[HN Gopher] The future of AI according to thousands of forecasters
___________________________________________________________________
The future of AI according to thousands of forecasters
Author : ddp26
Score : 77 points
Date : 2023-06-27 15:13 UTC (7 hours ago)
(HTM) web link (www.metaculus.com)
(TXT) w3m dump (www.metaculus.com)
| nologic01 wrote:
| Its depressing to go over all this ultra-shallow chit-chat that
| has short-circuited any intelligent discussion about the role and
| trajectory of information technology (let alone any more serious
| problem or opportunity of the current times).
|
| Talking about AI (and AGI) as if its some xenomorph lurking
| somewhere in silicon, waiting for its inevitable escape from its
| human prison.
|
| AI will not bootstrap itself with some emergent property if
| somebody spends gazillions of dollars and Watts to estimate
| petazillions of parameters.
|
| Further progress is _not_ going to come unless some very human
| brain and intelligence opens up completely new algorithmic
| vistas.
|
| The future of AI is literally tied to the future development of
| _human_ mental (mathematical) models around information,
| knowledge and its digital representation.
|
| If not intuitively obvious, the history of mathematical thought
| development is crushing evidence that it follows its own dynamic
| over timescales that span centuries.
| TeMPOraL wrote:
| Counterpoint 1:
|
| > _Talking about AI (and AGI) as if its some xenomorph lurking
| somewhere in silicon, waiting for its inevitable escape from
| its human prison._
|
| > _AI will not bootstrap itself with some emergent property if
| somebody spends gazillions of dollars and Watts to estimate
| petazillions of parameters._
|
| Not right now, though recent breakthroughs look worryingly
| close. But the problem isn't AGI creating itself _ex nihilo_ ,
| but rather _us_ creating it. And if you look at how the world
| reacted to LLMs, millions of minds and billions of dollars are
| being thrown towards making that happen - because for the first
| time in history, it looks like we have an actual "angle of
| attack", and neither curious minds nor greedy businesses will
| leave it on the table.
|
| > _Further progress is not going to come unless some very human
| brain and intelligence opens up completely new algorithmic
| vistas._
|
| All we need to do is to get to roughly average human
| intelligence in higher cognitive functions, running in pure
| software. At that point, you can have an AI programmer and an
| AI ML researcher of similar occupational capability as their
| human counterparts. But this is software we're talking about -
| if you can have a pair of them, you can keep horizontally
| scaling until you have thousands or millions of them. And if
| you let them directly or indirectly work on their own code...
| they won't stay human-level for long. You get a feedback loop
| that's to our technological progress what our technological
| progress is to biological evolution.
|
| Counterpoint 2:
|
| Maybe it's clearer if instead of using the word "intelligence",
| we distill it into "optimization". After all, at high level,
| this is what intelligence is - a powerful optimization process.
| Now, we humans are no strangers to optimization processes that
| get out of control. Corporations, arguably, are one. Markets
| are definitely one, and the aggregate market economy is a
| powerful optimization process that's _already out of control_ -
| it 's self-directing and _owns us_. Culture arguably is too,
| but it 's a weak one.
|
| Consider that every time people say things like "if only we
| weren't so short-sighted and greedy, we would've solved
| poverty/war/climate change". If you take seriously the
| sociological and macroeconomic fact that humans follow
| incentives, then this really becomes "the system/economy/market
| makes it impossible for us to solve those problems", and...
| well, what is that system if not for a self-directed
| optimization process that arose, unintentionally, from our
| individual needs and desires? Well, semi-unintentionally - free
| market proponents use exactly this strong optimizer nature to
| argue why the market is fair and awesome and better than any
| kind of central planning.
|
| Now, as powerful optimizer as our economic system is, it's
| still kind of dumb. It averages away individual human
| intelligence. But what if it didn't? What if it had an actual
| human-level mind of its own, or at least a human-level mind
| that's able to perceive and act on the market faster than any
| one human or group of humans could? Literally getting inside
| our collective OODA loop? This influence won't get cancelled
| out - at this point, we'd be screwed.
|
| And that's just one possible scenario - AI tech giving a mind
| to the economy itself. But the broader point here is, we've
| already established we can accidentally create powerful generic
| optimizers that end up controlling us. The ones we deal with
| today are _slow_ , because they run on humans and human
| interaction in physical space. But when we create an optimizer
| that runs on our digital infrastructure, that one will be
| _faster_.
| Footkerchief wrote:
| Do you think the human brain has bootstrapped itself with an
| emergent property in a way that is impossible in silicon?
| letmevoteplease wrote:
| "We have to learn the bitter lesson that building in how we
| think we think does not work in the long run. The bitter lesson
| is based on the historical observations that 1) AI researchers
| have often tried to build knowledge into their agents, 2) this
| always helps in the short term, and is personally satisfying to
| the researcher, but 3) in the long run it plateaus and even
| inhibits further progress, and 4) breakthrough progress
| eventually arrives by an opposing approach based on scaling
| computation by search and learning.
|
| ...
|
| The second general point to be learned from the bitter lesson
| is that the actual contents of minds are tremendously,
| irredeemably complex; we should stop trying to find simple ways
| to think about the contents of minds, such as simple ways to
| think about space, objects, multiple agents, or symmetries. All
| these are part of the arbitrary, intrinsically-complex, outside
| world. They are not what should be built in, as their
| complexity is endless; instead we should build in only the
| meta-methods that can find and capture this arbitrary
| complexity. Essential to these methods is that they can find
| good approximations, but the search for them should be by our
| methods, not by us. We want AI agents that can discover like we
| can, not which contain what we have discovered."
|
| http://www.incompleteideas.net/IncIdeas/BitterLesson.html
| __loam wrote:
| I think the bitter lesson has a lot more to do with the
| physical limits of von neumann computation and the structure
| of computing as we currently understand it than the direction
| that AI research should go.
|
| That the emergent deep learning truthers are on the ascent
| should not be an excuse to completely discount knowledge
| based approaches. We're currently grappling with a number of
| limitations in the latest generation of ML models,
| particularly surrounding the cost of computation required to
| train and run them, and the fact that they have absolutely no
| way to verify the quality or correctness of their output.
| Clearly there are drawbacks to relying on a system we barely
| understand to produce our programs for us.
| shawntan wrote:
| I'm a little bit tired of the Bitter Lesson copypasta.
|
| It doesn't seem to me like point 1 to 3 have been proven to
| be true about ConvNets. Sure, scaling convnets further help,
| I don't think anyone would argue that training a big model on
| more data would not at least see some improvement.
|
| I also think there are irrefutable lower bounds of
| computation that it would be important to consider when
| building these meta-methods. If your problem requires N steps
| of computation for a problem of N size, but your method can
| only always perform at most K steps of computation, no amount
| of data or compute you throw at it will result in the right
| solution.
| odobo wrote:
| I don't think the parent comment is irreconcilable with the
| Bitter Lesson. I don't think transformers are a path to AGI,
| but that doesn't mean we need to go back to symbolic AI. We
| need to iterate on the meta-methods we use to search for and
| encapsulate the complexity of intelligence.
| vok wrote:
| Related: https://news.ycombinator.com/item?id=36486490
| ilaksh wrote:
| Nowhere do they define "AGI". I guarantee that is a big reason
| why the predictions have so much variance.
|
| For many people, what GPT-4 does qualified as AGI -- up until
| GPT-4 came out and then everyone seemed to decide that AGI meant
| ASI.
|
| I am guessing for many people answering this poll it means "a
| full emulation of a person". Or maybe it had to be "alive".
|
| The thing that irritates me so much is that there is this lack of
| definition or moving of goalposts and also stupidly people seem
| to assume that AI can't be general purpose or useful unless it
| has all of those animal/human characteristics.
|
| GPT-4 is very general. Make it say 10-20 times faster, open up
| the image modality to the public, and you will be able to do most
| human tasks with it. You don't need to invent a lot of other
| stuff to be general purpose.
|
| You DO need to invent a lot of other stuff to become some kind of
| humanlike digital god. But that is not the least bit necessary to
| accomplish most human work output.
| sublinear wrote:
| > you will be able to do most human tasks with it. You don't
| need to invent a lot of other stuff to be general purpose.
|
| I think this is where most people strongly disagree with you. A
| probabilistic language model is not good enough to do anything
| requiring context particularly well.
| cwkoss wrote:
| Agentic uses of GPT can solve the context problem by breaking
| problems into steps and building prompts to solve those
| steps.
|
| Can't do everything, but GPT+APIs can do a lot.
| davidmanheim wrote:
| > Nowhere do they define "AGI"
|
| Ummm, maybe you should have looked? At the top of the very
| first prediction, here:
| https://www.metaculus.com/questions/5121/date-of-artificial-...
|
| We will thus define "an AI system" as a single unified software
| system that can satisfy the following criteria, all completable
| by at least some humans.
|
| Able to reliably pass a 2-hour, adversarial Turing test during
| which the participants can send text, images, and audio files
| (as is done in ordinary text messaging applications) during the
| course of their conversation. An 'adversarial' Turing test is
| one in which the human judges are instructed to ask interesting
| and difficult questions, designed to advantage human
| participants, and to successfully unmask the computer as an
| impostor. A single demonstration of an AI passing such a Turing
| test, or one that is sufficiently similar, will be sufficient
| for this condition, so long as the test is well-designed to the
| estimation of Metaculus Admins.
|
| Has general robotic capabilities, of the type able to
| autonomously, when equipped with appropriate actuators and when
| given human-readable instructions, satisfactorily assemble a
| (or the equivalent of a) circa-2021 Ferrari 312 T4 1:8 scale
| automobile model. A single demonstration of this ability, or a
| sufficiently similar demonstration, will be considered
| sufficient.
|
| High competency at a diverse fields of expertise, as measured
| by achieving at least 75% accuracy in every task and 90% mean
| accuracy across all tasks in the Q&A dataset developed by Dan
| Hendrycks et al..
|
| Able to get top-1 strict accuracy of at least 90.0% on
| interview-level problems found in the APPS benchmark introduced
| by Dan Hendrycks, Steven Basart et al. Top-1 accuracy is
| distinguished, as in the paper, from top-k accuracy in which k
| outputs from the model are generated, and the best output is
| selected.
|
| By "unified" we mean that the system is integrated enough that
| it can, for example, explain its reasoning on a Q&A task, or
| verbally report its progress and identify objects during model
| assembly. (This is not really meant to be an additional
| capability of "introspection" so much as a provision that the
| system not simply be cobbled together as a set of sub-systems
| specialized to tasks like the above, but rather a single system
| applicable to many problems.)
|
| Resolution will come from any of three forms, whichever comes
| first: (1) direct demonstration of such a system achieving ALL
| of the above criteria, (2) confident credible statement by its
| developers that an existing system is able to satisfy these
| criteria, or (3) judgement by a majority vote in a special
| committee composed of the question author and two AI experts
| chosen in good faith by him, for the sole purpose of resolving
| this question. Resolution date will be the first date at which
| the system (subsequently judged to satisfy the criteria) and
| its capabilities are publicly described in a talk, press
| release, paper, or other report available to the general
| public.
| gpderetta wrote:
| You do realize that many, if not most, humans would fail this
| test, right?
| kayodelycaon wrote:
| Yes, but humans as a group can do it. An AGI needs to show
| a similar number of AGIs can do the same given the same
| starting template.
|
| The AGI will need to look at all of the tasks written,
| determine what the success criteria is, and then combine
| that that into a single set of answers. With the
| instructions in human-readable form, not machine readable.
| It can use as many or as few AGIs as it needs to accomplish
| this.
|
| It's the same as if we gave these instructions to a human
| with sufficient skill and resources to delegate.
| TheOtherHobbes wrote:
| AGI is competing with _human culture as a whole._
|
| Individual humans are not exactly the best of all possible
| tests for AGI.
| og_kalu wrote:
| Yes you'll find that any testable definition of AGI that
| has not been passed yet would be unpassable for a big chunk
| of the human population.
|
| In other words, General, Artificial and Intelligent have
| been passed. That's why a few papers/researchers opt to
| call these models "General Artificial Intelligence" instead
|
| https://jamanetwork.com/journals/jama/article-
| abstract/28064...
|
| https://arxiv.org/abs/2303.12003
|
| Or some such variant like "General Purpose Technologies" as
| Open AI did.
|
| https://arxiv.org/abs/2303.10130
|
| since "AGI" has so much baggage with posts shifting at the
| speed of light.
| sdwr wrote:
| I think we're reaching a point where the Turing test is no
| longer useful. If you get into the nitty-gritty of it
| (instead of just handwaving "computer should act like
| person"), it's about roleplaying a fake identity. Which is a
| specific skill, not a general test of competence.
| dbspin wrote:
| Thank you. It was arguably never useful beyond an intuition
| pump. It's a test of credulity, of susceptibility to
| pareidolia, not reasoning ability.
| [deleted]
| nfc wrote:
| The Turing test seems to be a product of an era where the
| nature and capabilities of artificial intelligence were
| still in the realms of the unknown. Because of that it was
| difficult to conceive a specific test that could measure
| its abilities. So the test ended up focusing on human
| intelligence--the most advanced form of intelligence known
| at that time--as the benchmark for AI.
|
| To illustrate, imagine if an extraterrestrial race created
| a Turing-style test, with their intelligence serving as the
| gold standard. Unless their cognitive processes closely
| mirrored ours, it's doubtful that humans would pass such an
| examination
| usaar333 wrote:
| Correct, which is part of the reason the "weak" AGI is
| relatively out there. Will anyone bother dumbing down an AI
| to pass a Turing Test? "Oh a human can't write a poem that
| fast -- it's an AI!"
| ilaksh wrote:
| Yup, missed that, thanks. Has anyone scored GPT-4 on the APPs
| benchmark?
|
| I believe that if you take GPT-4 multimodal integrated with
| Eleven Labs and Whisper then there is a shot at passing that
| extended Turing test, if designed fairly. The wording is
| still a bit ambiguous.
|
| Also assembling that particular scale model is probably
| challenging but not really a general task and something that
| could be probably be achieved with simulated sensors and
| effectors given a 3-4 month engineering effort into utilizing
| advanced techniques (maybe training an existing multimodal
| LLM and integrating it with some kind of RL-based robot
| controller?) at interpreting and acting on those kinds of
| instructions. It would be possible to integrate it with the
| LLM such that it could report its projects and identify
| objects during assembly.
|
| So my takeaway is that with some serious attempts and an
| honest assessment of this bar, an AI would be able to pass
| that this year or next. I mean I don't know how far GPT-4 is
| from the 75%/90% but I doubt it is that far and so expect if
| not GPT-4 then GPT-4.5 or 5 could pass given some engineering
| effort aimed at the test competencies.
|
| If people really are thinking 2030 or 2040 when they read
| "AGI" and respond to that poll (I suspect some didn't read
| the definition) then that would indicate that people are just
| ignorant of the reality of how far along we are, or in
| denial. Or a little of both.
| jiggywiggy wrote:
| Chatgpt 4 is amazing. Still cant comprehend they build this.
|
| However if you work with it a lot you realize it doesn't
| understand reality, it predicts language.
|
| It reminds me of YouTube videos of chess when human start to
| figure out chess bots and the tricks they use to draw out time.
|
| Understanding language is super impressive, but a far cry from
| general intelligence. Maybe from here open ai can build
| further. But I have a hard time believing that this will be a
| foundation for general intelligence.
|
| A lot of animals have a form of general intelligence but cant
| do math or language. Yet in some ways are more capable then the
| latest self driving cars.
| jsight wrote:
| Is it surprising that a system that was exclusively trained
| on emitted language will only do well on language?
|
| I don't see how I can extrapolate to anything beyond that. I
| certainly can't extrapolate that it would be unable to learn
| other tasks.
| bg24 wrote:
| Everything is defined in language. As a system is able to
| learn from the corpus of texts, it also builds reasoning to
| a large extent. For example, GPT4 can guide you through
| solving a problem like building a flying and crawling drone
| for inspecting an attic. Or, watering plants. So this goes
| beyond language, unless I missed your point.
| og_kalu wrote:
| This is the problem here.
|
| A Claim is made. "GPT isn't general" or "GPT isn't
| Intelligent" or whatever but a testable definition is not
| made. That is, what is generality to you and what bar need be
| passed ? Or What Intelligence is and what competence level
| need be surpassed ?
|
| Without clearly stating those things, Intelligence may well
| be anything or any goal and your posts could shift to
| anywhere.
|
| I'm just going to tell you facts of the state we're in right
| now.
|
| Any testable definition of AGI that GPT-4 fails would also be
| failed by a significant chunk of the human population.
| dbspin wrote:
| > Any testable definition of AGI that GPT-4 fails would
| also be failed by a significant chunk of the human
| population.
|
| GPT cannot function in any environment on its own. Except
| in response to a direct instruction it cannot plan, it
| cannot take action, it cannot learn, it cannot adjust to
| changing circumstance. It cannot acquire or process energy,
| it has no intentionality, it has no purpose beyond
| generating new text. It's not intelligent in any sense, let
| alone generally. It's an incredibly capable tool.
|
| Here's a testable definition of AGI - any combination of
| software and hardware that can function independently of
| human supervision and maintenance, in response to
| circumstance that have not been preprogrammed.
|
| That's it. Zero trial learning and function. All adult
| organisms can do it, no AI can. Artificial general
| intelligence that's actually useful would need a bunch of
| additional functionality of course, there I'll agree with
| you.
| og_kalu wrote:
| >GPT cannot function in any environment on its own.
| Except in response to a direct instruction it cannot
| plan, it cannot take action, it cannot learn, it cannot
| adjust to changing circumstance.
|
| Sure it can. It's not default behavior sure but it's
| fairly trivial to set up, just expensive. Gpt-4 can loop
| on its "thoughts" and reflect, it can take actions in the
| real world.
|
| https://tidybot.cs.princeton.edu/
| https://arxiv.org/abs/2304.03442
| https://arxiv.org/abs/2210.03629
| https://arxiv.org/abs/2303.11366
| rhn_mk1 wrote:
| > Here's a testable definition of AGI - any combination
| of software and hardware that can function independently
| of human supervision and maintenance, in response to
| circumstance that have not been preprogrammed.
|
| Not sure how I feel about a significant portion of the
| population already not meeting that threshold. The
| elderly? The disabled? I think you're proving the
| parent's point.
| TeMPOraL wrote:
| > _Not sure how I feel about a significant portion of the
| population already not meeting that threshold. The
| elderly? The disabled?_
|
| Anyone? How did the saying go? The minimum viable unit of
| reproduction for homo sapiens is _a village_.
|
| _None of us_ passes the bar, if the test excludes
| "supervision and maintenance" by other people - and not
| just our peers, but our parents, and their parents, and
| _their_ parents, ... all the way back until we reach some
| self-sufficient-ish animal life form. That 's, AFAIR, way
| below primates on evolutionary scale.
|
| But that test is bad also for other reasons, including
| but not limited to:
|
| - It is confusing intelligence with survival. Survival is
| not intelligence, it is a highly likely[0] _consequence_
| of it[1].
|
| - It underplays the non-random aspect of it. Phrased like
| GP phrased it, a _rock_ can pass this test. The power of
| intelligence isn 't in passively enduring novel
| circumstances - it's in actively navigating the world to
| get more of what you want. Including changing the world
| itself.
|
| --
|
| [0] - A process optimizing for just about any goal will
| find its own survival to be beneficial towards achieving
| that goal.
|
| [1] - If you extend it from human-like intelligence to
| general optimization, then all life is an example of
| this: survival is a consequence of natural selection -
| the most basic form of optimization, that arises when you
| get a self-replicating something that replicates with
| some variability into similar self-replicating
| somethings, and when that variability affects survival.
| welshwelsh wrote:
| Define "reality."
|
| Human experience consists of more than language, for sure.
| There is also a visual, audible and and tactile component.
| But GPT-4 can also take visual inputs from my understanding,
| and it shouldn't be difficult to add the other senses.
|
| Google's experiments with PaLM-e show that LLMs are also
| useful in an embodied context, such as helping robots solve
| problems in real-time.
| floundy wrote:
| Where's the poll option for "it continues to be overhyped junk
| spewing misinformation, then arguing with the user (Bard) or
| acquiescing when pressed regardless of the correctness of the
| rebuttal (ChatGPT)"?
|
| You can surely get a indistinguishable imitation of human text
| from including things like Reddit comments in the LLM training
| data. Correctness is a hurdle I am not convinced will be
| surpassed.
| avionical wrote:
| It sure seems like people are getting value from the current
| crop of tools: https://fortune.com/2023/06/15/nine-of-ten-
| developers-using-...
| floundy wrote:
| Cool, now try it with a knowledge field that isn't code that
| can be tested for the proper output.
| avionical wrote:
| I find it useful for a few different non-coding work tasks,
| and I don't think I'm unusual there.
| floundy wrote:
| I write technical finance/econ articles and the only
| thing I've found it useful for is getting a vague outline
| of typical topics that might be touched on in an entry-
| level article about something.
|
| For example to GPT-4 I ask:
|
| >is silver a good investment? what are the considerations
| to take into account?
|
| Returns essentially an enumerated list of topics about
| supply and demand, volatility, storage considerations,
| and opportunity cost compared to other investments. These
| are very basic explanations of a sentence or two and
| usually correct, but too general to be of much use.
|
| I then ask:
|
| >how has the historical performance of silver compared to
| gold and the S&P 500 over the past 5 decades?
|
| And it provides vague history of what happened to each
| investment in each decade, no quantifiable data. Okay,
| let's ask:
|
| >Re-consider the above prompt using quantifiable data,
| how much would an investment of $1,000 per month adjusted
| for inflation into each of these investments have
| compared at the end of the 5 decades?
|
| Output: I apologize for the confusion, but as an AI
| language model, I don't have access to real-time data or
| the ability to perform specific calculations.
| malfist wrote:
| > Metaculus predicts a 75% likelihood of an attempt to influence
| the 2024 US presidential election with AI-driven misinformation.
|
| Hasn't that already happened? Wasn't DeSantis caught running
| deepfaked voices in an ad? Or am I misremembering something
| davidmanheim wrote:
| It's more specific than that once they actually operationalize
| the question:
|
| This question resolves as YES if, in Meta's 2024 Q4 Quarterly
| Adversarial Threat Report, Meta claims that there was at least
| one "coordinated inauthentic behavior" that
|
| specifically pertained to the 2024 US Presidential election,
| and Meta suspects was primarily conducted via AI.
| notahacker wrote:
| The operationalized question seems to be more of a bet on
| what Meta admits happens on its platform than what happens!
|
| We know that people aiming to influence the elections use
| bots to inflate particular sentiments, statistical techniques
| which are arguably 'AI' to target messaging and have the
| capability to effortlessly generate varations on content
| using LLMs... it'd almost be odd if people _didn 't_ do so in
| a coordinated manner for the US election.
| croddin wrote:
| It was fake images not fake voices, but yeah looks like it has
| already happened, not sure if it fully meets the criteria in
| the market.
|
| https://www.npr.org/2023/06/08/1181097435/desantis-campaign-...
| Imnimo wrote:
| Is there any already resolved question in which metaculus
| forecasters made a surprisingly accurate prediction about an AI
| advance?
| yunohn wrote:
| Anyone can signup and vote, so I assume it tends towards the
| majority option tbh. Seems like obviously noisy data.
| tersh wrote:
| The Metaculus prediction weights predictors by how accurate
| they've been.
| [deleted]
| yunohn wrote:
| Yes, but if voters are voting the majority (and probable)
| decision, that just continues the trend of predicting
| obvious outcomes.
|
| It's not something to do with understanding domain
| knowledge and voting based on scientific research.
| avionical wrote:
| I wouldn't say AGI in 10 years is predicting an obvious
| outcome. And the same goes for many other questions on
| the site.
| usaar333 wrote:
| https://www.metaculus.com/questions/track-record/
|
| Only 13 resolved binary questions where you had longer
| prediction horizons (1+ year), the accuracy is zilch in AI
| category - Brier score of 0.25 which is akin to just guessing
| out 50% for all questions. Generally overconfident.
|
| (Other categories much better - Brier of 0.14 1 year out)
| avionical wrote:
| There are several AI categories on the track record page;
| make sure you're not just selecting the one or you'll miss a
| lot. There's a careful analysis of the overall track record
| on AI questions here:
| https://www.metaculus.com/notebooks/16708/exploring-
| metaculu...
|
| The short version is that the Brier score is much better than
| .25 for AI questions, and the weighted Metaculus Prediction
| is more accurate still.
| Imnimo wrote:
| Can I see the list of questions used in this analysis
| somewhere? Is it literally just the set of questions I see
| when I filter for "Resolved" and "Artificial Intelligence"?
|
| My impression from browsing that set of questions is that
| it's a mix of pretty trivial things like "how expensive
| will chatGPT be?" or "when will Google release Bard?".
| There are very few questions in the bunch I'd even consider
| interesting, let alone ones where the metaculus prediction
| appears to have offered any meaningful insight.
| usaar333 wrote:
| Good call on the categories.
|
| > The short version is that the Brier score is much better
| than .25 for AI questions, and the weighted Metaculus
| Prediction is more accurate still.
|
| Added more categories. 1 year out is 0.217. I agree that's
| better than chance, though "much better"?
|
| That said, this is dominated by bad community predictions
| pre-2020 and there's not much data recently for binary
| questions. I agree that CRPS is better - but it's not clear
| to me from that link how early they are looking at
| questions - accuracy gets better closer to resolve date --
| I'm claiming that longer-term predictions are shakier.
| avionical wrote:
| And you may want to check the weighted Metaculus
| Prediction if you haven't already.
| sashank_1509 wrote:
| AGI by 2040 huh. I bet it won't happen by 2100, and I'm young
| enough that I can look back on this at 2040 and see how wrong/
| correct I was. Future me, don't forget!
| kenjackson wrote:
| Depending on who you ask, we will never have it or we have it
| already. We never had a perfect definition of AGI, but I feel
| like now the definition has become so murky to be useless.
| avionical wrote:
| True, though clearing up some of the murkiness is part of
| what forecast questions like these are for, with their
| explicitly spelled out resolution criteria.
| alach11 wrote:
| OP in 2040: "It's not AGI because it doesn't have a soul."
| sashank_1509 wrote:
| My definition would AGI as an AI embodied in a human robot
| that can do all the physical and cognitive tasks a regular
| human can, for example I would assume 90% of humans can be an
| Uber driver, and so the AGI system should be capable of being
| an Uber Driver. While perhaps only 5% can be a theoretical
| physicist or a professional tennis player, so I wouldn't
| expect my AGI to be capable of that
| shaunxcode wrote:
| Yeah I feel like people have turned the definition of AGI
| into what we previously called omnipotence.
| moomoo11 wrote:
| How cool would it be if we could build stuff that directly builds
| the society we want? Call it utopia or whatever who cares.
|
| But I wish there were other people in the game (none that I know
| personally at least, lots just act like accountants lol) who want
| to use their money to build and enable the kind of world at
| large, like we are playing a city builder irl. Making money is
| whatever but making a world is just _chefs kiss_.
|
| To use the technology available today in ways that people don't
| even have to think, but it leads to good outcomes.
|
| AI seems to be one of those vectors and I hope it works out. I'm
| personally all in with even just LLM applications.
| zgluck wrote:
| "Forecaster" here means any rando who signs up to their service
| and answers a question.
|
| Sometimes a large polling number does not equal a more accurate
| answer.
| saulmunn wrote:
| this isn't quite true -- on metaculus, accounts that have a
| history of forecasting things well are weighted more heavily
| zgluck wrote:
| SISO (Shit In, Shit Out) still applies. You guys need a high
| quality user base with domain knowledge, at least as a seed.
| There is no proof that you have that at the moment.
|
| Edit:
|
| Okay, that track record page avionical posted in a separate
| comment is actually a bit convincing now that I dig deeper
| into it. :-)
|
| I suppose that for e.g. AI/AGI a weakness could be that the
| estimates for most of the users have been short term (a few
| years at most) but the AGI estimates are 8-17 years away.
| Those estimates are a lot harder to do make and hence surely
| a lot less accurate.
| avionical wrote:
| What would be good evidence of a high-quality user base
| with the relevant skills? A transparent, well-calibrated
| track record?
| avionical wrote:
| Anyone can forecast, sure. But there's a large body of research
| on the accuracy of aggregated forecasts and on the ability of
| forecasters to become more accurate with practice. (Thinking
| here in particular of work by Mellers & Tetlock.)
|
| Metaculus provides a transparent track record of community
| forecasts here: https://www.metaculus.com/questions/track-
| record/ It's very difficult for any one person to consistently
| beat the community.
| notahacker wrote:
| The numbers there seem odd (or did before the page broke,
| possibly due to the HN 'hug of death')
|
| 90% chance of near term "human level" AI but only a 75% chance
| someone tries to influence the US election with "AI driven
| misinformation" which for most definitions of "AI" and
| "misinformation" is already happening?
| ddp26 wrote:
| Hug of death is fixed, even this modest traffic was too much
| for our cache.
|
| | 90% chance of near term "human level" AI but only a 75%
| chance someone tries to influence the US election with "AI
| driven misinformation" which for most definitions of "AI" and
| "misinformation" is already happening?
|
| Yes, if 2040 is "near term". The majority view is that before
| 2025, the only major AI safety concerns are deepfakes,
| misinformation, and maybe social engineering.
|
| But over the subsequent years, the consensus shifts to
| predicting widespread disruption.
| malfist wrote:
| Something about the page is certainly broke. I don't get the
| graphs to load until I use the mouse wheel on their ui elements
| [deleted]
___________________________________________________________________
(page generated 2023-06-27 23:02 UTC)