I'm especially interested to hear from people with long (i.e. 20+ year) timelines what they think the next 10 years will look like.
[EDIT: After pushback from Richard Ngo, I've agreed to stop talking about short and long timelines and just use numbers instead, e.g. "20+ year" and "<10 year" timelines. I recommend everyone do the same going forward.]
Ajeya (as of the time of her report at least) is such a person, and she gave some partial answers already:
By 2025, I think we could easily have decent AI personal assistants that autonomously compose emails and handle scheduling and routine shopping based on users’ desires, great AI copy-editors who help a lot with grammar and phrasing and even a little bit with argument construction or correctness, AIs who summarize bodies of information like conversations in meetings or textbooks and novels, AI customer service reps and telemarketers, great AI medical diagnosis, okay AI counseling/therapy, AI coding assistants who write simple code for humans and catch lots of subtle bugs not catchable by compilers / type checkers, even better AI assisted search that feels like asking a human research assistant to find relevant information for you, pretty good AI tutors, AIs that handle elements of logistics and route planning, AIs that increasingly handle short-timescale trading at hedge funds, AIs that help find good hyperparameter settings and temperature settings for training and sampling from other AIs, and so on.
But she thinks it'll probably take till around 2050 for us to get transformative AI, and (I think?) AGI as well.
The hypothesis I'm testing here is that people with long timelines [EDIT: 20+ year timelines] nevertheless think that there'll be lots of crazy exciting AI progress in the twenties, just nothing super dangerous or transformative. I'd like to get a clearer sense of how many people agree and what they think that progress will look like.
I think that it is very likely that AGI will emerge in the next 20 years, unless something massively detrimental to AI development happens.
So, it's the year 2050, and there is still no AGI. What happened?
Some possible scenarios:
We got lucky with the first COVID-19 variants being so benign and slow-spreading. Without that early warning (and our preparations), the Combined Plague could have destroyed the civilization. We've survived. But the disastrous pandemic has slowed down progress in most fields, including AI research - by breaking supply chains, by reducing funding, and by claiming many researchers.
After the Google Nanofab Incident, the US / the EU / China decided that AI research must be strictly regulated. They then bullied the rest of the world to implement similarly strict regulations. These days, it's easier to buy plutonium than to buy a TPU. The AGI research is ongoing, but at a much slower pace.
The collapse of the main AI research hub - the US. The Second Civil War was caused mostly by elite overproduction, amplified by Chinese memetic warfare, the pandemic, and large-scale technological unemployment. The Neoluddite Palo Alto Lynching is still remembered as one of the bloodiest massacres in the US history.
The first AGI secretly emerged, and decided to mostly leave the Earth alone, for whatever reason. Its leftowers are preventing the emergence of another AGI (e.g. by compromising every GPU / TPU in subtle ways).
We have created an AGI. But it requires truly enormous computational resources to produce useful results (similarly to AIXI). For example, for a few million bucks worth of compute, it can master Go. But to master cancer research, it needs thousands of years running on everything we have. We seem to be still decades away from the AGI making any difference.
I haven't thought about it that carefully but Ajeya's paragraph sounds reasonable to me. Intuitively, I feel more pessimistic about medical diagnosis (because of regulations, not because of limitations of AI) and more optimistic about AI copy-editors (in particular I think they'll probably be quite helpful for argument construction). I'm not totally sure what she means about AIs finding good hyperparameter settings for other AIs; under the naive interpretation that's been here for ages (e.g. population-based training or Bayesian optimization or gradient-based hyperparameter optimization or just plain old grid search).
I'd expect this all to be at "startup-level" scale, where the AI systems still make errors (like, 0.1-50% chance) that startups are willing to bear but larger tech companies are not. For reference, I'd classify Copilot as "startup-level" but probably doesn't yet meet the bar in Ajeya's paragraph (though I'm not sure, I haven't played around with it). If we're instead asking for more robust AI systems, I'd probably add another 5ish years on that to get to 2030.
High uncertainty on all of these. By far the biggest factor determining my forecast is "how much effort are people going to put into this"; e.g. if we didn't get good AI copy-editors by 2030 my best explanation is "no competent organization tried to do it". Probably many of them could be done today by a company smaller than OpenAI (but with similar levels of expertise and similar access to funding).
But she thinks it'll probably take till around 2050 for us to get transformative AI, and (I think?) AGI as well.
I'm similar on TAI, and want to know what you mean by AGI before giving a number for that.
I'm assuming it also has to be a "single system" (rather than e.g. taking instructions and sending them off to a CAIS-like distributed network of AI systems that then do the thing). We may not build AGI as defined here, but if we instead talk about when we could build it (at reasonable expense and speed), I'd probably put that around or a bit later than the TAI estimate, so 2050 seems like a reasonable number.
Hmm, a billion users who use it nearly every day is quite a lot. I feel like just from a reference class of "how many technologies have a billion users who use it every day" I'd have to give a low probability on that one.
Google Search has 5.4 billion searches per day, which is a majority of the market; so I'm not sure if web search has a billion users who use it nearly every day.
Social media as a general category does seem to have > 1 billion users who use it every day (e.g. Facebook has > 2 billion "daily active users").
On the other hand, Internet access and usage is increasing, e.g. the most viewed YouTube video today probably has an order of magnitude more views than the most viewed video 8 years ago. Also, it seems not totally crazy for chatbots to significantly replace social media, such that "number of people who use social media" is the right thing to be thinking about.
Still, overall I'd guess no, we probably won't have a billion people talking to a chatbot every day. Will we have a chatbot that's fun to talk to? Probably.
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That seems quite a bit more likely, I think I do expect that to happen (especially since I know lots of people who want to keep up-to-date with AI, e.g. I know a couple of people who use GPT-3 for fun).
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I don't know what you mean by this. We already use statistics to forecast tournament winners, and we already have algorithms that can operate on markets (including prediction markets when that's allowed). So I'm not sure what change from the status quo you're suggesting.
I'm especially interested to hear from people with long (i.e. 20+ year) timelines what they think the next 10 years will look like.
[EDIT: After pushback from Richard Ngo, I've agreed to stop talking about short and long timelines and just use numbers instead, e.g. "20+ year" and "<10 year" timelines. I recommend everyone do the same going forward.]
Ajeya (as of the time of her report at least) is such a person, and she gave some partial answers already:
But she thinks it'll probably take till around 2050 for us to get transformative AI, and (I think?) AGI as well.
The hypothesis I'm testing here is that people with long timelines [EDIT: 20+ year timelines] nevertheless think that there'll be lots of crazy exciting AI progress in the twenties, just nothing super dangerous or transformative. I'd like to get a clearer sense of how many people agree and what they think that progress will look like.
(This question is a complement to Bjartur's previous question)