Well, hello! Nothing like a major feature in The New York Times to drive up one’s subscriber numbers, so welcome to the 600-plus new Cognitive Resonance readers—I’m grateful you’ve stopped by, and I hope you’ll stick around. For the most part, I focus here on comparing and contrasting human cognition with generative AI, with a healthy dose of ranting about dumb applications of AI in education. And on occasion things will get a tad personal and political, but I try to keep it contained.
That said, the story of my father dying because of his mis-reliance on AI blends the professional and personal, of course, and since so many of you arrived here because of Teddy Rosenbluth’s in-depth reporting on what happened to him, I want to share a bit more about the experience of the story process itself. I had no idea that when Teddy reached out to me that she intended to comprehensively investigate what happened over the past 18 months, and I suspect she didn’t either—that’s how reporting goes. But both her journalistic process, as well as new facts she uncovered along the way, continue to affect me deeply.
So, to start, being “reported on” has revealed why my many attempts at undergoing therapy have never worked out. I often say the bedrock principle of cognitive science is that we understand new ideas based on the ideas we already know, but it turns out that’s true for understanding new people, too. Or at least me.
By which I mean, when Teddy flew out to Austin in early March to interview me for three whole days—the Times is thorough, y’all—it was only after she’d spent several weeks digging into my family history. As such, when we sat together in my kitchen, she came prepared with questions about the entire arc of my father’s life, the early hopes, the physical setbacks, the set of unique experiences that comprised the story of his time on this Earth.
She wanted to know about his interests in technology, and I delighted in telling her about the time he jerry rigged our Dodge Caravan with a portable television and VCR player for our cross-country move from Long Island to California. We watched together an odd video he made in the last year or so describing his concerns about the re-election of Trump (apple didn’t fall far from the tree there). And she had an amusing fascination with the Lay-z-Boy chair that served as his de facto life nerve center in the living room of his condo in Edmonds, Washington. She was bummed I never could find a picture of it.
What I learned was simply this: Describing my father’s life to a relative stranger was cathartic. Validating. Therapeutic. Through answering Teddy’s questions about my father, I felt seen, as if she was starting to understand me based on her growing understanding of my dad’s life.
I had a story to share and someone wanted to listen. Isn’t that what we all want?
(This of course is what students so often feel with their human teachers, too. It’s why the teacher-student relationship often stands second only to parenting in its impact on who we become, and the character we form.)
The upshot is that, when Teddy called me two weeks ago to tell me the story would soon be published, my immediate sensation was bittersweetness, if that’s even a word. As I told her, only semi-jokingly, as long as the story was still being reported on, she was obligated to take my calls and talk to me about my dad. She kindly relayed that she often stays in touch with the subjects of her stories, so I’m looking forward to our future monthly check-ins regarding how the Riley family is doing. (I’m kidding, Teddy. Mostly.)
But Rosenbluth is a reporter first and foremost, not a therapist, and she reported the hell out of this story. Despite being granted a generous 3,200 words by her editors, however, hard choices had to be made about what to include and exclude, and here’s where I want to share with you something she uncovered through her reporting that didn’t make it into the final story that, quite frankly, enrages me still.
Quick recap: on July 15, 2025, after discovering that my father was relying on a “report” by Perplexity AI to reject his oncologist’s recommended treatment, I emailed two oncologists whose research was referenced therein: Dr. Adam Kittai, then at Mt. Sinai, and Dr. David Bond at Ohio State University. When I emailed them, the questions I posed were not focused on the AI report itself so much as whether my dad was at risk if he continued to forego treatment for his leukemia based on his (mistaken) belief that he was undergoing Richter’s Transformation. I didn’t expect a response, but to my suprise both emailed quickly to confirm that my dad should follow the recommendation of his primary oncologist, and nothing in their research suggested otherwise. And that’s where things were left.
That is, until Teddy had the smart idea to circle back to same oncologists to ask them to take a closer look at the Perplexity “report” in detail. So they did, essentially conducting a peer review of the output generated by this mindless tool. What they found was not an error here or there but rather a document that was basically nonsense from start to finish.
Thus, after the NYT story was published, I contacted both oncologists to ask if I could share publicly what they found, and they helpfully agreed to let me do so, which you’ll see momentarily. Even for someone like me who knows the likelihood of these tools producing false output, this is shocking to read, and I’m presenting just a sample of their comprehensive commentary.
From Dr. Adam Kittai – you can just focus on the yellow notes:
And here’s one of 10 pages of notes of errors identified by Dr. Bond, including “one nonsensical statement not supported by evidence”:
I’ve defended the use of the term “hallucination” to describe false output from LLMs for pragmatic reasons—when a phrase sticks in the public consciousness, that’s not for nothing (see also “AI skepticism”). But after reading this defenestration of the Perplexity AI output by these two human experts, hallucination feels inadequate in capturing the full magnitude of the bullshit spewed. In every section of the AI-generated "report,” in every sentence even, there are misleading or wrong or unsupported or nonsensical statements. But of course my father was in no position to know this, because he wasn’t an oncologist.
Nor was my dad’s experience an outlier. In the comments to the NYT story, you’ll find many reports from doctors and patients who have discovered the unreliability of AI as tool for medical diagnosis: For example, one doctor said this:
“As a primary care physician, I have used AI tools to explore possible causes of difficult to diagnose patient symptoms. While helpful in bringing forth diagnosis that might have been missed, as one drills down on how to manage a particular disease I have seen it confidently assert erroneous conclusions. When I point out the scientific inconsistencies of what it has asserted it reverts to sycophantic praise for my intelligence and abruptly changes its recommendations. What worries me is that I was only able to spot it’s inaccuracies because of my depth of knowledge and experience in the subject, something that the average user does not have.”
And one patient shared this:
“I found real comfort and value in the AI responses. You can’t just message your doctor at 11 p.m. and get an immediate answer as to why you’re experiencing some new and confusing symptom. So I get how AI can become a trusted medical ‘friend.’ However, at the end of the day, AI was completely wrong about my diagnosis. In fact, out of probably 20 different possibilities it listed, my real condition was never an option it presented.”
This goes beyond anecdote too, as there’s actually robust empirical evidence that AI should not be used medically. Gary Marcus recently published a helpful essay summarizing four recent research studies on this topic, and concludes: “LLMs don’t know what they don’t know; they work decently well with the information they’ve got but don’t know how to conduct clinical interviews, and in the hands of the lay public can easily give bad advice because the proper questions never get asked, either by the patient or the LLMs.”
How is any of this legal? Good question, and it might not be. Of course, the NYT story includes a bland quote from some PR flack at Perplexity saying the company was “deeply saddened” to learn about my father’s death. Sure, right, thanks. Not mentioned in the story is that Perplexity was already aware of what happened my dad prior to Teddy contacting them—so while I doubt anyone there feels any genuine emotional burden for the role their product played in killing one of my parents, no doubt their lawyers are keeping tabs on things. I’ve long joked that “dangerous when used as intended” is a trial lawyer’s favorite phrase, and here, Perplexity AI was more than dangerous. It was lethal.
With this essay, I will conclude my public grieving of what happened to my father, though I will remain forever grateful for the kindness and support from so many of you. The truth is, I’ve found this experience restorative. My father was a remarkable person who lived his life with dignity and curiosity, but he was somewhat of a hermit, so it’s meant a lot to share his story with the world, even in tragedy. There’s just one thing I wish had make the final cut of the NYT story, and that’s the solitary comment he ever shared on this Substack, in response to my essay about his failing health. I didn’t tell him my plans in advance, so I was nervous when that newsletter went out—would he be mad for my having shared something so personal?
He responded with this:
What you wrote (with considerable elegance) goes to the heart of who we are and how we are different from any AI model of the human mind: emotions. I don’t mean simplistic descriptions (e.g., oxytocin “causes” feelings of attachment) but it is an essential part of defining how we experience the world, from love (eros and agape) to feel an enriched response to a poem or piece of music and so on. This is why computational models are inherently inadequate; they do not arise except as add on subroutines to mimic the emotional depth of our experiences. And it is, to use the words of Victor Frankl, the last freedom, our freedom to choose our attitude.
I have nothing but gratitude for how my life has gone. To love and be loved, to fight the good fights, to live with the contradictions of sorrow and joy and never fail to appreciate a good joke is for the living alone.
That was my father, Joe Riley, a good man who loved his children deeply, and who I loved so very much.
Last Saturday, I was interviewed by Paul Henley of BBC Newshour regarding what happened to my dad. You can listen to the four-minute segment below.












This is so gut-wrenching to read-- the parts about the AI shit, not the parts about the reporting.
It underlines what I've come to think of as a central irony of AI-- it's really only safe to use if you are already an expert on whatever you're using it for.
Thank you for sharing your father's story.
I think the 'defenestration' as you called it is important, necessary work.
I feel like I'm taking crazy pills ala Jacobim Mugatu describing how AI is hype and oversold and everyone else keeps talking about how none of us will have jobs in the near future.
So far as I have seen, AI tools we have cannot work independently on anything that requires technical, specialized, or expert knowledge; it cannot work independently on detailed work that requires accuracy. This sort of AI is fine for a 'good-enough,' 'slap some paint on it' type jobs - like summarizing meeting notes or helping to draft an email. But as 'spicy autocorrect' or extra mathy-Markov Chain babblers, the tools we have don't *know* things so they can't actually do knowledge work - not work that needs to be done properly, at least.
AI can *maybe* help workers do their jobs. But I keep hearing from line worker programmer friends at tech companies with these AI mandates that the AI tools essentially create babysitting tasks for programmers. The immediate native output code will be a mess, or buggy, or won't compile, or won't adhere to required standards or practices, and so on. And we have multiple cases now of lawyers being laughed out of court for relying too much on AI. And we are getting stories now like your dad's of AI leading to bad health outcomes.
I think in the era of algorithmic social media, and everyone being pushed to their spiciest and most confrontation takes, and the death of nuance and context --- sure, I grant that AI is impressive and can do some cool things.
But increasingly to me the maximalist (or doomist) AGI hype looks oversold. The tech broligarchs keep thinking if they throw more and more compute at their powerful predictive text tools they will get actual intelligence. But that isn't necessarily going to be the case. What is the case is that tech dudes do need to justify the continued fire house of money that is coming their way, so they have every incentive to keep doubling down on what they know, even if the ratio or oversold hype to genuine promise is getting wobbly and unbalanced.
Thanks for sharing and the writing you are doing!