A look at the potential future of personalized, AI-generated entertainment, and how it could both submerge human originality and enable new forms of expression
NOTE: Our Forums and CMS and RSS were nixed when our host updated Perl … Phil Hoad / The Guardian : An inside look at how Netflix's use of data led to generic “algorithm films” intended for broad appeal, with AI set to further entrench the production style X: @newyorker : Joshua Rothman considers the potential future of personalized, A.I.-generated entertainment and tests out several forms of content—including podcasts, walking tours, and media criticism—produced for an audience of one. https://www.newyorker.com/... LinkedIn: David Szauder : I rarely make illustrations, but when The New Yorker reached out, I couldn't say no. It was also published in print. Self-irony... https://lnkd.in/... Pinja Pakalen : I came across a great New Yorker article called “A.I. Is Coming for Culture”. It looks at how AI is showing up everywhere: comedy, music, podcasts, even art—and what that means for creativity. … Kieran Knowles : Loved this article by Joshua Rothman in the The New Yorker — Somehow manages to weave the line between existential threat, optimism and deep humanity. … Bluesky: Emily Feng / @emilyzfeng : “Its webs, meanwhile, are woven by machines that are owned by corporations.” www.newyorker.com/magazine/202... Alex Hern / @hern : This is also why I think porn/erotica/smut could be an exception. The market for those things is largely people who never discuss their consumption with their peers. Oliver Mantell / @olivermantell : Thought-provoking article (I think it passes a basic test about articles on ‘the future’: that it gives meaningfully interesting perspectives on the present and the past...) [embedded post] Alex Hern / @hern : I don't like to say “never” but this is one of the predictions of the AI sector that seems most off to me. People like experiencing the same culture as their friends; “personalised”, beyond the level of a game, seems like a dead end [embedded post] Ray Newman / @raynewman : This article is interesting, to a point, but mostly maddening. For example, the author feeds ChatGPT some of his wife's writing then asks it to interpret a painting as she might. The very idea made me feel queasy. — www.newyorker.com/magazine/202... Mastodon: Richard MacManus / @ricmac@mastodon.social : I have mixed feelings about this article. The writer, a longtime New Yorker employee, eventually comes to the right conclusion: that human minds are original and “never say quite what you expect”, whereas AI is unoriginal & often cliched. But I found myself annoyed that this comes from a position of enormous media privilege. … Forums: Hacker News : A.I. Is Coming for Culture
Context & Ripple Effects
The story extends earlier coverage of AI-generated books and personalized articles, where synthetic output was already beginning to compete for work previously commissioned from human writers. That earlier shift toward AI-authored publishing provides the immediate backdrop for applying the same logic to culture made for an audience of one.
It also places Netflix’s data-led push toward broad-appeal “algorithm films” beside a more individualized model. The important distinction is not simply automation, but a move from optimizing content for mass segments to generating it around inferred personal taste.
First-order effects
- Personalized generation makes formats such as podcasts, walking tours, and criticism easier to tailor to an individual, shifting some value from a finished work’s shared audience toward a system’s ability to infer preferences.
- For entertainment platforms, the reported risk is that data-led production conventions become more deeply embedded: scalable output may favor familiar patterns even as it opens room for new, highly specific formats.
Second-order effects
- Creators and publishers face a sharper split between work valued for efficient personalization and work valued for distinctive judgment or a shared cultural point of reference—an extension of AI’s pressure on human-written content markets.
- Platforms with both audience data and distribution can gain leverage over standalone producers, because personalization depends on knowing viewers as well as generating material.
Third-order effects
- If personalized entertainment scales, cultural markets could shift from selling a common catalog to continuously generating individualized experiences, making discoverability and audience-data control more central than any single title.
- The trade-off will be whether lower-cost, tailored output expands expressive experimentation or narrows mainstream production around model-derived conventions; the article presents both outcomes as plausible.
The trend: This is one data point in AI content commercialization, in which generative systems move from assisting production to shaping what audiences receive and how it is tailored.