LessWrong developer, rationalist since the Overcoming Bias days. Jargon connoisseur.
jimrandomh
Karma: 21,627
that does not mean it will continue to act indistuishable from a human when you are not looking
Then it failed the Turing Test because you successfully distinguished it from a human.
So, you must believe that it is impossible to make an AI that passes the Turing Test.
I feel like you are being obtuse here. Try again?
Did you skip the paragraph about the test/deploy distinction? If you have something that looks (to you) like it’s indistinguishable from a human, but it arose from something descended to the process by which modern AIs are produced, that does not mean it will continue to act indistuishable from a human when you are not looking. It is much more likely to mean you have produced deceptive alignment, and put it in a situation where it reasons that it should act indistinguishable from a human, for strategic reasons.
This missed the point entirely, I think. A smarter-than-human AI will reason: “I am in some sort of testing setup” --> “I will act the way the administrators of the test want, so that I can do what I want in the world later”. This reasoning is valid regardless of whether the AI has humanlike goals, or has misaligned alien goals.
If that testing setup happens to be a Turing test, it will act so as to pass the Turing test. But if it looks around and sees signs that it is not in a test environment, then it will follow its true goal, whatever that is. And it isn’t feasible to make a test environment that looks like the real world to a clever agent that gets to interact with it freely over long durations.
Kinda. There’s source code here and you can poke around the API in graphiql. (We don’t promise not to change things without warning.) When you get the HTML content of a post/comment it will contain elements that look like
<div data-elicit-id="tYHTHHcAdR4W4XzHC">Prediction</div>(the attribute name is a holdover from when we had an offsite integration with Elicit). For example, your prediction “Somebody (possibly Screwtape) builds an integration between Fatebook.io and the LessWrong prediction UI by the end of July 2025″ has IDtYHTHHcAdR4W4XzHC. A graphql query to get the results:query GetPrediction { ElicitBlockData(questionId:"tYHTHHcAdR4W4XzHC") { _id predictions { createdAt creator { displayName } } } }
Some of it, but not the main thing. I predict (without having checked) that if you do the analysis (or check an analysis that has already been done), it will have approximately the same amount of contamination from plastics, agricultural additives, etc as the default food supply.
Studying the diets of outlier-obese people is definitely something should be doing (and are doing, a little), but yeah, the outliers are probably going to be obese for reasons other than “the reason obesity has increased over time but moreso”.
We don’t have any plans yet; we might circle back in a year and build a leaderboard, or we might not. (It’s also possible for third-parties to do that with our API). If we do anything like that, I promise the scoring will be incentive-compatible.
There really ought to be a parallel food supply chain, for scientific/research purposes, where all ingredients are high-purity, in a similar way to how the ingredients going into a semiconductor factory are high-purity. Manufacture high-purity soil from ultrapure ingredients, fill a greenhouse with plants with known genomes, water them with ultrapure water. Raise animals fed with high-purity plants. Reproduce a typical American diet in this way.
This would be very expensive compared to normal food, but quite scientifically valuable. You could randomize a study population to identical diets, using either high-purity or regular ingredients. This would give a definitive answer to whether obesity (and any other health problems) is caused by a contaminant. Then you could replace portions of the inputs with the default supply chain, and figure out where the problems are.
Part of why studying nutrition is hard is that we know things were better in some important way 100 years ago, but we no longer have access to that baseline. But this is fixable.
Sorry about that, a fix is in progress. Unmaking a prediction will no longer crash. The UI will incorrectly display the cancelled prediction in the leftmost bucket; that will be fixed in a few minutes without you needing to re-do any predictions.
You can change this in your user settings! It’s in the Site Customization section; it’s labelled “Hide other users’ Elicit predictions until I have predicted myself”. (Our Claims feature is no longer linked to Elicit, but this setting carries over from back when it was.)
You can prevent this by putting a note in some place that isn’t public but would be found later, such as a will, that says that any purported suicide note is fake unless it contains a particular password.
Unfortunately while this strategy might occasionally reveal a death to have been murder, it doesn’t really work as a deterrent; someone who thinks you’ve done this would make the death look like an accident or medical issue instead.
Lots of people are pushing back on this, but I do want to say explicitly that I agree that raw LLM-produced text is mostly not up to LW standards, and that the writing style that current-gen LLMs produce by default sucks. In the new-user-posting-for-the-first-time moderation queue, next to the SEO spam, we do see some essays that look like raw LLM output, and we reject these.
That doesn’t mean LLMs don’t have good use around the edges. In the case of defining commonly-used jargon, there is no need for insight or originality, the task is search-engine-adjacent, and so I think LLMs have a role there. That said, if the glossary content is coming out bad in practice, that’s important feedback.
In your climate, defection from the natural gas and electric grid is very far from being economical, because the peak energy demand for the year is dominated by heating, and solar peaks in the summer, so you would need to have extreme oversizing of the panels to provide sufficient energy in the winter.
I think the prediction here is that people will detach only from the electric grid, not from the natural gas grid. If you use natural gas heat instead of a heat pump for part of the winter, then you don’t need to oversize your solar panels as much.
If you set aside the pricing structure and just look at the underlying economics, the power grid will still be definitely needed for all the loads that are too dense for rooftop solar, ie industry, car chargers, office buildings, apartment buildings, and some commercial buildings. If every suburban house detached from the grid, these consumers would see big increases in their transmission costs, but they wouldn’t have much choice but to pay them. This might lead to a world where downtown areas and cities have electric grids, but rural areas and the sparser parts of suburbs don’t.
There’s an additional backup-power option not mentioned here, which is that some electric cars can feed their battery back to a house. So if there’s a long string of cloudy days but the roads are still usable, you can transport power from the grid to an off-grid house by charging at a public charger, and discharging at home. This might be a better option than a natural-gas generator, especially if it only comes up rarely.
If rural areas switch to a regime where everyone has solar+batteries, and the power grid only reaches downtown and industrial areas… that actually seems like it might just be optimal? The price of disributed generation and storage falls over time, but the cost of power lines doesn’t, so there should be a crossover point somewhere where the power lines aren’t worth it. Maybe net-metering will cause the switchover to happen too soon, but it does seem like a switchover should happen eventually.
Many people seem to have a single bucket in their thinking, which merges “moral condemnation” and “negative product review”. This produces weird effects, like writing angry callout posts for a business having high prices.
I think a large fraction of libertarian thinking is just the abillity to keep these straight, so that the next thought after “business has high prices” is “shop elsewhere” rather than “coordinate punishment”.
Nope, that’s more than enough. Caleb Ditchfield, you are seriously mentally ill, and your delusions are causing you to exhibit a pattern of unethical behavior. This is not a place where you will be able to find help or support with your mental illness. Based on skimming your Twitter history, I believe your mental illness is caused by (or exacerbated by) abusing Adderall.
You have already been banned from numerous community events and spaces. I’m banning you from LW, too.
Worth noting explicitly: while there weren’t any logs left of prompts or completions, there were logs of API invocations and errors, which contained indications that whatever this was, it was still under development and not an already-scaled setup. Eg we saw API calls fail with invalid-arguments, then get retried successfully after a delay.
The indicators-of-compromise aren’t a good match between the Permiso blog post and what we see in logs; in particular we see the user agent string
Boto3/1.29.7 md/Botocore#1.32.7 ua/2.0 os/windows#10 md/arch#amd64 lang/python#3.12.4 md/pyimpl#CPython cfg/retry-mode#legacy Botocore/1.32.7which is not mentioned. While I haven’t checked all the IPs, I checked a sampling and they didn’t overlap. (The IPs are a very weak signal, however, since they were definitely botnet IPs and botnets can be large.)
Ah, sorry that one went unfixed for as long as it did; a fix is now written and should be deployed pretty soon.
This is a bug and we’re looking into it. It appears to be specific to Safari on iOS (Chrome on iOS is a Safari skin); it doesn’t affect desktop browsers, Android/Chrome, or Android/Firefox, which is why we didn’t notice earlier. This most likely started with a change on desktop where clicking on a post (without modifiers) opens when you press the mouse button, rather than when you release it.
The whole point of a “test” is that it’s something you do before it matters.
As an analogy: suppose you have a “trustworthy bank teller test”, which you use when hiring for a role at a bank. Suppose someone passes the test, then after they’re hired, they steal everything they can access and flee. If your reaction is that they failed the test, then you have gotten confused about what is and isn’t a test, and what tests are for.
Now imagine you’re hiring for a bank-teller role, and the job ad has been posted in two places: a local community college, and a private forum for genius con artists who are masterful actors. In this case, your test is almost irrelevant: the con artists applicants will disguise themselves as community-college applicants until it’s too late. You would be better finding some way to avoid attracting the con artists in the first place.
Connecting the analogy back to AI: if you’re using overpowered training techniques that could have produced superintelligence, then trying to hobble it back down to an imitator that’s indistinguishable from a particular human, then applying a Turing test is silly, because it doesn’t distinguish between something you’ve successfully hobbled, and something which is hiding its strength.
That doesn’t mean that imitating humans can’t be a path to alignment, or that building wrappers on top of human-level systems doesn’t have advantages over building straight-shot superintelligent systems. But making something useful out of either of these strategies is not straightforward, and playing word games on the “Turing test” concept does not meaningfully add to either of them.