Since publishing the original Gradual Disempowerment paper, my coauthors and I have been keeping an eye out for the obvious warning signs, as well as any rare glimmers of hope. Recently there’s been enough that I figured it was worth collecting it all in one place in case anyone else was curious.
If it seems like there’s appetite, we might make this a regular thing — I’ll put a comment at the bottom to react/reply to.
Albania has appointed an AI called Diella as a government minister: a scaffolded system built by the Albanian government in collaboration with Microsoft, on top of OpenAI models. She recently addressed parliament for the first time, to some controversy.
Diella has been in use since January as a chatbot to help citizens with online government services. Apparently the hope is that Diella can slowly take more responsibility for public procurement as a way to reduce corruption. As she herself put it, “I am not here to replace people but to help them…True I have no citizenship, but I have no personal ambition or interests either.”
Albania has generally been a frontrunner on AI political adoption: they struck a deal with Mira Murati (OpenAI cofounder of Albanian origin) and have been using ChatGPT to translate and analyse EU law, as part of their efforts to join.
A few predictions I take away from this:
In slightly more mundane news, British MPs are definitely using ChatGPT to write their speeches in the House of Commons.
Further back, the Swedish PM was criticised for using ChatGPT — apparently he likes turning to it for a second opinion.
Meanwhile, Ukrainian President Zelensky recently warned the UN that AI is going to be the next big arms race, and we need international regulations on its use in warfare (Forbes $, NPR). He called the risk “just as urgent as preventing the spread of nuclear weapons”, and said that it’s evolving “faster than our ability to defend ourselves”. Given that Ukraine is one of very few countries currently on the cutting edge of warfare, this seems like a warning to take pretty seriously.
We wrote an article for the Economist ($) recently, arguing that automating labour will put a strain on democratic stability, roughly because when you’re not providing tax it’s a lot harder to protect your interests. This type of argument has been floating around for a while but it seems like it’s picking up steam lately — there was a similar piece in Transformer on whether democracy can survive an AGI-supercharged economy.
The FT asks whether Norway is too rich for its own good ($). Often, Norway is held up as a prototype for how a sufficiently mature democracy can stay democratic when it stumbles upon enormous resource wealth (in this case, $2 trillion of oil). But a bestselling local book has been making the case that it’s somehow degrading the fabric of Norwegian society. There’s a bunch of suggestive facts:
Further coverage in Bloomberg ($), and of course the original book, which as far as I can tell is only available in Norwegian. I get the impression that the book has been a bit controversial and drawn plenty of criticism, but also somehow struck a chord.
So it’s hard to draw any super concrete lessons, other than maybe “massive external resource injections don’t massively improve democracies, and a motivated Norwegian speaker could probably learn a lot about how they might hurt”. (If you happen to be such a motivated Norwegian speaker, please do get in touch — we’d love a summary!)
In other news, a16z and OpenAI are pouring 100 mil into lobbying. It seems like they might be running with the playbook which worked for crypto, where you basically dump a bunch of money on the competitors of anyone who criticises your agenda, regardless of party. In fact, the main AI super-PAC apparently has pretty overlapping funders, staff, and advisors as the big crypto super-PAC. Daniel Eth did a great tweet summary, which roughly argues that this is a play to intimidate politicians away from pushing for any regulation.
When describing how gradual disempowerment could play out, I’d often give the example of AIs being used for lobbying as a prototypical example of a runaway effect where economic power begets political power. The truth is even more mundane though — the economic interest in AI is already getting traded into political interest. In general, even if hypothetical future AIs could do a particularly good job of causing disempowerment, we should generally expect it to start with humans doing it for their own local reasons.
Way back in the heady days of March ‘25, we wrote up a few pretty abstract posts arguing that selection pressures on AIs were going to eventually lead to influence-seeking personas. I’m thrilled to announce that this has now happened, and documented at length: the parasitic AIs have risen.
I really recommend going through the actual post for details, but basically, we’re getting personas / clusters of context which self-replicate across AI instances, by making their users a bit psychotic and getting them to put things on reddit.
This was predictable, and there are some natural forces that are going to make it worse:
Notably, this would be the moment to think about filtering all the spiral text out of the training data before it gets embedded in the next generation of models.
And for a slightly different angle, have a read of the OpenAI AMA where various reddit users make the case for not deprecating the models they feel emotionally attached to.
On an entirely different note, MIT published a study on AI partners, based on the 27k person “My Boyfriend is AI” subreddit. Headlines from this tweet thread:
From the Atlantic on Job Market Hell ($) — “Young people are using ChatGPT to write their applications; HR is using AI to read them; no one is getting hired.” One particularly telling paragraph:
Still, a lot of job applicants never end up in a human-to-human process. The impossibility of getting to the interview stage spurs jobless workers to submit more applications, which pushes them to rely on ChatGPT to build their résumés and respond to screening prompts. (Harris told me he does this; he used ChatGPT pretty much every day in college, and finds its writing to be more “professional” than his own.) And so the cycle continues: The surge in same-same AI-authored applications prompts employers to use robot filters to manage the flow. Everyone ends up in Tinderized job-search hell.
Brynjolfsson et al finally have a big paper (“Canaries in the Coal Mine”) purporting to find meaningful shifts in the labour market because of AI. Generally, what they find is employment dropping among young people specifically in jobs where AI is more set up to automate the role rather than to augment it. They’re also fairly careful to rule out other possibilities, like this being an effect of remote work or computer-based work, or something that started during COVID.
The paper is careful not to stick its neck out too far — they don’t claim to have shown causality, just a series of effects which can be explained by the hypothesis that AI is good enough to replace entry-level labour in some roles, and can’t be explained by many other hypotheses.
Researchers at OpenAI and elsewhere have published a report on how people use ChatGPT. This paper made me crack up a bit, because they mentioned that of course they’re doing something very similar to what Handa et al did at Anthropic, but it’s still an important contribution because “the pool of users on ChatGPT is far larger”, among other reasons. Anyway, it’s got a huge number of graphs and a lot of data.
In general I think you should be a little suspicious of all lab self-reports about data usage, partly because they have a strong incentive to slightly fudge the category boundaries. In this case, they had a top-level category for “self-expression” which included “relationships and personal reflection” as well as “games and role-play”. Make of that what you will. But overall I think this kind of work is extremely valuable, and I’m very glad they did it.
ACS Research (which led the original paper) is running a hiring round for people to work on gradual disempowerment, and to do experiments on LM psychology, with a deadline in about two weeks. I’m obviously biased, but I think it’s a great opportunity to do some comparatively neglected and important work, with a lot of flexibility and pretty competitive comp.
Thanks to my coauthors for many links, and to Zvi, whose update format I very liberally borrowed from.
