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Radio News the Iran war showed little signs of de escalating this week, with Israeli forces targeting nuclear development sites in Iran, the US Attacking Iranian minelaying vessels in the Strait of Hormuz, and Iranian drones striking Dubai International Airport. President Trump and Iran's new supreme leader each vowed Thursday to keep up their respective military campaigns amid mounting oil prices.
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Every day we lose about 20% of global oil supplies.
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We are just shy of $100 a barrel on Brent now.
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In a post on Truth Social, Trump wrote that preventing Iran from threatening the Middle east and having nuclear weapons was far more important to him than the cost of oil. Iran's new supreme leader, Ayatollah Mujtaba Khamenei, said Iran would continue its blockade of the Strait of Hormuz and adding that he'd consider opening other fronts if the war continues. But the war has already expanded to an important new front how it's being waged with AI enabled weaponry. In just the first 24 hours of the Iran war, the US hit more than 1,000 targets, according to the commander of US forces that is double the scale of the assault that opened the Iraq war in 2003.
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The decision to wage a campaign like this is intimately linked to how remotely the US can pursue this war.
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That's Bloomberg national security and tech reporter Katrina Manson.
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It's clearly really important for Donald Trump not to send US Troops in on the ground. So conducting an air war with the help of AI suddenly becomes critical to his own pursuit of a war.
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The US first strikes on Iran came hours after the Pentagon severed its contract with Anthropic, an AI company that had been working directly with the US Military. The Pentagon has formally notified Anthropic that it's deemed the artificial intelligence company and its products a supply chain risk to the United States.
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The Pentagon has said it needs the ability to use CLAUDE for, quote, all lawful purposes.
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Anthropic, which is best known for its CLAUDE AI tool, wanted assurances from the US Government that its technology would not make lethal decisions on its own or helped to conduct mass surveillance on Americans. Anthropic's ouster and a move by its rival OpenAI to start working with the Department of Defense have struck a nerve. Some Americans are applauding Anthropic's decision. CLAUDE went down last week because of unprecedented demand. It's the latest turn in a long simmering debate over how the US Military works with Silicon Valley companies and how those tech titans contribute to the development of AI weapons systems. Katrina took a deep dive into that story, and it's a big part of her forthcoming book on the US Military and AI.
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AI may be good for scale, it may be good for speed, but is it as good for accuracy and saving lives as these claims have been made in the past? We don't know yet.
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I'm David Gura and this is the big take from Bloomberg News today on the show as Anthropic and the Pentagon feud. How is the US integrating AI into its war fighting machine? How is AI enabled weaponry being regulated? And is the tech as good as it needs to be with so many lives at risk? About five years ago, Dario Amadeh and his sister left their jobs at OpenAI to found Anthropic, an AI company meant to enforce strong safety guardrails. Since then, Anthropic has achieved mainstream success with Claude. It's even managed to partner with the US government. But that all changed at the start of the year. Bloomberg senior editor Mike Shepard has been following the saga closely.
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The Pentagon began reviewing how it wanted to roll out artificial intelligence across the armed forces, and in January, they put out an order from Defense Secretary Pete Hegseth saying that they needed to accelerate adoption across the Defense Department, which he refers to as the Department of War. He put up posters around the building saying the government wants you to use AI as part of it. They included language that said they did not want to be bound by any usage restrictions that might come from an AI provider of any stripe. They didn't single out Anthropic. But Anthropic is not only one of the leading AI developers and providers in the world. They are one that has stood out for what many see as its safety first stance and its adherence to principles of trying to develop AI with a mind toward avoiding some of the worst case scenarios. Now, for its part, Anthropic has expressed continued interest in working with the military so long as the Pentagon and military officials abide by those usage restrictions. And the two that have really been a red line for the company concern the use of its AI technology for mass surveillance of Americans domestically and then also fully autonomous weapons deployment. They, as the developers of the technology, insist that they don't have full confidence that it's ready for those uses safely.
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Katrina, you have a book coming out later this month on the Pentagon's efforts to integrate AI into warfare. I'm curious when that initiative started. When did the Pentagon begin looking into this in earnest?
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The Pentagon likes to say it's been developing AI for 60 years. But the real project that I think we can set the timer by is Project Maven, which started in 2017. And it was an effort that really spoke to America's concern about falling behind China. The US began to realize it was using old tech and that this new age of warfare was coming that would require robots, autonomy and AI. And Project Maven was this effort to experiment with AI. At the time, the cutting edge was computer vision, things that could identify objects on a video feed taken by drones and process that quicker. But the people I spoke to also explained to me that all along they imagined that this would help with targeting.
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You write about the software that comes out of Project Maven, Maven Smart System, which is made by Palantir and incorporated technology from Amazon and Microsoft and others. Is this something the Defense Department thought they could do in house, or was it always something that they needed the cooperation of private industry?
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It's a real core point that obviously the Pentagon is still struggling with for this very advanced tech, this recognition that has been happening over the past 10 years that warfare is going to be what some call software defined. They need commercial companies and so When Project Maven happened for the first time, really, they were going outside the traditional primes, as they're known, the traditional defense contractors, and looking at companies like Google, Microsoft and Amazon, but other tiny startups as well, who were just beginning to experiment with fascinating algorithms that could detect images on wedding cakes and then reapplying that for the tools of war. And that transition was incredibly uncomfortable, clunky, difficult. And it backfired at one point rather spectacularly when in 2018, Google workers discovered that their company was working on Project Maven and they feared that their tech and their traditions for them could be subverted into what they ended up calling in a protest letter, the business of war. And the parallel with Anthropic today isn't quite the same. The CEO of Anthropic all along has said he believes in national security work more than any other AI lab. Anthropic has lent into classified work and the classified cloud is where Pentagon does its fighting. So they've been involved with lethal operations in some way for more than a year. What I think is different is he had these red lines and as he is trying to uphold them, tech workers in other companies are really paying note now.
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Katrina, ethics are so central to this program. And I'm curious how defense officials addressed those ethics of ceding life or death decision making to machines, to artificial intelligence.
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They would argue, I think very current now to the operations that are using AI tools against Iran, that humans are still making the decisions. But in a very interesting presentation by the commander of US forces just this week, they've made clear that they've hit 5,500 targets. That speed is exactly why they want AI and that scope. And the Pentagon has had to work very hard thinking through precision. The claim, of course, is that U.S. weapons are the most precise in the world, but where you decide to put them, that is where America has had problems and the scale at which it's shooting at areas where we know civilians are present because CENTCOM is warning civilians to stay home, telling them to stay away from ports. There is a margin of error. There's a decision to accept or not accept a certain amount of collateral damage. They haven't made public what margin they set on that collateral damage. But these are key ethical decisions. And the targeting process is a multi stage effort where people feed in and eventually a commander makes a decision to sign off. But as you involve AI, that process speeds up the decision making. Time is reduced and fears for things like automation bias or the algorithms themselves going wrong, hallucinating or drifting algorithms tend to naturally get worse over time. All of that has really yet to be worked out. Now the US has got a policy for that. It's a directive. Some people to me frame it more as a process than a rule. But it does say that there needs to be human judgment over the appropriate use of force. Well, that's supervision. That's not necessarily making a decision. And so I think from all the people I've spoken to, that role, that human role is reducing. And CENTCOM has been particularly proud this week the commander to say that AI is helping them reduce operations decisions from what used to be days and hours to seconds after the break.
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How good is this technology really? We hear about one test where things went awry and we dig into how lawmakers are responding. Support for the show comes from Public, the investing platform for those who take it seriously. On Public you can build a multi asset portfolio of stocks, bonds, options, crypto and now generated assets which allow you to turn any idea into an investable index. With AI it all starts with your prompt. From renewable energy companies with high free cash flow to semiconductor suppliers growing revenue over 20% year over year, you can literally type any prompt and put the AI to work. It screens thousands of stocks, builds a one of a kind index and lets you back test it against the S&P 500. Then you can invest in a few clicks. Generated assets are like ETFs with infinite possibilities, completely customizable and based on your thesis, not someone else's. Go to public.com podcast and earn an uncapped 1% bonus when you transfer your portfolio. That's public.com podcast paid for by Public Investing Brokerage Services by Open to the Public Investing Inc. Member FINRA and SIPC Advisory Services by Public Advisors llc. SEC Registered Advisor Generated Assets is an interactive analysis tool. Output is for informational purposes only and is not an investment recommendation or advice. Complete Disclosures available at public.comdisclosures Ryan Reynolds here from Mint Mobile. I don't know if you knew this, but anyone can get the same Premium Wireless for $15 a month plan that I've been enjoying. It's not just for celebrities. So do like I did and have one of your assistant's assistants switch you to Mint Mobile today. I'm told it's super easy to do.
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Charmin Ultra Soft Smooth hair Charmin Ultra Soft Smooth Hair has the same softness you love now with weighty edges that tear better than the leading one Ply brand Enjoy the go with Charmin. Proponents of AI enabled weapons say the technology can improve decision making on the battlefield and put fewer troops at risk, which could save lives. Its promise of speed makes it imperative to national security experts who see it as essential in the widening AI arms race with China. But Bloomberg's Katrina Manson points out it also comes with risks.
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AI is this fundamentally unpredictable black box technology. So it's brilliant at bringing a lot of data to bear. It just might be the wrong data and it might be organized in the wrong way. And if you're not giving enough time to checking, or if you don't understand where it can make mistakes and you put it in too critical a place in your own system, you've made yourself incredibly fallible. Now, from the US Perspective, that brings a couple of problems. One is you may end up killing civilians, which is against US policy. Certainly deliberate targeting, inadvertent targeting under the rule of law, has to be proportionate. But the second thing is you can also hurt your own troops and allied troops. And the US has a history of grappling with what are called friendly fire incidents. And AI was meant to help clear up this kind of Klaus Witzian idea of the fog of war. One of the ways they've integrated AI into the battlefield picture is through the system that emerges from Project Maven, called Maven Smart System. For most of us, it's a really basic idea. It's essentially just a digital map. It's Google Maps for war. Really hard for the military to create that because they have data in all sorts of places. They haven't labeled their data. They have spent the last 10 years really getting their equipment, their tech, their connectivity up to scale where something like this could work. But then integrating AI into it is really down to what checks they make for it. The algorithms themselves. I found cases where the quality of the algorithm, the ability of the algorithm to detect what it's meant to be identifying, can change if the weather changes. If you move an algorithm from a hot area to a green area, picking up something as simple as a truck or a tank, and distinguishing between a man or a woman or a child, which is really critical to those life and death decisions. And the rules under which the US Military operates really isn't at the stage that you can give that over to algorithms. So the risk is, if they are not sufficiently tire kicking their own algorithms when it comes to computer vision, or when it comes to using LLMs and chatbots to speed up their processes and analyze data, you could be going in the wrong direction for quite some time before you notice it.
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Katrina, I wonder if you could tell us a story of what happens when this technology doesn't work as it's intended to. When you write about a test that took place back in June of 2025, maybe you could just walk us through what happened then and what lessons we can draw from how that unintended result could portend difficulties down the road.
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The teams behind Maven had made computer vision, and then this was the next iteration. This is for a program called Replicator. So it would be to identify a target, and then the drone could go after the target and then select it, identify it, and explode. And developing automatic target recognition is one thing that relies on creating algorithms that can find things. The other is this swarming technology coordinating between drones. Of course, they were testing this. It's expected to fail. That's why they do it in test conditions. And the aim was to deliver multiple thousands of drones by a certain date. And two months before that date, there was a test in California of some drone boats. And in this one experiment, the drone was towed out to sea before it was to be switched into autonomy mode. That in itself was meant to be a safety measure. What happened was, inadvertently, a command was sent from the dock to the drone boat. And when the drone boat was activated into autonomy mode, without anyone realizing it, it started trying to get away from the captain who was towing it. The boat started accelerating, decelerating multiple times between 0 and 6 knots at pace semicircling action, the rope goes taut and the captain is capsized. At that point, he's in the water, and then the drone boat turns and comes toward him. That's a very dangerous moment because the rope could strangle him underwater. He could be submerged. There's a run, runaway boat coming for him. A third boat was able to intervene and save him, and he was okay. And what actually happened in the investigation that ensued was that someone had mistakenly sent what's called a zero command just by pressing enter on a command line, deployed the boat into autonomy mode, and then all of this ensued. So they fixed it. This is a very early stage of testing. They're meant to be putting explosives on these boats. They're meant for these boats to be all cooperating together and able to defend an island such as Taiwan in the event of an invasion. And I think it showed that the tech is really hard to deliver and just simply not ready.
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In a statement for Katrina's book, a Navy spokesperson said that safety is always their top priority, that they have backup systems to prevent danger, and the lessons they learn during these events drive improvements in their systems. Mike, these conversations about ethics are happening among the Defense Department and these private companies. Where are lawmakers? Is Congress showcasing any interest in engaging with this subject?
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Showcasing is a good word because they do like to showcase their interest. But actually advancing a proposal that would codify some regulation or law, even on how AI is deployed in warfare, we are a long way from that. There's discussion of attaching some sort of amendment to the annual defense authorization measure, which every year usually gets caught up in the fight of the moment. And that could be where this ultimately ends up. But it's unclear whether there would be enough consensus between both parties to really come up with language they all could agree on and that the Trump administration would not try to torpedo somehow itself. Remember, the tech industry, a lot of the big tech companies have really moved to align themselves with President Donald Trump in a lot of different ways. And it's difficult for them and a lot of other business fronts to challenge the president, including on this.
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Katrina. I want to ask you lastly just about how much the horses is out of the barn here. I think there'll be a lot of people listening to this who will be impressed by how far this field has advanced, that is AI integration into warfare, and may wonder if there's any recourse or anything that they can do, they as citizens, to slow down this process.
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People talk about a costless war. We've already seen that from the US Side alone, it's not a costless war. AI is meant to give you a riskless war. And probably where civilians and citizens come involved, are trying to understand the contours of is there such a thing as a riskless war and who is harmed by that? And if in any way AI isn't saving civilians or even there are misfires that involve AI, then really you have to re examine if it makes war more likely. That in itself is a change for the way that the US had maybe been thinking about conducting wars under President Trump himself, who of course is the main political leader who has said, I don't want any more wars.
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Katrina Manson's book Project a Marine Colonel, His Team and the dawn of AI Warfare comes out later this month. This is the Big Take from Bloomberg News. I'm David Gura. To get more from the Big Take and unlimited access to all of bloomberg.com, subscribe today@bloomberg.com podcastoffer if you like this episode, make sure to follow and review the Big Take. Wherever you listen to podcasts, it helps people find the show. Thanks for listening. We'll be back tomorrow.
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Date: March 12, 2026
Host: David Gura (Bloomberg News)
Guests: Katrina Manson (National Security & Tech Reporter), Mike Shepard (Senior Editor)
In this episode, the Big Take explores the role of artificial intelligence (AI) in the rapidly escalating Iran war, with a focus on how the Pentagon is integrating AI into its military strategies and the complex ethical, political, and technical challenges that arise. The discussion is driven by the fallout between the Pentagon and AI company Anthropic, the growing arms race with China, and a critical look at recent AI-enabled incidents within the Department of Defense.
Escalation: The Iran war intensifies, with US, Israeli, and Iranian forces exchanging advanced strikes (01:41).
AI-enabled Warfare: The US launched over 1,000 strikes in 24 hours—double the opening of the Iraq war in 2003—enabled by AI to rapidly process and execute targeting decisions (02:13).
"The decision to wage a campaign like this is intimately linked to how remotely the US can pursue this war."
— Katrina Manson, 02:51
Severed Ties: The Pentagon ended its contract with Anthropic, identifying the company as a supply chain risk (03:19).
Anthropic’s Red Lines: Anthropic refused to allow their AI, Claude, to be used for autonomous lethal decisions or mass domestic surveillance (03:43).
"Anthropic, which is best known for its CLAUDE AI tool, wanted assurances from the US Government that its technology would not make lethal decisions on its own or help to conduct mass surveillance on Americans."
— David Gura, 03:43
OpenAI Steps In: OpenAI began collaboration with the Department of Defense after Anthropic’s exit, intensifying the debate on tech’s role in U.S. military campaigns (03:53).
Accelerated Adoption: Defense Secretary Pete Hegseth’s directive encourages widespread use of AI in the military, rejecting any provider-imposed use restrictions (05:27).
Private Sector Partnerships: The military is increasingly reliant on commercial technology firms for cutting-edge AI (Project Maven, Palantir, Amazon, Microsoft), moving beyond traditional defense contractors (08:14).
"They need commercial companies and so when Project Maven happened, for the first time really, they were going outside the traditional primes… looking at companies like Google, Microsoft and Amazon."
— Katrina Manson, 08:14
Worker Resistance: Google’s Project Maven involvement prompted employee backlash in 2018; now, Anthropic’s stance is signaling to other tech workforces about ethical boundaries (08:53).
Speed Versus Oversight: AI dramatically accelerates mission planning and targeting—from days or hours to seconds (10:03).
Ethics of Automation: While policies state humans remain 'in the loop,' oversight is shrinking, increasing concerns over automation bias, collateral damage, and unchecked error margins (10:03).
"As you involve AI, that process speeds up the decision making… fears for things like automation bias… tend to naturally get worse over time. All of that has yet to be worked out."
— Katrina Manson, 10:49
Systemic Vulnerabilities: AI’s unpredictability—especially in "life and death decisions"—poses risks for both civilians and allied troops (14:54).
"AI is this fundamentally unpredictable black box technology. So it's brilliant at bringing a lot of data to bear. It just might be the wrong data and it might be organized in the wrong way."
— Katrina Manson, 14:54
Project Maven and ‘Google Maps for War’: Integration of AI with battlefield information is akin to a digital map, but problems with data quality, labeling, and algorithm robustness persist (15:38).
Failure in Autonomy: During a June 2025 test for the Replicator program, a drone boat misinterpreted a command, nearly injuring a captain and demonstrating the dangers of operational missteps (17:23).
"Inadvertently, a command was sent from the dock… The boat started accelerating… the captain is capsized. At that point, he's in the water, and then the drone boat turns and comes toward him. That's a very dangerous moment..."
— Katrina Manson, 17:23
Lesson: Such incidents, even in controlled settings, highlight how nascent and risky battlefield AI remains (19:23).
Regulation Remains Distant: While lawmakers discuss AI in warfare, meaningful legislation or oversight is still far off (19:57).
"They do like to showcase their interest. But actually advancing a proposal to codify… how AI is deployed in warfare, we are a long way from that."
— Mike Shepard, 19:57
Industry–Government Ties: Tech companies are increasingly aligned with political leadership, blurring regulatory independence (20:45).
The ‘Costless’ War Myth: As wars become increasingly automated, the public may misunderstand the very real human costs that persist or grow with AI-enabled conflict (21:21).
Civic Engagement: Manson suggests citizens question whether true “riskless war” is possible and who is harmed if AI fails or makes war easier to pursue (21:21).
"People talk about a costless war… if in any way AI isn't saving civilians or even there are misfires that involve AI, then you really have to re-examine if it makes war more likely."
— Katrina Manson, 21:21
On AI Speed in Targeting:
"They've hit 5,500 targets. That speed is exactly why they want AI... CENTCOM has been particularly proud this week to say that AI is helping them reduce operational decisions from what used to be days and hours to seconds."
— Katrina Manson, 10:03
On AI's Unpredictability:
"You could be going in the wrong direction for quite some time before you notice it."
— Katrina Manson, 16:53
On Public Engagement:
"If in any way AI isn't saving civilians or even there are misfires that involve AI, then you really have to re-examine if it makes war more likely."
— Katrina Manson, 21:21
This episode unmasks the Pentagon’s internal and external struggle to responsibly blend AI into its war machine at a critical historical moment. As the Iran conflict rages, the US is testing the limits of what AI can do—and what it should be allowed to do. Safety red lines are fraying, both inside companies like Anthropic and across government. Real-world failures, like the drone boat mishap, underscore that the technology is not mature—and that the consequences could be catastrophic. Meanwhile, lawmakers lag desperately behind the technology’s pace, failing to craft meaningful regulations. Ultimately, the episode cautions that the public, not just the government or Silicon Valley, must engage with what it means to wage "AI war" and face hard questions about risk, oversight, and what kind of world this emerging technology is creating.
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