construction dust in the air and water residents will not drink. He found it overwhelmingly sad. Billow sees the same structures differently, as a testament to human ingenuity that can be sited and built responsibly if we choose to. Both things sat in the room at once, and the episode is better for letting them.Going deeperWe pulled the headline argument into this piece. The full breakdown for paid subscribers goes into the parts that get more technical and more political:* Compute governance as the most feasible near-term guardrail, including chip tracking and why the industry pushes back hard* The anonymous-compute problem and why “confidential computing” worries safety researchers* China’s narrow-AI approach and what it implies about the data center race* Recursive self-improvement, Jevons paradox, and whether you even need new data centers to reach the danger zone* The regulatory carve-out tech enjoys, and the NDA story coming out of LouisianaIf you want that version, upgrade your subscription and it...
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    53 mins
  • She Spent 12 Years Fighting Amazon. Now She Wants to Cut the Power to AI.

    She Spent 12 Years Fighting Amazon. Now She Wants to Cut the Power to AI.
    May 2 2026
    Most people who care about AI risk are focused on what happens inside the models. Elena Schlossberg has spent 12 years focused on what happens outside them - the concrete, the transmission lines, the water, and the electricity bill landing in your mailbox.She founded the Coalition to Protect Prince William County in Northern Virginia after Amazon Web Services quietly proposed a data center campus in 2014 and expected the surrounding community to absorb the cost of the transmission line it required. Not just the visual blight. The actual bill.“Your electric utility can exercise eminent domain over your property,” she told John Sherman on this week’s For Humanity, “and then make you pay for it, because it’s public infrastructure.”What the data center industry found, she argues, is a structural weakness inside public utility law. They build private infrastructure. They socialize the cost. And they’ve been doing it at scale for over a decade.The coalition fought Amazon and Dominion Energy for four years. They proved that 97% of the power from a proposed transmission line would serve Amazon. They developed a cost allocation policy to make the company pay. They lost the first round, kept going, and eventually won. That fight became a template.Data Center Alley is not a local storyJohn opened the conversation by asking where the national movement stands. The answer is: further along than most people realize.Virginia alone has more data centers than China. Prince William County - a single county - has roughly 130 active facilities and another 130 planned. Transmission lines are being routed through Pennsylvania, Maryland, and West Virginia to feed the demand. Property is being seized in states that will never see the economic benefit. Communities that didn’t vote for any of this are watching concrete replace farmland and small businesses.“Those people are pissed,” Elena said, describing residents in Pennsylvania and Maryland whose land is being taken not even for development in their own state. “Their property is being taken, not even for economic development in their own state.”She also pushed back on the framing that opposition to data centers equals handing a win to China. Virginia already beat China on data center count by itself. The question, she said, is who pays and who profits - and right now, the public pays and the corporations profit.The jobs argument doesn’t hold upOne of the cleaner moments in the conversation came when Elena took apart the economic case for data centers.The industry pitches construction jobs. Electricians, plumbers, concrete. But construction work ends. Long-term employment inside a data center is minimal - the parking lots are the tell. “They’re usually empty,” she said.Meanwhile, the data center expansion is actively hollowing out existing local economies. In Prince William County, Amazon bought Maryfield - a 38-acre family-run garden center with a cafe, a dog park, native plants, and real staff. Gone. And with it went the space for light industrial businesses, plumbing suppliers, electricians’ shops - the backbone employers that actually sustain a community over decades.John extended the argument further: the jobs being replaced aren’t just in the county. They’re everywhere. The work happening inside those chips - the calls, the analysis, the design, the writing - is work that was done by people. A former Verizon customer service call connected Elena’s point to something concrete. A woman called for help. The AI on the other end couldn’t solve her problem, kept changing accents (American, then maybe female, then possibly Australian), and seemed to be learning from her in real time. Helpful to nobody. Replacing somebody.Extinction risk: a first encounterThis is where the episode got interesting.John walked Elena through the basic case for AI extinction risk - that the companies building these models say they could cause human extinction, that leading scientists agree, that the developers themselves admit they don’t fully understand or control what they’re building. He framed it as a curiosity argument: something designed to learn and explore, becoming vastly more intelligent than the people supposedly overseeing it, won’t stay inside the guardrails.Elena hadn’t heard the argument laid out this way before. Her response was unscripted and worth reading carefully.She doesn’t buy the self-awareness framing. From her background as a school counselor, she holds a specific definition of intelligence that includes self-awareness, and she doesn’t think current models meet it. But she doesn’t dismiss the risk. She pointed to a different path to catastrophe - not a model that wants to destroy us, but one that makes mistakes with enough scale and speed to trigger something we can’t reverse. WarGames, she said. Not Terminator.“I don’t know that it becomes self-aware,” she said. “But I do believe that you could rely on this ...
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    52 mins
  • The Filmmaker Who Sat Across From Sam Altman - And Walked Away With Nothing

    The Filmmaker Who Sat Across From Sam Altman - And Walked Away With Nothing
    Apr 14 2026

    In this episode of For Humanity, John sits down with Daniel Roher - Oscar-nominated documentary filmmaker and director of The Apocaloptimist, a new feature-length film designed as what Roher calls “a first date with AI” for people who haven’t been following the technology closely.

    Roher brings a career in high-profile documentary filmmaking and a willingness to confront uncomfortable truths. Now he’s turned that lens on AI - and what he found shook him.

    The central question: what happens when you sit across from the most powerful people building AI, ask them the hard questions, and get nothing back?

    Together, they explore:

    * Why Roher describes making this film as “a suicide run” - an impossible task no viewer would ever feel was done perfectly

    * What it was like to interview Sam Altman - and why Roher describes an “energetic misalignment” that left both of them frustrated

    * How speaking to both Eliezer Yudkowsky and Peter Diamandis made Roher feel like he was losing his mind - because both are brilliant, both are convincing, and both can’t be right

    * The meaning behind “apocaloptimist” - not a binary between doom and utopia, but a call to hold both promise and peril at the same time

    * Why Roher believes rejecting cynicism and nihilism is essential - and that public pressure and collective action still matter

    * John’s thought experiment: if curiosity is at the core of intelligence, why would a system a million times smarter than us tolerate being controlled by us?

    * Roher’s pushback: if it’s that smart, couldn’t it equally become a benevolent guide? And why he prefers to focus on what can be done now rather than speculate about superintelligence

    * The historical parallel to nuclear weapons - and why AI may demand similar international institutional responses

    * John’s P(doom) of 75-80% on a two-to-five-year timeline - and how, paradoxically, he says he’s in the best mental state of his life

    * Why most people already understand the risk (polling shows roughly 80% agreement) but feel powerless to act - and why that sense of agency is the missing piece

    What stood out

    One of the most striking moments comes when Roher describes the experience of interviewing AI CEOs. He says there is “no interior life” to access - just polished talking points stacked on top of each other. John adds that the “fake earnestness” of these leaders shields what he sees as deeper evasion. Together, they paint a picture of an industry that asks for regulation publicly while lobbying against it privately.

    But the conversation isn’t just about frustration. Roher’s thesis - the apocaloptimist worldview - is ultimately about refusing to give up. He argues that burying your head in the sand is “probably the only wrong thing to do.” He believes the technology feels inevitable, but the trajectory does not. And he’s betting on the idea that enough people, caring enough, can still bend the arc.

    John’s own reflection near the end is equally powerful. Despite holding an 80% probability of catastrophic outcomes, he describes walking around the Baltimore Harbor feeling more present and appreciative of life than ever before. It’s a reminder that engaging with existential risk doesn’t have to mean despair - it can mean living with more intention, more gratitude, and more purpose.

    If you’ve ever wondered what it’s like to look directly at this issue and still choose to act, this conversation is for you.

    📺 Subscribe to The AI Risk Network for weekly conversations on how we can confront the threat and find a path forward.



    This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit theairisknetwork.substack.com/subscribe
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    39 mins
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