[HN Gopher] What policy makers need to know about AI
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What policy makers need to know about AI
Author : jph00
Score : 72 points
Date : 2024-06-17 17:50 UTC (5 hours ago)
(HTM) web link (www.answer.ai)
(TXT) w3m dump (www.answer.ai)
| jph00 wrote:
| Hi Jeremy here - I wrote this article. The deeper I got into
| studying this, the more I realised the people writing the laws
| that will regulate AI actually don't really understand what
| they're regulating at all.
|
| So I created this to try to at least help them create regulations
| that actually do what they think they're going to do.
|
| California's SB 1047, which I analyse closely, currently totally
| fails to meet the goals that the bill authors have stated.
| Hopefully this will help them fix these problems. If you have
| views on SB 1047, you can make a public comment here:
| https://calegislation.lc.ca.gov/Advocates/
|
| Let me know if you have any questions or comments.
| throwadobe wrote:
| this belongs in major newspapers and media outlets. some PR
| campaign to get this message out there should prove fruitful.
| you can hire someone and just have them suggest articles to
| magazines and papers, who are always looking for content
| anyway. it's topical, urgent, convincing, and it comes from an
| authority in the field, so it checks all the boxes IMHO
| atlasunshrugged wrote:
| Jeremy, this is a great read, thank you! What do you think
| about the amended version from today that gives the FMD
| significantly greater authority on what would and would not be
| covered by the legislation? Any other specific recommendations
| for the legislation that would help protect open-source?
|
| Edit to ask: Does it seem likely to you that one of the
| unintended consequences of the legislation as written is that
| companies like Meta will no longer open-source their models?
| jph00 wrote:
| It'll take me a while to digest today's changes, so I don't
| have an educated opinion about them as yet.
|
| Yes, companies like Meta will no longer be able to open-
| source their models, once their compute reaches the
| threshold, if the bill goes through and if the "covered
| model" definition is interpreted to include base models (or
| is modified to make that clear).
| cs702 wrote:
| Jeremy -- thank you for sharing this on HN. And thank you also
| for everything else you've done for the community :-)
|
| I agree with you that one of the biggest issues -- maybe the
| biggest issue -- with the proposed legislation is that it fails
| to differentiate between "releasing" and "deploying" a model.
| For example, Jamba was released by AI21, and Llama3 was
| released by Meta. In contrast, GPT-4o was deployed by OpenAI
| and the latest/largest Gemini was deployed by Google, but
| neither model was ever released! We don't want legislation that
| prevents researchers from releasing new models, because
| releases are critical to scientific progress.
|
| However, I'm not so sure that lack of understanding by
| politicians is the main driver of misguided legislation. My
| understanding is that politicians prefer to consider the
| opinion of "experts" with the most "impressive" pedigrees, like
| high-ranking employees of dominant tech companies, most of
| which don't want _anyone_ to release models.
| jph00 wrote:
| Interestingly enough, in this case none of the 3 sponsoring
| organizations are dominant tech companies. Rather, they are
| well-funded AI safety orgs -- although, to be fair, these
| orgs generally get their money from folks that are some of
| the biggest investors in Anthropic, OpenAI, and Google.
|
| But I do have the impression they earnestly believe they're
| doing the right thing. The AI safety orgs have done
| incredibly effective outreach at universities for years, and
| have as a result gotten a huge amount of traction amongst
| enthusiastic young people.
| cs702 wrote:
| Thank you. Like you, I also have the impression that folks
| at those AI safety orgs sincerely believe they're doing the
| right thing.
|
| But I would ask them the same questions I would ask the
| politicians: Which "experts" did they consult to reach
| their conclusions? From whom did their "talking points"
| come?
|
| I hope you're right that they and the politicians are
| willing to change course.
| numlocked wrote:
| Jeremy -- this is interesting and worthwhile. Thank you!
|
| In the same spirit (ignoring the question of whether this sort
| of attempted regulation is a good idea), I have a question:
|
| Debating release vs. deploy seems a bit like regulating e.g.
| explosives by saying "you can build the bomb, you just aren't
| allowed to detonate it". Regulation often addresses the
| creation of something dangerous, not just the usage of it.
|
| Did you consider an option to somehow push the safety burden
| into the training phase? E.g. "you cannot train a model such
| that at any point the following safety criteria are not met." I
| don't know enough about how the training works to understand
| whether that's even possible -- but solving it 'upstream' makes
| more intuitive sense to me than saying "you can build and
| distribute the dangerous box, but no one is allowed to plug it
| in".
|
| (Possibly irrelevant disclosure: I worked with Jeremy years ago
| and he is much smarter than me!)
| jph00 wrote:
| Yes I considered that option, but it's mathematically
| impossible. There's no way to make it so that a general
| purpose learned mathematical function can't be tweaked
| downstream to do whatever someone chooses.
|
| So in that sense it's more like the behaviour of the pen and
| paper, or a printing press, than explosives. You can't force
| a pen manufacturer to only sell pens that can't be used to
| write blackmail, for instance. They simply wouldn't be able
| to comply, and so such a regulation would effectively ban
| pens. (Of course, there's also lots of ways in which these
| technologies are different to AI -- I'm not making a general
| analogy here, just an analogy to show why this particular
| approach to regulation is impossible.)
| numlocked wrote:
| That makes sense. Regulating deployment may simply be the
| only option available -- literally no other mechanic
| (besides banning releasing models altogether) is on the
| menu.
| darosati wrote:
| I would not say it's impossible... my lab is working on
| this (https://arxiv.org/abs/2405.14577) and though it's far
| from mature - in theory some kind of resistance to
| downstream training isn't impossible. I think under
| classical statistical learning theory you would predict
| it's impossible with unlimited training data and budget for
| searching for models but we don't have those same
| gaurentees with deep neural networks.
| zoobab wrote:
| There is no agreed definition of what an open source AI model
| is.
|
| I guess if the models you mention would have to be packaged in
| Debian, they would end up in the non-free section, since you
| cannot rebuild them from the training data, which is not
| published.
| the8472 wrote:
| It's more like creative commons, licensed binary assets. The
| source isn't included. And the compilation process is
| onerous.
| the8472 wrote:
| > These kinds of technologies, like AI models, are fundamentally
| "dual use". The general purpose computation capabilities of AI
| models, like these other technologies, is not amenable to
| control.
|
| I find that entire section to be misleading or even false.
| Comparing a N-billion or even trillion parameter model
| representing aggregated human knowledge and some (however
| limited) agentness when put in a harness like autogpt makes it a
| different category than a pen and paper.
|
| Additionally it is not true that models are just has hard to
| control as a piece of paper. If millions of dollars are invested
| in each training run, the reseachers and the associated
| infrastructure then this clearly is not a simple piece of paper.
| It's more like sat tech covered by ITAR or semiconductor tech
| which is also export-restricted.
| tgv wrote:
| It is pretty hard to build anything that can compete with
| decent LLMs, so indeed. The section you quote is the only
| argument in favor of allowing release of LLMs, and it rests on
| the assumption that LLMs will be like "all these technologies
| have been, on net, highly beneficial to society." This is a
| purely hypothetical extrapolation from cherry-picked examples.
| It is intellectually dishonest.
|
| Releasing the actual models without deploying them (in terms of
| the article) still allows bad actors to generate large amounts
| of spam and disinformation, to mimic voices and generate
| revenge porn, to mention but a few risks.
|
| And the author had better not reply that that's FUD:
|
| > A restriction on Californian AI would mean that Americans
| would have to increasingly rely on Chinese software if they
| wanted full access to models.
| jph00 wrote:
| If someone is generating spam and disinformation, or
| mimicking voices and generating revenge porn, it is a
| deployment under the definition of 'deploy' in the article.
| So under the proposal there, this would be regulated.
| Aerroon wrote:
| Unfortunately the EU has already rammed their legislation
| through. The US is always going to be compared to EU propaganda
| about "how they protect the people".
| thegrim33 wrote:
| Is there a name for the logical fallacy that the author presents,
| that goes like:
|
| 1) In the past (some portion of) society was scared about the
| printing press, and it turned out to be fine
|
| 2) In the past (some portion of) society was scared about the
| internet, and it turned out to be fine
|
| 3) Therefore, if nowadays (some portion of) people are scared of
| AI, then they're wrong, AI is safe, because in the past some
| portion of the population was wrong about other technologies
|
| I guess it would be called a non-sequitur?
|
| Here's a more contrived example to make the fallacy more clear:
|
| 1) In the past (some portion of) people didn't think automobiles
| could obtain speeds of 50mph and they turned out to be wrong
|
| 2) In the past (some portion of) people didn't think automobiles
| could obtain speeds of 300mph and they turned out to be wrong
|
| 3) Therefore, nowadays, my claim that I have an automobile that
| will drive 10,000 mph must always be right, because in the past
| (some portion of) people were wrong about automobile progress.
|
| I've been seeing lots of examples of this type of fallacy where
| the giveaway is people pointing out about how people in the past
| made bad predictions, which somehow means any predictions people
| are making today are also wrong. It just doesn't follow.
| janalsncm wrote:
| I'm not sure if there is a specific term, but it's basically an
| example of the problem of induction and confirmation bias. The
| conclusion does not logically follow from its tenants.
| Basically, no matter how many white swans you've seen, you
| can't use that information to prove that black swans don't
| exist.
| hatthew wrote:
| "Weak induction" might be a good way to describe this. "Hasty
| generalization" if you want a more common logical fallacy to
| name, though ironically it's a more general fallacy that
| doesn't perfectly describe the situation you're talking about.
|
| Technically all inductive arguments are a non-sequitur, since
| (non-)sequitur is a deductive concept and inductive arguments
| are inherently non-deductive.
| entrepy123 wrote:
| As a cognitive bias: That sounds like the "normalcy" (or
| normality) bias, "the refusal to plan for, or react to, a
| disaster which has never happened before" [0], [1].
|
| As a logical fallacy: Based on skimming the list at [2], the
| "appeal to tradition" [3, 4, 5] fallacy seems close: "claim in
| which a thesis is deemed correct on the basis of correlation
| with past or present tradition". (Aka: appeal to tradition,
| argumentum ad traditionem, argumentum ad antiquitatem, back in
| those good times, conservative bias, good old days); or, maybe:
| argument from inertia, stay the course.
|
| [0] https://en.wikipedia.org/wiki/List_of_cognitive_biases
|
| [1] https://en.wikipedia.org/wiki/Normalcy_bias
|
| [2] https://biaslist.com/?q=_lf
|
| [3] https://biaslist.com/?q=appeal+to+tradition
|
| [4] https://en.wikipedia.org/wiki/Appeal_to_tradition
|
| [5]
| https://utminers.utep.edu/omwilliamson/engl1311/fallacies.ht...
| mofeien wrote:
| Claude identifies a mix of False Analogy, Hasty Generalization,
| and Appeal to History
| salawat wrote:
| Past performance is not an indicator of future results.
|
| It underlies everything in modern society, yet seems to be one
| of the most oft lost sight of understandings on the planet
| jph00 wrote:
| That argument does not appear in the article.
|
| The article says that actually the current bill does not cover
| any models at all, and gives advice on how to change it so it
| does.
|
| It never makes any claim that AI is safe.
|
| A lot of people read what they expect to see, rather than the
| words that are actually there.
| janalsncm wrote:
| The article claims that AI is a "dual use" general purpose
| computing technology, and that it can be used for good and
| evil. To my knowledge, most technology can be used for good
| and evil depending on who is using it, so the article begs
| the question of how much of each we can reliably expect.
| janalsncm wrote:
| > These kinds of technologies, like AI models, are fundamentally
| "dual use".
|
| It is certainly true that technologies can be used for good and
| evil. But that doesn't mean that in practice good and evil
| benefit equally. "Dual use" implies a more or less equal split,
| but what about a good/bad 10/90 or 1/99 split? Technology, at its
| core, makes accomplishing certain tasks easier or harder, and
| besides the assertion of dual use, the article doesn't really
| justify AI models being equally good and bad.
|
| In the Soviet Union, a large percentage of the population was
| used for surveillance. The U.S. had surveillance too, but less.
| Technological limitations made surveilling every person
| prohibitively expensive. Police couldn't just surveil everyone.
|
| Today, surveillance is not only ubiquitous but better. It is
| possible to track millions of people in near real time. So this
| technology has caused a decrease in the cost and scalability of
| mass surveillance, which in conjunction with the third party
| doctrine (read: loophole) has the emergent effect of neutering
| the 4th amendment.
|
| What makes this hard/impossible is anticipating likely
| applications, which is why I lean towards not regulating.
| However, we should recognize the possibility of a moral hazard
| here: by shielding industry from certain consequences of their
| actions, we may make those consequences more likely in the
| future.
|
| > The general purpose computation capabilities of AI models, like
| these other technologies, is not amenable to control.
|
| Sure. And we can't stop people from posting copyrighted material
| online, but we can hold people accountable for distributing it.
| The question in my mind is whether we will have something like
| Section 230 for these models, which shields large distributors
| from first-pass liability. I don't know how that would work
| though.
| ayakang31415 wrote:
| Maybe I am naive about the progress in this space, but we should
| not use the word "AI" first because it adds to the confusion many
| people have about DNN based programs. So called AI is not much
| different from many software we're using in a sense that you give
| an input to the program, then it spits out the output. When I
| think about AI, I think of animal intelligence (no pun intended)
| that dogs or other mammals have.
| the8472 wrote:
| A spider has intelligence too. It's far more limited than a
| mammal's, but it's still on the same spectrum. And intelligence
| is not a single linear measure. AIs outperform humans on some
| tasks and are worse than rats at others. So it's more like that
| AIs have this weirdly shaped higher-dimensional capability
| surface that partially overlaps with what we consider
| intelligence. Haggling about which exact overlap gets to be
| called intelligence and which doesn't seems like...
| unproductive border-drawing on a poorly charted concept-map.
| Considering that they're getting more powerful with each year
| and such policies are about future capabilities, not just
| today's.
| ayakang31415 wrote:
| This is exactly my point about the word AI. They should not
| use the word AI to describe LLMs or any other generative
| models. Then again, words evolve to mean different things
| over time, so AI is a fine term to stick with.
| xg15 wrote:
| > _As you can see from this description, just like creating
| weights cannot be inherently dangerous (since they're just lists
| of numbers), neither can running a model be inherently dangerous
| (because they are just mathematical functions that take a list of
| numbers as an input, and create a new list of numbers as an
| output). (And again, that is not to say that running a model
| can't be used to do something harmful. Another critical technical
| distinction!)_
|
| Ah, the classic duality of big tech: Singlehandedly bringing upon
| the next stage in the evolution of mankind (to investors) while
| at the same time just tinkering in their garages on some silly,
| entirely inconsequential contraptions that do nothing more than
| turn ones and zeros into different ones and zeros (to
| regulators).
| jph00 wrote:
| You do see the words you just pasted which say "that is not to
| say that running a model can't be used to do something
| harmful", don't you?
| crabbone wrote:
| Well, one thing to keep in mind is what can be practically
| regulated and bring the desired results.
|
| Here are some examples: firearms don't kill people on their
| own, but we regulate their production as well as distribution
| and use (analogous to release and deployment in terms of the
| article). We do this because regulating use alone would be
| impractical due to enforcement. This is because we'd rather
| prevent things from happening than punish perpetrators in
| this case.
|
| Another example: we, generally, don't seek a _just_ verdict
| when suing the insurance company of the driver who caused an
| accident by hitting the back of our car. Maybe it was the
| front car driver 's fault -- the courts don't have time for
| that, and even if "unjustly" in many cases, they will still
| rule in favor of the front car driver.
|
| So, is it practical to regulate at the level of deployment?
| -- I don't know... It would seem that to be on the safe side,
| it'd be better to find a way to regulate earlier. Eg. an
| autopilot combined with a drone with a dangerous payload:
| certainly, whoever launched the drone bears responsibility,
| but similarly as with the case with guns, perhaps there
| should be regulations in place that require licensing such
| programs in a way that children or mentally ill people
| couldn't obtain them?
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