Episode 183: AI Hype and the Disciplining of "Creative," Academic, and Journalistic Labor
Added 2023-05-31 14:03:14 +0000 UTC"Is artificial intelligence advancing too quickly?" 60 Minutes warns. "BuzzFeed CEO says AI may revolutionize media, fears possible 'dystopian' path," CBS News tells us. "TV and film writers are fighting to save their jobs from AI. They won't be the last," CNN reports.
Over and over, especially in recent months, we hear this line: AI is advancing so fast, growing so sophisticated, and becoming so transformative as to completely reshape the entire economy to say nothing of our shaky media landscape. In some cases, those in the press deem this a good thing; in others, a bad thing but in terms that get the problem all wrong. But virtually all media buy the basic line that something big and transformative isn’t just coming, but is in fact already here.
Obviously, we can't predict the future, but we can comment on the present. Yes, AI platforms can generate low-level marketing copy, pro forma emails, and shitty corporate art. But progress in these capacities does not, as such, portend a radical advancement into actual human intelligence and creativity.
Meanwhile, there’s little to no evidence to support the claim that AI, namely large language models like ChatGPT, actually can perform – or even intervene to save time performing – any type of high-level writing craft, journalism, fiction, screenwriting, and a host of “creative” production.
So why do we keep hearing otherwise? What purpose does this type of uncritical, providential thinking serve? And who stands to benefit from the vague sense of a future of AI-written essays, articles, and scripts, no matter how terrible they may be?
In this episode, we explore media's current Inevitability Narrative, namely its credulous warning that ChatGPT is about to do the work of media and entertainment professionals, examining the ways in which this narrative, despite the evidence to the contrary, serves as a constant, implicit threat to workers and a convenient pretext for labor abuses like wage reduction, layoffs, and union-busting. We also review how this media hype works to obscure the very real, banal harms of AI, such as racism, surveillance, over policing and lack of accountability for the powerful.
Our guest is Rutgers professor Dr. Lauren M.E. Goodlad.
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Guest
Dr. Lauren M.E. Goodlad is a Distinguished Professor of English and Comparative Literature at Rutgers, as well as a faculty affiliate of the Center for Cultural Analysis and the Rutgers Center for Cognitive Science. Dr. Goodlad currently serves as chair of a new interdisciplinary initiative on Critical Artificial Intelligence and as Editor-in-Chief of the multidisciplinary journal Critical AI, published by Duke University Press.
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Show Notes
As TV Writers Strike, US Media Uncritically Echoes Film Studio Execs’ Bogus “AI Writer” Hype
Adam Johnson | May 16, 2023 | The Column
Writers Like Me Have Shut Down Hollywood. Here’s Why.
Josh Gondelman | May 4, 2023 | The Nation
Nellie Andreeva and Dominic Patten | May 3, 2023 | Deadline
Now The Humanities Can Disrupt “AI”
Lauren M.E. Goodlad and Samuel Baker | February 20, 2023 | Public Books
Could AI pen ‘Casablanca’? Screenwriters take aim at ChatGPT
Jake Coyle | May 5, 2023 | Associated Press
Hamilton Nolan | May 18, 2023 | How Things Work
AI machines aren’t ‘hallucinating’. But their makers are
Naomi Klein | May 8, 2023 | The Guardian
Alex Hern | May 5, 2023 | The Guardian
Will A.I. Become the New McKinsey?
Ted Chiang | May 4, 2023 | The New Yorker
Policy makers: Please don’t fall for the distractions of #AIhype
Emily Bender | March 29, 2023 | Medium
Statement from the listed authors of Stochastic Parrots on the “AI pause” letter
March 31, 2023 | DAIR
ChatGPT Is a Blurry JPEG of the Web
Ted Chiang | February 9, 2023 | The New Yorker
ChatGPT Is About to Dump More Work on Everyone
Ian Bogost | February 2, 2023 | The Atlantic
How a Google Employee Fell for the Eliza Effect
Brian Christian | June 21, 2022 | The Atlantic
The Dangerous Ideas of “Longtermism” and “Existential Risk”
Émile P. Torres | July 28, 2021 | Current Affairs
Raffi Khatchadourian | November 23, 2015 | The New Yorker
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Transcript
For a full transcript of this episode, go here. You can find transcripts of past episodes and News Briefs here.
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Credits
Senior Producer: Florence Barrau-Adams
Producer: Julianne Tveten
Production Assistant: Trendel Lightburn
Newsletter: Marco Cartolano
Transcription: Morgan McAslan
Music: Grandaddy
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Comments
did Prof. Goodlad make a Universal Paperclip reference? :D
Wren Hearn
2023-06-12 04:10:49 +0000 UTCAdam's recurring point about the cost of "rewriting" is actually a well understood concept in the business world: "rework" is always more inefficient than work. Quality Control books summarize it with the aphorism: "Anything worth doing is worth doing right the first time." Of course none of this will stop studio bosses eager to cheat workers out of their share of the profits.
Cree Merr
2023-06-07 23:50:31 +0000 UTCThis episode was so good. Wanted to put this on your radar if you had not seen it, ties back into an article Adam wrote a while back as well re: chatbots acting as therapists under the guise of "expanding access", all the while firing unionizing helpline employees: https://www.vice.com/en/article/qjvk97/eating-disorder-helpline-disables-chatbot-for-harmful-responses-after-firing-human-staff https://www.vice.com/en/article/n7ezkm/eating-disorder-helpline-fires-staff-transitions-to-chatbot-after-unionization
Leann
2023-06-02 15:14:21 +0000 UTCThis episode was awesome! I feel vindicated because I work in a space that's adjacent to this subject and the hype has been... bleh. I do want to make two points though: 1. A small correction for Dr. Goodlad around 1:17:30 -- there are actually quite a few tech companies that are dipping their toes into the ML for science pool (climate change, drug discovery, materials for energy, and so on). Microsoft has AI4Science, which employs quite a few chemistry and engineering professors; Google has DeepMind, which is doing a lot with protein folding (among other things); and Meta has stuff like the Open Catalyst project (for energy applications). I think those projects are less "sexy" than LLMs because they're less directly and immediately useful for end users, so they're not marketed as intensely but tech giants are definitely in the game. Now, I'm much more skeptical of those companies than I am of academics who are doing similar work because we (academics) are supposed to openly disclose our findings. Plus, I also fall into the Mariana Mazzucato school of thought that believes in the transformative power of basic fundamental science that's publicly funded and whose results are openly available. (source: am academic working on ML for materials with friends/acquaintances at some of these places, but folks can read more about the things I mentioned at these links https://www.microsoft.com/en-us/research/lab/microsoft-research-ai4science/ https://www.deepmind.com/research/highlighted-research/alphafold https://ai.facebook.com/research/impact/open-catalyst/) 2. On the usefulness of LLMs for coding and writing, they're excellent for debugging code and correcting my mistakes. That is, in a wonderful twist of irony, basically the opposite of what so many companies are suggesting. I find my life is much easier when I write the original stuff and then let a machine proofread for me and make suggested edits because it can catch errors much faster than I can, explain why they're wrong, and provide suggestions that I can then use to fix what I've done.
Alex
2023-06-01 22:51:29 +0000 UTCThis is a feel good episode because even I was starting to get sucked into the hype about AI. Seeing it as another extension of class warfare makes it way clearer and my anger is now focused where it needs to be - so many people need to understand this - Dr Goodlad is my new hero
HenrytheWorst
2023-05-31 19:13:40 +0000 UTC
