All right, Kevin, let's get into the biggest news of the week, which is the war in Iran. Specifically, we want to talk about what we know about how AI is being used in this fight.
Yeah. And I think the reason to talk about this is not just because it's happening. It's the biggest story in the world, but also because I think this is really a turning point in the use of AI in the military. We've been hearing for years and reading science fiction books and listening to people talk about the use of AI in military applications, but now I think we are starting to see exactly how these tools are being used on the battlefield and what kind of effects they might be having. We are, and I'll say up top that anytime you're talking about the use of technology in war, there is always the risk that you are just passing along propaganda, right? Because both the military and the contractors have a vested interest in telling you, hey, we have some real g-whiz new stuff and it's totally changing the game, right? Everybody has an incentive to tell you that. And yet, as you and I have dug into it, we do believe that there are some notable ways that AI are being used and I think it is worth mentioning them. If for no other reason than I think it's been the experience in the United States over the past couple of decades that tools that are deployed abroad during times of war sometimes come back home after the war and wind up being used against American citizens.
Yeah. So I think we should tease apart a few things here. One of which is like let's talk about how the actual AI tools are being used by the military, what the tools are, what the kind of ramifications of using them this way are. We should talk about how Claude in particular seems to be a key part of the war in Iran so far and at least from what we know seems to be behind a lot of the strategic decisions and operations that the military is making. And finally about how this conflict is or isn't going to reshape the future of AI by doing things like taking aim at data centers, by interrupting the supply chains of things like semiconductor materials, all the larger questions about how this conflict is playing out. And before we get into it, let's briefly do our disclosures. My fiance works at Anthropic.
And I work for the New York Times, which is suing OpenAI, Perplexity, and Microsoft over alleged copyright violations. Okay, Kevin. So, where should we begin? Well, let's talk about how AI is actually being used in the war in Iran and what we know about the actual deployment of this stuff. Casey, what do we know?
Yeah. So, I read a great overview this week in the Wall Street Journal by Daniel Michaels and Dove Lieber, who goes into good detail about what we know about how the United States and the Israeli militaries are using AI. They're upfront about the fact that the military is trying to keep a lot of this secret. They are not apparently going into a lot of detail, but there are some things that we know. One is that Israeli intelligence for years had been monitoring traffic cameras in Tehran that they had hacked into and also eavesdropped on senior officials' communications. And this is a big theme, Kevin, that runs through all of the coverage of AI in the war in Iran, which is that the military is saying that it is very effective, as you would probably imagine, at processing large quantities of information.
Yeah. So basically, you've got all this data coming at you if you're, you know, running a military in the year 2026. You've got data from drones and sensors and maybe security cameras that you've found a way into. And you can kind of use AI to process all of that to put it onto some kind of like a real-time dashboard so that you can just like open a screen and kind of see where all your supplies and all your troops and where all the enemy combatants are and like use it to sort of make sense of this wave of information that is coming at you every day.
Yeah. You know, recently on the show, as we've been talking about the conflict between Anthropic and the Pentagon, we've been talking about the potential eventually to have autonomous weapons out in the battlefield, potentially killing people without human intervention. And the big message that I'm reading in the coverage so far is we are not there yet, right? That the AI tools that are being used, we're seeing them in fields like intelligence, mission planning, logistics, actually pretty far away from the battlefield doing things like helping to find a target to send a missile at and then after an attack trying to do some kind of quick analysis to see, hey, what exactly did we hit and maybe what should our next target be? It's also really clear that what's happening in the military is what I would call like shrinking the haystacks where there's sort of these massive troves of data where it's like we have, you know, hundreds of thousands of phone calls or audio recordings or emails or intercepted traffic to Iranian websites and we can like use that AI to kind of narrow down the bits of that that might be useful to us. Because in all intelligence gathering situations since the dawn of eternity, like 99 plus percent of what you're collecting is totally useless and there have been, you know, entire divisions of humans who have been employed to like dig through all that stuff and find the stuff that's actually useful and now AI can do that pretty well.
Yeah. And military leaders are saying that there are many, many missions that just never happened because they didn't have the manpower to do exactly what you just said and now they do. And I would point out, Kevin, that again, you know, when in our whole discussion of Anthropic versus the Pentagon, we were talking about, you know, the risk of this technology being deployed against Americans and how effective that could be in, you know, all sorts of surveillance operations. So, I think it's important to highlight like that exact thing that we were talking about, like sort of like a bad scenario in the United States if the government was doing it to its own people is just sort of absolutely happening right now in Iran.
Yeah. And we probably won't know the extent to which it's happening because most of it is classified and, you know, nobody in the military wants to like give away their secrets to any potential adversaries. But my best guess and from the people that I've talked to who have been working on this stuff is that this is happening pretty rapidly, that we are seeing many, many divisions of the military that are essentially using this stuff every day.
Yes. Now one question that is coming up a lot is to what extent, if any, is the military starting to offload decisions to AI, right? Is it the case that there is some military commander that is typing into a chatbot, hey, should I send the missile here or there? The public statements are that they are not doing this, right? They are sort of taking care to say no, like humans are in the loop here, we are relying on human judgment. But there are other experts that are saying, you know, at some point if you're going to be consulting with a chatbot and the chatbot is getting smarter and smarter, before too long, it's probably not going to feel very different from the AI actually just making the decision for where to shoot a missile.
Yeah, I think that's a really good point. I think there is a difference between a fully autonomous weapon that can sort of do everything from selecting the target to like firing the weapon all on its own with no humans in the loop. But I think what you're talking about is sort of a system that can do everything except fire the weapon. It can sort of select the target. It can tell you the right timing. It can like identify all the objects in the surveillance footage. And it can kind of give the military officials the confidence they need to go ahead and push the button. And there's some worry that this is starting to happen with the help or the encouragement of AI. There was a missile strike in Iran that hit an elementary school the other day and according to Iranian officials killed over 175 people, mostly children. Horrible thing. And people have been wondering if that was related to Claude or some other AI system telling the military maybe erroneously that this was a legitimate target. When now we should say that particular incident is still under investigation and initial reports from the military have said that it was unlikely that AI was responsible in that case. But I think this is the kind of thing you're going to start seeing more and more of is like when there is an attack that, you know, kills civilians or doesn't hit its intended target, people are going to be asking, oh, was that a human who made that mistake or was that an AI system?
Yeah. And I have to imagine, Kevin, that there is just going to be more and more pressure within the military to more fully defer these decisions to AI systems, right? Because at some point there will at least be some contingent in the military saying these systems are more trustworthy, they can make decisions faster and let's do it. So I think that's just something that we need to be very much on guard for.
Yeah. So that is what we know about how AI systems have been deployed so far. But Kevin, as you mentioned, there's also been a lot of discussion about, well, what some particular models may or may not be doing during the war.
Yeah. And I think Claude and Anthropic have come up a lot in recent weeks for obvious reasons. They had this big fight with the Pentagon. But it's also the case that right now in this war in Iran, Claude is the only AI model that has actually been deployed inside classified military systems. So to the extent that AI is having an effect in Iran, it is probably Claude.
Yes. And the Washington Post had a story about AI and the war in which they said that Claude was so essential to operations that if for some reason Anthropic said, hey, we want you to stop using Claude, the military would push back and say we're actually going to force you to continue to use this product. So just again the continued strangeness of the situation. The Pentagon has now formally declared Anthropic to be a supply chain risk. This week Anthropic sued over that.
Yeah. And there's also been a lot of reporting coming out over the past week or two about the actual ways that Claude is being used and deployed in the military. There's been some reporting on this system built by Palantir called Maven Smart System, which from what I can tell is kind of a real-time dashboard for intelligence that basically allows you to pull in a bunch of drone footage and sensor data and track a bunch of, you know, supplies and troop movements and things like that. And by the way, this is the system that caused a huge controversy at Google in the late 2010s. And, you know, Google's like quit over this. They did not want the company involved with Project Maven. And eventually Google dropped the contract. When they did, Palantir stepped in and eventually brought on Claude. Right. And so Claude has been integrated into Maven Smart System since 2024.
And the reporting that I've seen over the past week, including in this article in the Washington Post, said that this combination of the Maven Smart System built by Palantir and Claude has already suggested hundreds of targets, issued precise location coordinates, and prioritized those targets according to importance. And according to this same article, it says that the use of Maven and Claude has turned weeks-long battle planning into real-time operations. So, this is not just like a kind of tool that people in the military are using for handling like routine office work. This is actually sort of a core part of their strategic decision-making process. Now, Kevin, do you know if this is like a specialized model of Claude? Again, I'm thinking back to our conversation with Amanda Askell where she talked about all these efforts to make sure that, you know, Claude is really good. I'm sort of imagining that version of Claude being told like, hey, analyze all this footage and decide like where to send a missile to kill a bunch of people. It's hard for me to imagine that version of Claude being like, yeah, yes, sir, right away. Right. So, do we understand at all how that is working?
So my understanding is that it is largely the same model that consumers and enterprises would use. But that there may be some additional fine-tuning to make it work inside these classified systems on these sort of military applications. That it may sort of refuse different prompts or fewer prompts than a model aimed at consumers. And that there may be some additional kind of changes around the edges, but that it's basically the same Claude that you and I have.
Hmm. I see. Well, so this appears to be a very temporary phenomenon. We know that OpenAI has signed a deal with the Pentagon and presumably its systems will be onboarded onto classified defense systems soon. Gemini was approved for non-classified uses at the Pentagon. So I think pretty soon the Pentagon is to have more options to choose from as it deploys these systems. So that is how AI is being used offensively by the United States and Israel, Kevin. But we should also talk about what Iran is doing offensively against some of these AI systems.
Yeah, this is a part that I have not spent as much time looking into. So tell me what you're seeing.
Well, so as you know, there's been this huge buildout of AI infrastructure throughout the Middle East over the past several years. We've seen these multi-billion dollar projects being signed and built in Saudi Arabia and United Arab Emirates and Qatar. And these deals involve basically all of the big American tech giants, Amazon, Microsoft and Google. And I would say there's sort of like two major pieces of infrastructure that are relevant here. One is data centers, right, which are, you know, being used to run AI systems and also just provide basic cloud hosting and storage services to all sorts of companies. And then you have fiber optic cables which connect those data centers to the rest of the world. So let's maybe talk about the data centers first. Sure. So, the Guardian reported that on the morning of March 1st, which was the day after the initial US attacks in Iran, Iran responded by striking a couple of Amazon data centers in the UAE. And they also damaged a third one in Bahrain. And in the immediate aftermath of that, people in those countries were opening up their phones and they couldn't check their bank balances, they couldn't order a taxi. It seems like a lot of services in those countries were being hosted on AWS and they just didn't have access to those services anymore. Afterwards, Iran put out a statement that said that they had gone after the data centers to identify the role that they played in supporting the enemy's military and intelligence activities.
That's so interesting. So they were basically targeting data centers rather than say troops because they thought it could actually be more disruptive if it turned out that the US or Israel or any of the other allied nations were running their services on data centers located in the Middle East.
Yeah. Well, I mean and also like data centers are a great target. Like they're just sitting there. They don't have any defenses, right? So you can just send a few missiles over there and do an asymmetric amount of damage. And so now Kevin, people are starting to question the logic of doing all these multi-billion dollar deals in the Middle East. They're saying, hey, should this really be a linchpin of global AI infrastructure if it's just kind of a rough neighborhood and all of the investments that you're going to build there are just going to be kind of perpetually at risk?
Yeah, I think that's a really interesting sort of tactical shift that just speaks to how central all of this AI stuff has become in military conflict. And then you have all these other risks of disruptions to the supply chain. And right now there are lots of ships stuck that can't get through the Strait of Hormuz because it's been blocked off. And we now have people and companies saying that some of the raw materials that you need to make things like semiconductors might be delayed for weeks or months or however long this conflict lasts. And that prices might go up and it might get harder for companies to build new data centers here in the US. So all these ripple effects we're starting to see are like downstream from the fact that we're at war with Iran.
So that's what's going on with the data center infrastructure. Kevin, you're also probably wondering what is going on with these undersea cables. So there are very important fiber optic cables that run through the Strait of Hormuz that are responsible for transporting internet traffic from that region to the rest of the world. As of press time, as we record this, these lines have not been attacked or disrupted, but everyone is keeping a really close eye on it because were they to be disrupted, there is just simply no obvious way to fix them in the middle of a live war. Casey, how does this all make you feel that AI is playing such an important and central role in an ongoing war in Iran?
I mean, this to me just feels like the frog is being boiled, right? Like when I think of all of the potential violent uses of AI, data analysis is not among those that gets me most nervous. Although of course I do have concerns about, you know, domestic surveillance. I also know how rapidly these systems are advancing. I know the pressures that are quite apparent in our military to use AI for ever more things. I worry that there aren't going to be appropriate safeguards on those things. And so, yeah, I just have a high degree of concern about where all of this is going. I'm open to the idea that AI systems could be used to wage war more safely and to maybe even prevent casualties, but I am not sure that we have built systems that will actually do that.
Yeah. And I would just say like I keep thinking about how all of the companies that are building frontier AI systems today at one point in their existence had decided that they didn't want their stuff being used by the military. You know, back in 2014 when DeepMind was a sort of little known AI startup in London, they sold themselves to Google. And one of the major sticking points in those negotiations, one of the reasons they sold to Google and not what became Meta and was at the time Facebook was that Google had allowed them to have this prohibition on using their technology for military applications or surveillance.
As recently as a couple of years ago, Google's AI principles said that we are not going to allow our technology to be used for the military. And in 2025, it quietly took that language out. OpenAI, same thing. They had language in their terms prohibiting their models from being used for military applications. They took that language out quietly in 2024. Meta, same thing. Anthropic, interestingly, is the one sort of frontier AI lab that never had an explicit prohibition on military applications, but they did have a bunch of language in their original terms that they have amended to make it more possible for the military to use this stuff. And so like I understand strategically why you would make the decision to sell your AI tools to the US military, but I just don't want us to forget that like all of these companies were run by people who at one point thought this was all a bad idea to be selling these very advanced AI tools to the military. And then they changed their minds and they did that because of some combination of pressure or just maybe market opportunity to get these big military contracts. But they did at one point have a principle that involved we don't want our stuff being used to kill people. And I would like them to at least reflect on the fact that that has changed.
Yes. And for everyone else, the next time one of these companies tells you about some unshakable principle that is the foundation that the entire company is built on, it should make you wonder whether that can hold up to pressure as well.
So Kevin, I feel like there is this new genre of blogs and social media posts all devoted to the idea that using AI is making people feel completely exhausted.
There's a spectrum and it starts at exhausted and it goes all the way to insane. Sidon Carr, who's an engineer who builds tools for AI agents, wrote a blog post that I saw all over social media recently called AI fatigue is real and nobody talks about it. And he said that on one hand he felt like he'd had the most productive quarter of his entire life as he uses all these new agentic coding tools, but on the other hand he said he had felt more drained than ever before in his career.
Yeah, I think people are starting to sort of use these tools more and come to grips with not only the effect it's having on their productivity, but also like on their brains and on their ability to kind of make sense of how quickly things are shifting. I really liked this essay that a venture capitalist wrote a few weeks ago about what he called token anxiety, which was this feeling that like if you don't have a bunch of, you know, cloud code agents like running parallel tasks for you while you sleep, like you're feeling like you're missing out. And people at dinner parties in San Francisco are now talking about bragging about how many agents they have running at all times. So there's like something psychological happening to the people who are using this stuff a lot at work.
Absolutely. And recently we have begun to see some actual empirical research on the subject. So last month researchers at UC Berkeley published some findings in the Harvard Business Review from an eight-month study observing workers at one 200-person tech company. And they found that AI was just making work a lot more intense. Workers were having to multitask a lot more. They felt like if they were not using a lot of AI tools, they were not keeping up with expectations and that they used to have little breaks during the day where, you know, you go to the water cooler and talk about, you know, what's going to happen on Survivor this week. Well, that doesn't exist anymore, at least not at this company. And then last week, a group of researchers at BCG shared some similar findings in the Harvard Business Review. And this one really caught our eye because they found that under certain conditions, workers are experiencing what the researchers are calling AI brain fry.
And to be clear, that is different than AI brain rocked, which is what you get on TikTok when you start looking at videos of Ballerina Cappuccino.
That's right. You know, and actually they thought that Emmanuel Macron might have this, but that turned out to be AI French fry. So anyways, here's what AI brain fry is, Kevin. They're defining it as mental fatigue from excessive use or oversight of AI tools beyond one's cognitive capacity, which I think is kind of a funny idea. It's almost like you got a new coworker and they're really, really smart and it's sucking your life force out of your body. So, we want to know more about this study because I think it gives shape to a conversation that we're seeing rippling out across the economy as more and more managers are telling their workers to start using AI tools. It is clear that not all is well out there. People are starting to feel kind of bad and they're maybe going to be less productive and likely to leave their jobs as a result. So to learn more about the findings in this study, we've invited the lead author, Julie Bedard. Julie is a managing director and partner at Boston Consulting Group as well as a fellow at the Henderson Institute, which is an internal research group and think tank at BCG. So let's bring her in. Let's do it. Let's get fried. Julie Bedard, welcome to Hard Fork.
Thank you. So, thanks for having me.
So, let's talk about the study. You surveyed 1,488 workers in January of this year from all different disciplines, lots of different companies. What kind of questions did you ask these workers?
Yeah, we asked them all kinds of questions around how they use AI, how they feel at work, you know, traditional burnout metrics. We asked some, you know, sort of proxies for cognitive ability. And we did throw in a question about AI brain fry. We said specifically like what do you think about this thing that could be AI brain fry? Like are you feeling that?
And tell us how you define AI brain fry and what the survey results told you about it.
We defined it as really like a type of cognitive strain. So we said it was mental fatigue. It was related to excessive use of interaction with or oversight of AI and it was about being beyond one's cognitive ability. So it's sort of like I'm using the tool but it feels beyond my ability to process it. So 14% of people who use AI said that they felt this and I was especially surprised by the extent to which they told us about it. We asked, you know, free-ended like just tell us what is this thing? What does it show up? How does it feel to you? And people wrote a lot, right? Like they wrote all these things about feels like I have 12 browser tabs open in my head or it feels like I'm working so hard to manage the tools. I'm actually not really doing the work. Like I'm not actually managing what I'm supposed to be doing.
I thought this was so interesting because on paper, if you told me, hey, we're going to give you a brilliant new assistant. They can answer all of your questions. They can do many of the tasks that you prompt it to do. That would sound very exciting. You know, sometimes I think what would it be like to have like a really great podcast co-host? You know, somebody kind of came in really prepared, asked a lot of great questions, had a great energy.
You'll never know. And I'll never know.
Okay. But some of these people at work are now having that experience. But what you're saying is that that is not an energizing thing for them. It's draining them in some way. So what do you think is the mechanism by which people are coming to feel so exhausted by working with these systems?
Yeah. Well, I do think it's particular to these two things that we found, which is the oversight of the tools and the intensification of work due to AI. And what people reported specifically is they put in more mental effort, they felt more fatigue and they felt information overload. And, you know, we need more research, right? Like this is new and we're learning. But my hypothesis, right, from working with a lot of different companies on this kind of thing is it is fun and exciting combined with we feel more pressure. Everybody's talking about AI, AI, productivity, right? And I think it's just nature to okay, one more thing. Let me just sort of try this out, see what I can do. And we're not reentering on like what was I actually trying to achieve today, right? We're not getting focused on some of the most important aspects of our work.
Yeah. I'm curious how much you think this really boils down to fear. Because when I talk to people who are anxious about using AI at work, they sort of circle around this issue that like maybe it's materializing as burnout or feelings of overwhelm, but like at its core, what they're nervous about is that we now have these systems that can do parts of their job and they're worried about losing their jobs. And so did anything in your study sort of get to any of the economic or sort of survival anxiety that these workers might have been feeling that might have been registering to them as burnout but deeper were something else?
Yeah. So this is probably a good time to separate the two because the brain fry is the cognitive piece. Burnout is, you know, physical and mental exhaustion. It's more emotional. It's more about how I feel about work and, you know, do I feel like I'm doing a good job at work? Burnout, we did not find a correlation with brain fry. So, I just want to be really like clear. It was very interesting. I thought we would, we did not. Brain fry is distinct. And then what we found is actually you could use AI to reduce burnout. So, if you use AI for more repetitive tasks, you actually were reducing burnout. So, you're actually making workers feel like better at work. And that is something that's really positive that we need to lean into. So there's a lot of nuance. Maybe the last thing I would say is we did look at, you know, how positive or negative you feel, but typically the people who are afraid are not the people who are doing heavy oversight work in my experience, right? So they're sort of the people who are, you know, leveraging it more like a search tool, right? They're not necessarily getting up that learning curve to more of the intensive interactions.
Mhm. In your study, you found that people in certain industries tended to experience AI brain fry more frequently. I was struck by marketing seems to be the place where people are feeling it the most. And people in areas like management and law and compliance reported significantly less brain fry. Do you have a theory on why that is?
Yeah, so the short answer is unfortunately our survey at least scientifically was not designed to answer that question. But I have my theories based on other work that I've done. And, you know, three years ago I worked with some of the models to try to predict skill disruption. I was trying to figure out like which jobs will change the most. And one of the jobs that changed the most from a skill perspective was marketing manager. A marketing manager was 90% disrupted from a skill perspective. So that's sort of the first fundamental piece about marketing is like they've tended to adopt and it's a really different way of working because of the power of the tools. The next thing if I really just think about like what is brain fry like, it's about the iteration, it's about the oversight. A lot of marketing lends itself to that. Like in the field we see stories of folks who are doing image creation, they're doing synthetic consumer panels, right? They're spinning up a bunch of campaigns at the same time. And it really lends itself to that definition of like when do they know they're done? When do they know the image is ready? Like have they defined those success thresholds for themselves? I'm guessing they haven't yet, right? Like they haven't figured out how do you do all the things to the right level of quality based on the outcome that you're trying to drive for.
It makes sense to me that like the more your job is changing, the more kind of vertigo you're going to be experiencing as these new tools are introduced into your workplace. You know, Kevin, you just observed that managers seem to be experiencing this less. One of my theories was that well, the reason is because they're already used to overseeing a bunch of digital abstractions since they're human employees, right? They're mostly just sending them Slack messages and sending them emails, you know, hopefully meeting in person, you know, fairly regularly. But I think if you're a manager, you've already been used to sort of overseeing a bunch of stuff and those people just sort of may have skills that people who have not yet been in management roles don't have. I think there's something to that. And I also wonder, Julie, if you think there's anything that is sort of inherently isolating about these tools. One thing that I found with using AI for my own work is like it's a single-player video game, right? You're going back and forth with a machine. Very rarely am I in a room with other people using AI with them. And I wonder if part of the brain fry is sort of this siloing effect that these tools tend to have in the workplace where it's like everyone is chatting with their chatbots and their agents and no one is talking to each other.
I'm glad you brought that up, Kevin, because back to this point around there's ways to use AI that actually reduce burnout. The people who were using it for repetitive tasks, they actually were doing those types of things. Like we found that they felt more socially connected at work. And so it's interesting like in all
The companies that I go to, I do various types of, you know, AI enablement and workshops. And one of the questions that I always get a lot of engagement on is what could you use AI for, which is like the three worst things on your to-do list, like the procrastination things, like the things you really wait and do. I mean, people love to talk about using AI for those. And my hypothesis is sometimes that's probably the repetitive work. And when you use it for that type of repetitive work, you actually reinvest the time in things that give you energy. So more work needs to be done. But I think I've seen that a bit in the field and that's what our data would suggest as well.
I want to ask about the three-tool cliff, which was a funny part of your study. Basically, you found that the sort of number of AI tools that people are using at work has some sort of bearing on their productivity or their feelings of productivity. And that actually when you switch from using three to four AI tools at work, there's something that happens where you all of a sudden start experiencing these things as not like a productivity enhancer but actually just more of a stressful thing. Do you have a theory on why that is or why there seems to be this threshold? Classically, multitasking is not very productive, right? Like we all are, you know, seduced by the idea that we can do more and more and more.
Casey's playing right now.
So yeah. No, I think multitasking is part of that. But it's back to this point of like I'm overseeing more things, like I'm actually doing more things. I'm starting more things. I'm stopping more things. I have more output to govern. You know, advice for leaders and managers are to help people understand this. Like one of the things I'd love to see is AI fluency right now mostly was defined by technical skills. Maybe in the last six to nine months we've started to talk about the human skills that persist. I actually think cognitive sort of health should be part of defining AI fluency as we go forward. So both again like individuals like I can start to work differently with the tools but also again managers and leaders can help protect against that.
Let me ask one objection that some people might have to the research. You work for a consultancy. Consultants have an interest in making AI seem difficult so that companies will hire them to help manage it. Is there any chance that we're over-pathologizing what is going on here or sort of, you know, giving a scary-sounding name to what might just sort of be a temporary adjustment process as people, you know, start to use AI tools in the workplace?
Yeah, I'm glad you've asked that. You know, maybe what I would say just first about kind of how I look at this and why I'm doing this research. So, I am a consultant. Yes, I do advise companies. It's sort of the bread and butter of what I do. However, I'm also a researcher and I care really deeply about the data. And what's been very hard is our clients have wanted answers. Answers that we don't necessarily have all of the playbook for because it's so new and is changing so rapidly. So I'd say just, you know, we really designed this to be a data-driven intervention. But beyond that, I think I've been for, like I said, for the last three years at the rock face. Like I've talked to more than 100 companies. I've actually trained teams myself. I've been in the room with software developers, marketers, etc., trying to use these tools. And I see that like there's something there, like there's a real strain where I'm trying to do the right thing, but something's getting in the way of me being productive with the tools and we need to redesign work hopefully and particularly within teams to do that better.
And like if you're a worker out there, if people are listening to this and saying, 'Yes, I am a worker. I am using AI tools at work. I am feeling the brain fry that you are describing.' What can they do to help themselves? What has shown itself to be effective in your experience?
Yeah. So if you're an individual worker, I think first just acknowledging that this is a risk, right? Is the first thing. The second thing is really focusing on what you're trying to achieve. It's like back to that outcome piece. I mean, I know this is really basic, but if we were very clear about we're measuring outcomes, not output, and we're trying to get to the right answer, and what are those steps to help me get there? And so, you know, from our data, we would say the things you could do is one, engage your manager. So, managers who engaged in questions, we saw brain fry go down. And I think it's about creating that sort of open dialogue about how should I use AI? When is it valuable? The other thing is to engage your team on this. So interestingly, when teams were using AI together and they had better integrated it into their workflow. So like how I hand off work to Kevin and Kevin does to Casey, we also saw brain fry go down. And you know, I don't have the data to say exactly why, but my hypothesis would be is we're not bottlenecking work in one person and we're creating actually like a much more effective system where we're getting the work done with the right outcomes together.
It seems tricky to me though because I think there is just so much thrashing around in organizations right now. I think that the amount of knowledge that any given manager or worker has about AI right now is highly variable, whether their knowledge is keeping pace with the capabilities of the latest models. That seems like an open question to me. So, I have to say like in the near term, I actually feel quite pessimistic about this. I'm sure there are going to be individual managers and teams that are like doing a great job, but at an economy-wide level, I think people are just absolutely all over the map on this.
Yeah, I think so, too. And I think it's also not clear to me that people are going to feel comfortable talking to their managers about how they're feeling about AI because I think a lot of people have these reasonably well-founded fears that like if you tell your manager like I'm using AI to do this part of my job, the manager's first thought is well going to be, well, maybe I can lay you off, right?
Maybe I don't need all these humans anymore. And I think we're seeing enough of that happening at big companies now where they're laying off big percentages of their workforce and sort of attributing that to productivity gains from AI that I think people are sort of feeling like well if I discover how to use AI for my work I'm going to keep it to my damn self.
Absolutely. Or Kevin, I think we also see the reverse of that, which is you go on social media and you see people bragging about the insane lengths that they are going to be using AI at all times to have their, you know, cloud swarms up and running and coding, you know, while they sleep. And I feel this sort of deep insecurity embedded in that, which is if I'm not out there constantly telling you how much AI I'm using, you know, I might sort of be next on the chopping block.
My reaction to that is this is why leaders play a really important role because I think Kevin your point is well taken. I think there are things individuals can do. There are absolutely things managers can do but this is about systemic redesign of work. So Casey to your point like I don't think AI brain fry is going away unless we tackle it head-on. Like I don't think this is something that we can sort of just democratize and let everybody figure it out. Although I think there are things they can do to mitigate. But I'm really interested in actually like, okay, let's rethink how we get the job done. Like, you know, we are really bad at stopping work. Is all work valuable? Like, if we had leaders engage more meaningfully in these questions, that's the work we need to do if we really want to address some of this.
Julie, I'm wondering how much you went back and looked through sort of historical precedent here. When I was researching my last book, I was doing a lot of reading about the 1970s when a bunch of manufacturing workplaces like auto plants were getting all these new automated robots to help them do things like assemble cars. And there was this whole sort of nationwide panic about this. They called it Lordstown syndrome because the first sort of GM plant to have this level of automation was in Lordstown, Ohio. And you know, Congress held hearings about this like sort of new wave of worker alienation that was happening in these blue-collar manufacturing workplaces for a lot of the same reasons that to me seem like they rhyme with at least this AI brain fry idea. Workers were just saying basically like I don't feel like a human anymore. I feel like I just push buttons and the robots do all the work. I don't talk to people at the office anymore. My managers have all these crazy productivity expectations of me. And I think what was interesting in that beyond just the parallels to what people are feeling in white-collar workplaces today was that the way that they sort of got out of that was through striking and through organizing and unionizing and getting a bigger share of the profits that these companies were making from all this productivity. So I guess I'm just wondering if you could riff on maybe some of the historical parallels before and where this may all be heading.
