felixsimon.bsky.social
Research Fellow in AI and News, Reuters Institute, Oxford University | Research Associate & DPhil, Oxford Internet Institute | AI, news, misinfo, tech, democracy | Affiliate Tow Center, CITAP | Media advisor | My views etc…
https://www.felixsimon.net/
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As in: What motivates someone to move effortlessly (and without deep expertise) from pontificating about e.g. geopolitics, populism, to Covid, to AI? Are they convinced by the wares they sell? And who pays for this so-called "expertise" and why?
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hahahha
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Like sure this is all awful at the end of the day but let the people have some fun for once.
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Affirmative
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(And what Meta can do, Google can do, too. Or at least one would assume so)
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Seems like this is true for advertising with the slight wrinkle that it might be even easier here because “in advertising, we don't have to care about truth” as one executive recently put it to me.
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I argued (in what feels like ages ago) that AI in news not just expanded platform control over means of distribution but also to a degree over production.
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Network effects are gonna network effect I guess
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The best I could muster on a Thursday eve after a glass of white wine 😅
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A big thanks to our speakers Gill Whitehead, Adam Mahdi, @chrismoranuk.bsky.social , @Jonathan Hvithamar Rystrøm, Zeynep Pamuk & Scott Hale, our many guests, and to @ballioloxford.bsky.social, @michelledisser.bsky.social & @amyrossarguedas.bsky.social for all the logistical support. Stay tuned.
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The upshot? Agentic AI promises dazzling productivity gains (if it materialises remains to be seen), but without good governance and public-interest guard-rails we could be headed for trouble.
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And the public sphere does not get spared either, with agents potentially personalising news to an ‘audience of one’, threatening publishers’ business models (and perhaps shared democratic deliberation) in the same breath.
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Regulators, meanwhile, are scrambling; a “pick-and-mix” mosaic of principles, sector codes and voluntary standards leaves vast latitude to the very firms building AI agents (and the underlying system).
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Some of the trade-offs involved are no longer theoretical: big banks now run systems that draft complaint letters, chase fraud and may soon pre-empt customers’ gripes. Healthcare providers are thinking about systems that could outperform doctors on some diagnoses…but not on all
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From thermostats to agents AI systems, we traced the spectrum of what “agentic” means, learned that greater capability often walks hand-in-hand with greater opacity, forcing us to weigh usefulness against a thicket of risks.
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Also I guess everyone can now see what I’m up to next week but hey 🤷♂️
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Makes one wonder if the deal was struck with Amazon because:
1) They offered more $$$?
2) They offered better conditions for the NYT?
3) They are not seen as cannibalising the NYT's traffic (unlike e.g. Google, OpenAI, Perplexity)?
4) All or some of the above together
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Shocked how well it works
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The latter
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Yup. Almost killed two recent publications of mine at two different journals— both of which said they accepted them in their guidance 🙃 they got through thanks to kind editors but it was a fight
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Yup agree with that and would argue that both these things are true at the same time: individual responsibility for your actions AND institutional mechanisms that prevent such cases :)
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Thanks, although I would say that journalists have some individual responsibility, too, in how they use AI systems. E.g. in this case the fact that it wasn't (?) intentional & that the freelancer seemingly did not know that AI's could hallucinate does not fully exonerate them from checking output
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Thank you, Jan. That’s very kind of you to say.
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The Sun-Times at least seems to have drawn consequences from this (chicago.suntimes.com/press-room/2... ) which strike me as reasonable and well-advised.
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…for some tasks – but here is the rub: For some tasks, but not for others. Helping journalists and the public to understand and distinguish one from the other needs to be part of the way forward.
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Railing against their general use as some do is fine – we need criticism of the political economy around them (copyright, dependency, and all that jazz) and their irresponsible use. But at the same time, people (including journalists) are using them and they are clearly useful…
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My initial reaction to this case was: "Really, this is still happening?" Quite indicative of my own blind spots. I had simply assumed that most journalists would know by now that this particular use of an AI chatbot comes with risks. Well, I was wrong!
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What can we learn from this case? We really need a better education of journalists on all levels (from freelancers to executives) about how these systems work and for what (and where they fail). This does not just apply for hallucinations but also questions around sensitive data.
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Yes, the AI created errors. But that it was allowed to end up in print is to blame on oversight structures. This is, btw, not just an AI thing as e.g. the 2018 case of Claas Relotius and completely invented magazine pieces in Germany demonstrate: www.bbc.co.uk/news/world-e...
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It is also too easy to just blame the technology here and raises broader question about why such syndicated material is not acknowledged as originating from a third party and not subjected to more thorough verification and review.
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Regardless, it demonstrates that journalists working with such tools at such a basic level and for the generation of information (regardless of one’s opinion on whether these systems should be used for such tasks in news at all) must double-check the output*
(*exceptions apply)