A.I. Goes to War + Is ‘A.I. Brain Fry’ Real? + How Grammarly Stole Casey’s Identity
Episode
66 min
Read time
3 min
Topics
Productivity, Leadership, Marketing
AI-Generated Summary
Key Takeaways
- ✓AI in Military Targeting: Claude, integrated into Palantir's Maven Smart System since 2024, has already suggested hundreds of missile targets, issued precise location coordinates, and compressed weeks-long battle planning into real-time operations. It remains the only AI model deployed inside classified U.S. military systems. OpenAI and Google's Gemini are cleared for non-classified Pentagon use, meaning Claude's monopoly on classified systems is temporary.
- ✓"Human in the Loop" Is Eroding: Military officials publicly maintain humans retain final firing authority, but analysts warn that when AI handles target selection, timing, location coordinates, and post-strike analysis, the human role reduces to pressing a button. The elementary school strike in Iran that killed over 175 people, mostly children, prompted immediate questions about whether AI misidentified the target.
- ✓AI Brain Fry vs. Burnout: Julie Bedard's BCG study of 1,488 workers found 14% of heavy AI users experience "AI brain fry," defined as cognitive strain from excessive oversight of AI tools beyond one's processing capacity. Critically, brain fry showed no correlation with burnout — they are distinct conditions. Brain fry is cognitive overload; burnout is emotional exhaustion. Treating them as the same leads to wrong interventions.
- ✓The Three-Tool Cliff: Workers using up to three AI tools simultaneously report productivity gains, but crossing to four or more tools triggers a measurable reversal — increased stress, cognitive overload, and diminished output quality. The mechanism is classic multitasking failure compounded by output governance: more tools generate more deliverables requiring human review, creating a compounding oversight burden that exceeds cognitive capacity.
- ✓Marketing Workers Hit Hardest: Marketing managers report the highest brain fry rates across all professions surveyed, while lawyers and compliance professionals report the least. BCG's prior skill-disruption modeling found marketing manager roles were 90% disrupted by AI from a skills perspective — the highest of any tracked profession. Jobs with undefined quality thresholds, like image creation and campaign generation, create endless iteration loops that drive cognitive fatigue.
What It Covers
Kevin Roose and Casey Newton examine three converging AI stories: Claude's deployment inside classified U.S. military systems during the Iran conflict, BCG researcher Julie Bedard's findings on "AI brain fry" affecting 14% of heavy AI users, and Grammarly's unauthorized use of real journalists' identities to sell a fabricated expert-review feature.
Key Questions Answered
- •AI in Military Targeting: Claude, integrated into Palantir's Maven Smart System since 2024, has already suggested hundreds of missile targets, issued precise location coordinates, and compressed weeks-long battle planning into real-time operations. It remains the only AI model deployed inside classified U.S. military systems. OpenAI and Google's Gemini are cleared for non-classified Pentagon use, meaning Claude's monopoly on classified systems is temporary.
- •"Human in the Loop" Is Eroding: Military officials publicly maintain humans retain final firing authority, but analysts warn that when AI handles target selection, timing, location coordinates, and post-strike analysis, the human role reduces to pressing a button. The elementary school strike in Iran that killed over 175 people, mostly children, prompted immediate questions about whether AI misidentified the target.
- •AI Brain Fry vs. Burnout: Julie Bedard's BCG study of 1,488 workers found 14% of heavy AI users experience "AI brain fry," defined as cognitive strain from excessive oversight of AI tools beyond one's processing capacity. Critically, brain fry showed no correlation with burnout — they are distinct conditions. Brain fry is cognitive overload; burnout is emotional exhaustion. Treating them as the same leads to wrong interventions.
- •The Three-Tool Cliff: Workers using up to three AI tools simultaneously report productivity gains, but crossing to four or more tools triggers a measurable reversal — increased stress, cognitive overload, and diminished output quality. The mechanism is classic multitasking failure compounded by output governance: more tools generate more deliverables requiring human review, creating a compounding oversight burden that exceeds cognitive capacity.
- •Marketing Workers Hit Hardest: Marketing managers report the highest brain fry rates across all professions surveyed, while lawyers and compliance professionals report the least. BCG's prior skill-disruption modeling found marketing manager roles were 90% disrupted by AI from a skills perspective — the highest of any tracked profession. Jobs with undefined quality thresholds, like image creation and campaign generation, create endless iteration loops that drive cognitive fatigue.
- •Grammarly's Identity Exploitation Model: Grammarly's "Expert Review" feature displayed real journalists' names — including Casey Newton, Cara Swisher, and Timnit Gebru — as editorial advisors without consent, compensation, or actual involvement. The underlying model appeared to be a non-frontier version generating generic, low-quality advice. Investigative reporter Julia Angwin filed a class action complaint against Grammarly's parent company. Within days of Newton's reporting, Grammarly disabled the feature entirely.
Notable Moment
When BCG's Julie Bedard revealed that using AI for repetitive, low-value tasks — the work people procrastinate on most — actually reduced burnout and increased feelings of social connection at work, it directly contradicted the assumption that more AI use uniformly drains workers. The benefit depends entirely on which tasks AI handles.
Episode Transcript
Well, I'm having sort of a weird day. How so? Well, I woke up this morning, and I, you know, checked my social media feeds. Mhmm. And, I saw messages like the following. You're garbage, and I hope you lose your job and become homeless. God, what a waste of sperm you are. And if you have never seen a message like that before 8AM, you might not work for the New York Times. Well, I I suspect that I know what this was about, but tell the listeners what made people so mad. So my colleague Stuart Thompson and I recently published this quiz Mhmm. Which is basically a set of AI written passages next to unlabeled sort of works from from masterful human writers. Yeah. And it was sort of designed as kind of a blind taste test where you pick which one you liked better, and then it would tell you, you know, which one is generated by AI and which one was written by a human. And, Casey, people did not like this quiz. Well, what were the findings of the quiz? Well, so the the big headline finding is that, like, it's basically a coin flip. Like, slightly more people, at least so far, have preferred the AI written passages. But when you tell them that they prefer the AI written passages, they get very mad. Because they think that they are too smart to fall for AI writing. Yeah. Or they just don't like the way that the test was constructed or they just it makes them uncomfortable or they think, you know, we're we're cooked now that AI can write passable, versions of this thing. Or they just start saying, you know, oh, it's just it's because it was trained on all these books, so, obviously, it can sort of mimic them. So I think there's a lot of different emotional reactions, but, mostly, the emotional reaction has been to get mad at the people who made the quiz. I have to say you seem excited about this. Like, whenever a large group of people gets mad at you, you experience a glee that I have I rarely see in people. It's not a glee. It's just like yeah. You're right, baby. I'm Kevin Roose, a tech columnist at the New York Times. I'm Casey Newton from Platformer. And this is hardfork. This week, how AI is reshaping the war in Iran. Then researcher Julie Bedard joins us to discuss the discovery of a strange new condition they're calling AI brain fry. And finally, I was turned into an AI editor against my will by Grammarly. Here's how I stopped it. It involved overwhelming physical force. Alright, 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 …
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Books, tools, and gear mentioned in this episode
SignalCast may earn commission on purchases via these links.
Tools
by Anthropic
“Claude, integrated into Palantir's Maven Smart System since 2024, has already suggested hundreds of missile targets, issued precise location coordinates, and compressed weeks-long battle planning into real-time operations.”
by Grammarly
“Grammarly's 'Expert Review' feature displayed real journalists' names — including Casey Newton, Cara Swisher, and Timnit Gebru — as editorial advisors without consent, compensation, or actual involvement.”
by Google
“OpenAI and Google's Gemini are cleared for non-classified Pentagon use, meaning Claude's monopoly on classified systems is temporary.”
by Palantir
“Claude, integrated into Palantir's Maven Smart System since 2024, has already suggested hundreds of missile targets, issued precise location coordinates, and compressed weeks-long battle planning into real-time operations.”
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