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Our newsroom AI policy

arstechnica.com

41–50 of 144 posts

Re: Our newsroom AI policy

#41

AI is in danger of peeing in it's own water source. It's unbelievably useful at imitating and generating content, but it needs enough original content to be able to train and scrape. Google got one thing wrong and nearly destroyed the internet - people need to have an incentive to contribute content online, and that incentive should not be to game the system for advertising. This in particular dawned on me when askin…

> I was imaging if LLMs could finally solve the micropayments solution people have always proposed for the internet. Part of my monthly payment gets split between all of the sites that the LLM scraped knowledge. Paid out like Spotify pays out artists.

This system is usually called taxes.

Which then pay for the universal healthcare, free education, affordable housing, libraries, parks,.. and so on.

LLM doesn't need to invent it, we should stop allowing them (people and companies behind LLM) to avoid it.

Re: Our newsroom AI policy

#42

Self-contradictory policy. > Reporters may use AI tools vetted and approved for our workflow to assist with research, including navigating large volumes of material, summarizing background documents, and searching datasets. If this is their official policy, Ars Technica bears as much responsibility as the author they fired for the fabricated reporting. LLMs are terrible at accurately summarizing anything. They very r…

> You cannot permit your employees to use LLMs in this manner and then tell them it's entirely their fault when it makes mistakes, because you gave them permission to use something that will make mistakes 100% without fail.

Yes you can. The same way Wikipedia (or, way back when, a paper encyclopedia) can be used for research but you have to verify everything with other sources because it is known there are errors and deficiencies in such sources. Or using outsourced dev resource (meat-based outsourced devs can be as faulty as an LLM, some would argue sometimes more so) without reviewing their code before implemeting it in production.

Should they also ban them from talking to people as sources of information, because people can be misinformed or actively lie, rather than instead insisting that information found from such sources be sense-checked before use in an article?

Personally I barely touch LLMs at all (at some point this is going to wind up DayJob where they think the tech will make me more efficient…) but if someone is properly using them as a different form of search engine, or to pick out related keywords/phrases that are associated with what they are looking for but they might not have thought of themselves, that would be valid IMO. Using them in these ways is very different from doing a direct copy+paste of the LLM output and calling it a day. There is a difference between using a tool to help with your task and using a tool to be lazy.

> it's company policy not to burn everything to the ground!

The flamethrower example is silly hyperbole IMO, and a bad example anyway because everywhere where potentially dangerous equipment is actually made available for someone's job you will find policies exactly like this. Military use: “we gave them flamethrowers for X and specifically trained them not to deploy them near civilians, the relevant people have been court-martialled and duly punished for the burnign down of that school”. Civilian use: “the use of flamethrowers to initiate controlled land-clearance burns must be properly signed-off before work commences, and the work should only be signed of to be performed by those who have been through the full operation and safety training programs or without an environmental risk assessment”.

Re: Our newsroom AI policy

#43
post #39

Earlier quoted context omitted.

And yet we are discussing this in the context of a reporter having been fired from Ars Technica for publishing an article which included inaccurate LLM-generated summaries in 2026. How come? https://news.ycombinator.com/item?id=47226608

Maybe you should read the article? :) What failed was extracting verbatim quotes, not summarizing. If you want an LLM to do verbatim anything, it has to be a tool call. So I’m not surprised.

[dead]

Re: Our newsroom AI policy

#44
post #7

AI is in danger of peeing in it's own water source. It's unbelievably useful at imitating and generating content, but it needs enough original content to be able to train and scrape. Google got one thing wrong and nearly destroyed the internet - people need to have an incentive to contribute content online, and that incentive should not be to game the system for advertising. This in particular dawned on me when askin…

> I was imaging if LLMs could finally solve the micropayments solution people have always proposed for the internet. Part of my monthly payment gets split between all of the sites that the LLM scraped knowledge. Paid out like Spotify pays out artists. As a software user I wish I could do the same for all the software I use.

Many open source projects accept donations. There's also explicitly paid-for software. What exactly do you wish for that you can't do right now?

Re: Our newsroom AI policy

#45
post #44
post #7

Earlier quoted context omitted.

> I was imaging if LLMs could finally solve the micropayments solution people have always proposed for the internet. Part of my monthly payment gets split between all of the sites that the LLM scraped knowledge. Paid out like Spotify pays out artists. As a software user I wish I could do the same for all the software I use.

Many open source projects accept donations. There's also explicitly paid-for software. What exactly do you wish for that you can't do right now?

Specifically the part where engineers get paid the same way as artists on Spotify.

Re: Our newsroom AI policy

#47
post #45
post #44

Earlier quoted context omitted.

Many open source projects accept donations. There's also explicitly paid-for software. What exactly do you wish for that you can't do right now?

Specifically the part where engineers get paid the same way as artists on Spotify.

So not at all for their work and with a reverse Robin Hood model? That would be terrible for software. The way artists gets paid on streaming is a genius play at catering to the biggest artists and labels and screw over the smaller ones, especially true on Spotify with their freemium model

Re: Our newsroom AI policy

#48
AI policy with AI usage is always difficult to write/read. Lengthy, frontloaded with excuses, values, and big words, followed by more words to fill the gap between sliced up ugly truth.

AI policy without AI usage is easy to read and write.

> We don't use them. That's it.

Re: Our newsroom AI policy

#49

AI is in danger of peeing in it's own water source. It's unbelievably useful at imitating and generating content, but it needs enough original content to be able to train and scrape. Google got one thing wrong and nearly destroyed the internet - people need to have an incentive to contribute content online, and that incentive should not be to game the system for advertising. This in particular dawned on me when askin…

> Paid out like Spotify pays out artists.

That's probably not the best comparison. Spotify only benefits the big players resp. those with the most bots. If you actually want to support specific artists, you'd have to use Bandcamp or similar sites.

Re: Our newsroom AI policy

#50

Self-contradictory policy. > Reporters may use AI tools vetted and approved for our workflow to assist with research, including navigating large volumes of material, summarizing background documents, and searching datasets. If this is their official policy, Ars Technica bears as much responsibility as the author they fired for the fabricated reporting. LLMs are terrible at accurately summarizing anything. They very r…

> LLMs are terrible at accurately summarizing anything. They very randomly latch on to certain keywords and construct a narrative from them, with the result being something that is plausibly correct but in which the details are incorrect, usually subtly so, or important information is omitted because it wasn't part of the random selection of attention. I don't know what you've been doing, but the summaries I get from…

Depends on topic, often what they consider important isn't what is important and details that are essential get out of view. I'm having good success with youtube video, not as much with technical docs.
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