HumanPrint: How to Use AI Without Losing Yourself
Aug 20, 2026 · 19 min · 10 segments
**What this episode is about** You can disagree with everything a platform is doing and still have your subscribers, income, archive, and professional network sitting on it. Leaving is an option…
Christine WhitmarshHostSubstack has spent years presenting itself as a home for writers, and I understand why that language, that branding, that kind of positioning appealed to people.
Writers have been squeezed by publishers, shrinking media budgets, unstable freelance work, social algorithms, and this expectation that we should produce an endless supply of free material while somehow finding time to write the work we actually care about.
Then Substack came along and it offered direct publishing, email distribution, paid subscriptions, and really a cleaner relationship between writers and their readers.
But Substack is also a technology company building a broader social platform.
It has added notes and recommendations and direct messages and all kinds of bells and whistles, videos, live stream, social discovery, other features that extend well beyond sending newsletters.
And now it has partnered with Pangram to let readers scan eligible writing for an estimate, there's a key word again, estimate, of human versus AI involvement.
At some point, we have to stop responding to each new feature as if it's a surprise.
It does mean, though, that its interests and your interests will sometimes overlap and sometimes go the opposite way.
Now I've been reading a book, Karen Howe's book, it's called Empire of AI, which documents the development of open AI and the larger competition between AI companies to build increasingly powerful systems with AGI, artificial general intelligence, serving as the central goal around which enormous amounts of money and compute and energy, data, labor, all sorts of things are organizing around that AGI goal with many companies.
So the author's argument in the book is broader than one company or one product.
She describes an industry driven by the belief that reaching AGI first is important enough to justify a pace and scale that can push the costs onto workers, community artists, researchers, and people whose data or labor helps make those systems possible.
Again, you don't have to agree with every part of her analysis to recognize the competitive pressure that she's talking about.
They are competing over models and users and data and infrastructure, the infamous, the data centers and talent distribution, and really they're competing for control over how AI enters our lives.
Social media and publishing platforms are part of that environment because they possess something that AI companies need and technology companies value, which is large quantities of human communication, along with information about who created it, how other people responded, and what happened next.
One theory I raised in the most recent episode is that readers scan and creators disclosures and error reports, all that kind of stuff, AI slot flags, they can produce useful classification and behavioral data like tagging.
Substack has spent years presenting itself as a home for writers, and I understand why that language, that branding, that kind of positioning appealed to people.
Writers have been squeezed by publishers, shrinking media budgets, unstable freelance work, social algorithms, and this expectation that we should produce an endless supply of free material while somehow finding time to write the work we actually care about.
Then Substack came along and it offered direct publishing, email distribution, paid subscriptions, and really a cleaner relationship between writers and their readers.
But Substack is also a technology company building a broader social platform.
It has added notes and recommendations and direct messages and all kinds of bells and whistles, videos, live stream, social discovery, other features that extend well beyond sending newsletters.
And now it has partnered with Pangram to let readers scan eligible writing for an estimate, there's a key word again, estimate, of human versus AI involvement.
At some point, we have to stop responding to each new feature as if it's a surprise.
It does mean, though, that its interests and your interests will sometimes overlap and sometimes go the opposite way.
Now I've been reading a book, Karen Howe's book, it's called Empire of AI, which documents the development of open AI and the larger competition between AI companies to build increasingly powerful systems with AGI, artificial general intelligence, serving as the central goal around which enormous amounts of money and compute and energy, data, labor, all sorts of things are organizing around that AGI goal with many companies.
So the author's argument in the book is broader than one company or one product.
She describes an industry driven by the belief that reaching AGI first is important enough to justify a pace and scale that can push the costs onto workers, community artists, researchers, and people whose data or labor helps make those systems possible.
Again, you don't have to agree with every part of her analysis to recognize the competitive pressure that she's talking about.
They are competing over models and users and data and infrastructure, the infamous, the data centers and talent distribution, and really they're competing for control over how AI enters our lives.
Social media and publishing platforms are part of that environment because they possess something that AI companies need and technology companies value, which is large quantities of human communication, along with information about who created it, how other people responded, and what happened next.
One theory I raised in the most recent episode is that readers scan and creators disclosures and error reports, all that kind of stuff, AI slot flags, they can produce useful classification and behavioral data like tagging.
The rest of this transcript — segmented and speaker-labeled, so you land on the exact moment something was said
Search every transcript — by keyword, by phrase, or by meaning, across every show Radar indexes
Trends — what is surging across podcasts, measured against its own baseline
Alerts — when a name you follow appears in a newly indexed episode
No account is needed to search Radar.
