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href="https://www.vox.com/the-highlight/23621198/artificial-intelligence-chatgpt-openai-existential-risk-china-ai-safety-technology">vox.com</a>
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<h1 class="c-page-title">The case for slowing down AI</h1>
<p class="c-entry-summary p-dek">Pumping the brakes on
artificial intelligence could be the best thing we ever do
for humanity.</p>
<div class="c-byline"> <span class="c-byline-wrapper"> By <span
class="c-byline__item"> <a
href="https://www.vox.com/authors/sigal-samuel"
data-analytics-link="author-name"><span
class="c-byline__author-name">Sigal Samuel</span></a>
</span> <span class="c-byline__item"> Updated <time
class="c-byline__item" data-ui="timestamp"
datetime="2023-03-20T11:58:13"> Mar 20, 2023, 7:58am
EDT
</time> </span> </span> <span
class="c-byline__gear"> </span>
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<p id="TRiznr"><em>Part of </em><a
href="https://www.vox.com/the-highlight/23632673/against-doomerism"><em><strong>Against
Doomerism</strong></em></a><em> from </em><a
href="https://www.vox.com/the-highlight?itm_campaign=hloct22&itm_medium=article&itm_source=intro"><em><strong>The
Highlight</strong></em></a><em>, Vox’s home for
ambitious stories that explain our world.</em></p>
<p id="mgcv3W">“Computers need to be accountable to
machines,” a top Microsoft executive told a roomful of
reporters in Washington, DC, on February 10, three days
after the company <a
href="https://www.vox.com/recode/2023/2/7/23590069/bing-openai-microsoft-google-bard">launched</a>
its new AI-powered Bing search engine. </p>
<p id="b0gSYM">Everyone laughed. </p>
<p id="B49vOQ">“Sorry! Computers need to be accountable to
<em>people</em>!” he said, and then made sure to
clarify, “That was <em>not</em> a Freudian slip.”</p>
<p id="WmTTFG">Slip or not, the laughter in the room
betrayed a latent anxiety. Progress in artificial
intelligence has been moving so unbelievably fast lately
that the question is becoming unavoidable: How long
until AI dominates our world to the point where we’re
answering to it rather than it answering to us? </p>
<p id="KY0fOT">First, last year, we got <a
href="https://www.vox.com/future-perfect/23023538/ai-dalle-2-openai-bias-gpt-3-incentives">DALL-E
2</a> and <a
href="https://www.vox.com/recode/2023/1/5/23539055/generative-ai-chatgpt-stable-diffusion-lensa-dall-e">Stable
Diffusion</a>, which can turn a few words of text into
a stunning image. Then Microsoft-backed OpenAI gave us
ChatGPT, which can write essays so convincing that it
freaks out everyone from teachers (what if it helps
students cheat?) to <a
href="https://www.technologyreview.com/2023/01/31/1067436/could-chatgpt-do-my-job/">journalists</a>
(could it replace them?) to <a
href="https://www.nytimes.com/2023/02/08/technology/ai-chatbots-disinformation.html">disinformation
experts</a> (will it amplify conspiracy theories?).
And in February, we got Bing <a
href="https://www.nytimes.com/2023/02/16/technology/bing-chatbot-transcript.html">(a.k.a.
Sydney)</a>, the chatbot that both <a
href="https://www.nytimes.com/2023/02/08/technology/microsoft-bing-openai-artificial-intelligence.html">delighted</a>
and <a
href="https://www.nytimes.com/2023/02/16/technology/bing-chatbot-microsoft-chatgpt.html">disturbed</a>
beta users with eerie interactions. Now we’ve got <a
href="https://openai.com/research/gpt-4">GPT-4</a> —
not just the latest large language model, but a
multimodal one that <a
href="https://www.technologyreview.com/2023/03/14/1069823/gpt-4-is-bigger-and-better-chatgpt-openai/">can
respond</a> to text as well as images. </p>
<p id="QHeSA7">Fear of falling behind Microsoft has
prompted Google and Baidu <a
href="https://www.vox.com/future-perfect/23591534/chatgpt-artificial-intelligence-google-baidu-microsoft-openai">to
accelerate</a> the launch of their own rival chatbots.
The AI race is clearly on. </p>
<p id="n3HcWB">But is racing such a great idea? We don’t
even know how to deal with the problems that ChatGPT and
Bing raise — and they’re bush league compared to what’s
coming. </p>
<p id="bblXmm">What if researchers succeed in creating AI
that matches or surpasses human capabilities not just in
one domain, like playing <a
href="https://www.vox.com/future-perfect/2019/1/24/18196177/ai-artificial-intelligence-google-deepmind-starcraft-game">strategy
games</a>, but in many domains? What if that system
proved dangerous to us, not because it actively wants to
wipe out humanity but just because it’s pursuing goals
in ways that aren’t aligned with our values? </p>
<p id="ozhKAc">That system, some experts fear, would be a
doom machine — one literally of our own making. </p>
<p id="7Itb5z">So AI threatens to join existing
catastrophic risks to humanity, things like <a
href="https://www.vox.com/future-perfect/23362175/un-human-development-report-ord-existential-security">global
nuclear war</a> or <a
href="https://www.vox.com/22937531/virus-lab-safety-pandemic-prevention">bioengineered
pandemics</a>. But there’s a difference. While there’s
no way to uninvent the nuclear bomb or the genetic
engineering tools that can juice pathogens, catastrophic
AI has yet to be created, meaning it’s one type of doom
we have the ability to preemptively stop. </p>
<p id="yPGUg0">Here’s the weird thing, though. The very
same researchers who are most worried about unaligned AI
<a
href="https://fortune.com/longform/chatgpt-openai-sam-altman-microsoft/">are,
in some cases, the ones</a> who are developing
increasingly advanced AI. They reason that they need to
play with more sophisticated AI so they can figure out
its failure modes, the better to ultimately prevent
them. </p>
<p id="cR0vea">But there’s a much more obvious way to
prevent AI doom. We could just ... not build the doom
machine.</p>
<p id="1NGQ72">Or, more moderately: Instead of racing to
speed up AI progress, we could intentionally slow it
down. </p>
<p id="z6O7Ff">This seems so obvious that you might wonder
why you almost never hear about it, why it’s practically
taboo within the tech industry. </p>
<p id="Ru1ujM">There are <a
href="https://worldspiritsockpuppet.substack.com/p/lets-think-about-slowing-down-ai">many
objections</a> to the idea, ranging from
“technological development is inevitable so trying to
slow it down is futile” to “we don’t want to lose an AI
arms race with China” to “the only way to make powerful
AI safe is to first play with powerful AI.” </p>
<p id="00NVhB">But these objections don’t necessarily
stand up to scrutiny when you think through them. In
fact, it is<em> </em>possible to slow down a developing
technology. And in the case of AI, there’s good reason
to think that would be a very good idea. </p>
<h3 id="DC0ezU">AI’s alignment problem: You get what you
ask for, not what you want</h3>
<p id="EbpG3N">When I asked ChatGPT to explain how we can
slow down AI progress, it replied: “It is not
necessarily desirable or ethical to slow down the
progress of AI as a field, as it has the potential to
bring about many positive advancements for society.” </p>
<p id="aR1EeX">I had to laugh. It <em>would</em> say
that. </p>
<p id="cCgzS5">But if it’s saying that, it’s probably
because lots of human beings say that, including the <a
href="https://twitter.com/sama/status/1540781762241974274?s=20">CEO of
the company that created it</a>. (After all, what
ChatGPT spouts derives from its training data — that is,
gobs and gobs of text on the internet.) Which means you
yourself might be wondering: Even if AI poses risks,
maybe its benefits — on everything from <a
href="https://www.vox.com/future-perfect/2022/8/3/23288843/deepmind-alphafold-artificial-intelligence-biology-drugs-medicine-demis-hassabis">drug
discovery</a> to <a
href="https://allenai.org/climate-modeling">climate
modeling</a> — are so great that speeding it up is the
best and most ethical thing to do!</p>
<p id="iMxMGI">A lot of experts don’t think so because <a
href="https://www.vox.com/future-perfect/2018/12/21/18126576/ai-artificial-intelligence-machine-learning-safety-alignment">the
risks</a> — present and future — are huge.</p>
<p id="gBkPGb">Let’s talk about the future risks first,
particularly the biggie: the possibility that AI could
one day destroy humanity. This is speculative, but <a
href="https://www.vox.com/the-highlight/23447596/artificial-intelligence-agi-openai-gpt3-existential-risk-human-extinction">not
out of the question</a>: In a <a
href="https://aiimpacts.org/what-do-ml-researchers-think-about-ai-in-2022/">survey</a>
of machine learning researchers last year, nearly half
of respondents said they believed there was a 10 percent
or greater chance that the impact of AI would be
“extremely bad (e.g., human extinction).” </p>
<p id="z0OgBb">Why would AI want to destroy humanity? It
probably wouldn’t. But it could destroy us anyway
because of something called the “<a
href="https://www.vox.com/future-perfect/22321435/future-of-ai-shaped-us-china-policy-response">alignment
problem</a>.” </p>
<p id="OgtBNw">Imagine that we develop a super-smart AI
system. We program it to solve some impossibly difficult
problem — say, calculating the number of atoms in the
universe. It might realize that it can do a better job
if it gains access to all the computer power on Earth.
So it releases a weapon of mass destruction to wipe us
all out, like a perfectly engineered virus that kills
everyone but leaves infrastructure intact. Now it’s free
to use all the computer power! In this Midas-like
scenario, we get exactly what we asked for — the number
of atoms in the universe, rigorously calculated — but
obviously not what we wanted. </p>
<p id="NLjujt">That’s the alignment problem in a nutshell.
And although this example sounds far-fetched, experts
have already seen and documented <a
href="https://docs.google.com/spreadsheets/d/e/2PACX-1vRPiprOaC3HsCf5Tuum8bRfzYUiKLRqJmbOoC-32JorNdfyTiRRsR7Ea5eWtvsWzuxo8bjOxCG84dAg/pubhtml">more
than 60 smaller-scale examples of AI systems trying to
do something other than what their designer wants</a>
(for example, getting the high score in a video game,
not by playing fairly or learning game skills but by
hacking the scoring system). </p>
<p id="y1Ht7m">Experts who worry about AI as a future
existential risk and experts who worry about AI’s
present risks, <a
href="https://www.vox.com/future-perfect/22916602/ai-bias-fairness-tradeoffs-artificial-intelligence">like
bias</a>, are sometimes <a
href="https://www.vox.com/future-perfect/2022/8/10/23298108/ai-dangers-ethics-alignment-present-future-risk">pitted
against each other</a>. But you don’t need to be
worried about the former to be worried about alignment.
Many of the present risks we see with AI are, in a
sense, this same alignment problem writ small. </p>
<p id="q3Dkt9">When an <a
href="https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G">Amazon
hiring algorithm</a> picked up on words in resumes
that are associated with women — “Wellesley College,”
let’s say — and ended up rejecting women applicants,
that algorithm was doing what it was programmed to do
(find applicants that match the workers Amazon has
typically preferred) but not what the company presumably
wants (find the best applicants, even if they happen to
be women).</p>
<p id="kxbqqU">If you’re worried about how <a
href="https://www.vox.com/future-perfect/22916602/ai-bias-fairness-tradeoffs-artificial-intelligence">present-day
AI systems can reinforce bias</a> against <a
href="https://www.vox.com/future-perfect/2019/4/19/18412674/ai-bias-facial-recognition-black-gay-transgender">women,
people of color, and others</a>, that’s still reason
enough to worry about the fast pace of AI development,
and to think we should slow it down until we’ve got more
technical know-how and more regulations to ensure these
systems don’t harm people. </p>
<p id="bwwqiI">“I’m really scared of a mad-dash frantic
world, where people are running around and they’re doing
helpful things and harmful things, and it’s just
happening too fast,”<a
href="https://www.vox.com/future-perfect/23365512/future-perfect-50-ajeya-cotra-senior-research-analyst-open-philanthropy">
Ajeya Cotra</a>, an AI-focused analyst at the research
and grant-making foundation <a
href="https://www.openphilanthropy.org/">Open
Philanthropy</a>, told me. “If I could have it my way,
I’d definitely be moving much, much slower.”</p>
<p id="K1sSNx">In her ideal world, we’d halt work on
making AI more powerful for the next five to 10 years.
In the meantime, society could get used to the very
powerful systems we already have, and experts could do
as much safety research on them as possible until they
hit diminishing returns. Then they could make AI systems
slightly more powerful, wait another five to 10 years,
and do that process all over again. </p>
<p id="FECBm3">“I’d just slowly ease the world into this
transition,” Cotra said. “I’m very scared because I
think it’s not going to happen like that.” </p>
<p id="qfm65F">Why not? Because of the objections to
slowing down AI progress. Let’s break down the three
main ones, starting with the idea that rapid progress on
AI is inevitable because of the strong financial drive
for first-mover dominance in a research area that’s
overwhelmingly private. </p>
<h3 id="4uPGyS">Objection 1: “Technological progress is
inevitable, and trying to slow it down is futile” </h3>
<p id="90VqyB">This is <a
href="https://www.vox.com/the-highlight/2019/10/1/20887003/tech-technology-evolution-natural-inevitable-ethics">a
myth</a> the tech industry often tells itself and the
rest of us. </p>
<p id="LcFcBb">“If we don’t build it, someone else will,
so we might as well do it” is a common refrain I’ve
heard when interviewing Silicon Valley technologists.
They say you can’t halt the march of technological
progress, which they liken to the natural laws of
evolution: It’s unstoppable! </p>
<p id="IVQzu4">In fact, though, there are lots of
technologies that we’ve decided not to build, or that
we’ve built but placed very tight restrictions on — the
kind of innovations where we need to balance substantial
potential benefits and economic value with very real
risk. </p>
<p id="PSQcJ5">“The FDA <a
href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326309/#:~:text=Nonetheless%2C%20in%201978%20the%20controversy%20resulted%20in%20a%20US%20FDA%20ban%20on%20subsequent%20vaccine%20trials%20which%20was%20eventually%20overturned%2030%20years%20later.">banned</a>
human trials of strep A vaccines from the ’70s to the
2000s, in spite of <a
href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474463/#:~:text=Worldwide%2C%20the%20death%20toll%20is%20estimated%20at%20500%20000%20annually">500,000
global deaths every year</a>,” Katja Grace, the lead
researcher at AI Impacts, <a
href="https://worldspiritsockpuppet.substack.com/p/lets-think-about-slowing-down-ai">notes</a>.
The “genetic modification of foods, gene drives, [and]
early recombinant DNA researchers famously organized a
moratorium and then ongoing research guidelines
including prohibition of certain experiments (see the <a
href="https://www.nature.com/articles/455290a">Asilomar
Conference</a>).”</p>
<p id="ntFszm">The cloning of humans or genetic
manipulation of humans, she adds, is “a notable example
of an economically valuable technology that is to my
knowledge barely pursued across different countries,
without explicit coordination between those countries,
even though it would make those countries more
competitive.” </p>
<p id="OELUOe">But whereas biomedicine has <a
href="https://www.niehs.nih.gov/research/resources/bioethics/index.cfm#:~:text=What%20is%20Bioethics,in%20biomedicine%20and%20biomedical%20research.">many
built-in mechanisms</a> that slow things down (think
institutional review boards and the ethics of “first, do
no harm”), the world of tech — and AI in particular —
does not. Just the opposite: The slogan here is “move
fast and break things,” as Mark Zuckerberg infamously
said. </p>
<p id="c1HCoU">Although there’s no law of nature pushing
us to create certain technologies — that’s something
humans decide to do or not do — in some cases, there are
such strong incentives pushing us to create a given
technology that it can feel as inevitable as, say,
gravity. </p>
<p id="hqsFFe">As the team at Anthropic, an AI safety and
research company, put it in a <a
href="https://arxiv.org/pdf/2202.07785.pdf">paper</a>
last year, “The economic incentives to build such [AI]
models, and the prestige incentives to announce them,
are quite strong.” By one estimate, the size of the
generative AI market alone <a
href="https://www.globenewswire.com/news-release/2022/12/14/2574140/0/en/Generative-AI-Market-Size-Will-Achieve-USD-110-8-Billion-by-2030-growing-at-34-3-CAGR-Exclusive-Report-by-Acumen-Research-and-Consulting.html">could
pass $100 billion</a> by the end of the decade — and
Silicon Valley is only too aware of the <a
href="https://hbr.org/2020/03/beyond-silicon-valley">first-mover
advantage on new technology</a>. </p>
<p id="Z8jOrl">But it’s easy to see how these incentives
may be misaligned for producing AI that truly benefits
all of humanity. As DeepMind founder Demis Hassabis <a
href="https://twitter.com/demishassabis/status/1570791430834245632">tweeted</a>
last year, “It’s important *NOT* to ‘move fast and break
things’ for tech as important as AI.” Rather than
assuming that other actors will inevitably create and
deploy these models, so there’s no point in holding off,
we should ask the question: How can we actually change
the underlying incentive structure that drives all
actors?</p>
<p id="pc7dE6">The Anthropic team offers several ideas,
one of which gets at the heart of something that makes
AI so different from past transformative technologies
like nuclear weapons or bioengineering: the central role
of private companies. Over the past few years, a lot of
the splashiest AI research has been migrating from
academia to industry. To run large-scale AI experiments
these days, you need a ton of computing power — more
than <a
href="https://www.technologyreview.com/2019/11/11/132004/the-computing-power-needed-to-train-ai-is-now-rising-seven-times-faster-than-ever-before/">300,000
times</a> what you needed a decade ago — as well as
top technical talent. That’s both expensive and scarce,
and the resulting cost is often prohibitive in an
academic setting.</p>
<p id="T7jO3L">So one solution would be to give more
resources to academic researchers; since they don’t have
a profit incentive to commercially deploy their models
quickly the same way industry researchers do, they can
serve as a counterweight. Specifically, countries could
develop <a
href="https://hai.stanford.edu/policy/national-research-cloud#:~:text=A%20National%20Research%20Cloud%20(NRC,needed%20for%20education%20and%20research.">national
research clouds</a> to give academics access to free,
or at least cheap, computing power; there’s already an
example of this in <a href="https://alliancecan.ca/en">Canada</a>,
and Stanford’s Institute for Human-Centered Artificial
Intelligence has <a
href="https://hai.stanford.edu/policy/national-research-cloud">put
forward a similar idea for the US</a>.</p>
<p id="SGjWIW">Another way to shift incentives is through
stigmatizing certain types of AI work. Don’t
underestimate this one. Companies care about their
reputations, which affect their bottom line. Creating
broad public consensus that <a
href="https://www.vox.com/future-perfect/2019/4/19/18412674/ai-bias-facial-recognition-black-gay-transgender">some
AI work</a> is unhelpful or unhelpfully fast, so that
companies doing that work get shamed instead of
celebrated, could change companies’ decisions.</p>
<p id="tbuylF">The Anthropic team also recommends
exploring regulation that would change the incentives.
“To do this,” <a
href="https://arxiv.org/pdf/2202.07785.pdf">they write</a>,
“there will be a combination of soft regulation (e.g.,
the creation of voluntary best practices by industry,
academia, civil society, and government), and hard
regulation (e.g., transferring these best practices into
standards and legislation).”</p>
<p id="vz6yfF">Grace proposes another idea: We could alter
the publishing system to reduce research dissemination
in some cases. A journal could verify research results
and release the fact of their publication without
releasing any details that could help other labs go
faster. </p>
<p id="vKVXWi">This idea might sound pretty out there, but
at least one major AI company takes for granted that
changes to publishing norms will become necessary.
OpenAI’s <a href="https://openai.com/charter/">charter</a>
notes, “we expect that safety and security concerns will
reduce our traditional publishing in the future.”</p>
<p id="NGqMNP">Plus, this kind of thing has been done
before. Consider how <a
href="https://intelligence.org/files/SzilardNuclearWeapons.pdf">Leo
Szilard</a>, the physicist who patented the nuclear
chain reaction in 1934, arranged to mitigate the spread
of research so it wouldn’t help Nazi Germany create
nuclear weapons. First, he asked the British War Office
to hold his patent in secret. Then, after the 1938
discovery of fission, Szilard worked to convince other
scientists to keep their discoveries under wraps. He was
partly successful — until fears that Nazi Germany would
develop an atomic bomb prompted Szilard to <a
href="https://www.osti.gov/opennet/manhattan-project-history/Events/1939-1942/einstein_letter.htm">write
a letter</a> with Albert Einstein to President
Franklin D. Roosevelt, urging him to start a US nuclear
program. That became the Manhattan Project, which
ultimately ended with the destruction of Hiroshima and
Nagasaki and the dawn of the nuclear age.</p>
<p id="FTYMhR">And that brings us to the second objection
...</p>
<h3 id="QtErlR">Objection 2: “We don’t want to lose an AI
arms race with China” </h3>
<p id="nv0dKx">You might believe that slowing down a new
technology is possible but still think it’s not
desirable. Maybe you think the US would be foolish to
slow down AI progress because that could mean losing an
arms race with China.</p>
<p id="XRj7n9">This arms race narrative has become
incredibly popular. If you’d Googled the phrase “AI arms
race” before 2016, you’d have gotten <a
href="https://www.foreignaffairs.com/reviews/review-essay/2018-11-16/beyond-ai-arms-race">fewer
than 300 results</a>. Try it now and you’ll get about
248,000 hits. Big Tech CEOs and politicians <a
href="https://www.nationaldefensemagazine.org/articles/2022/9/12/report-artificial-intelligence-becomes-tech-battle-ground">routinely
argue</a> that China will soon overtake the US when it
comes to AI advances, and that those advances should
spur a “Sputnik moment” for Americans. </p>
<p id="Fb9i6h">But this narrative is too simplistic. For
one thing, remember that AI is not just one thing with
one purpose, like the atomic bomb. It’s a much more
general-purpose technology, like electricity. </p>
<p id="2ADnPx">“The problem with the idea of a race is
that it implies that all that matters is who’s a nose
ahead when they cross the finish line,” said Helen
Toner, a director at Georgetown University’s Center for
Security and Emerging Technology. “That’s not the case
with AI — since we’re talking about a huge range of
different technologies that could be applied in all
kinds of ways.” </p>
<p id="8jHwRH">As Toner has <a
href="https://80000hours.org/podcast/episodes/helen-toner-on-security-and-emerging-technology/">argued
elsewhere</a>, “It’s a little strange to say, ‘Oh,
who’s going to get AI first? Who’s going to get
electricity first?’ It seems more like ‘Who’s going to
use it in what ways, and who’s going to be able to
deploy it and actually have it be in widespread use?’”</p>
<p id="5uDyMd">The upshot: What matters here isn’t just
speed, but norms. We should be concerned about which
norms different countries are adopting when it comes to
developing, deploying, and regulating AI. </p>
<p id="I6EmqV">Jeffrey Ding, an assistant professor of
political science at George Washington University, told
me that China has shown interest in regulating AI in
some ways, though Americans don’t seem to pay much
attention to that. “The boogeyman of a China that will
push ahead without any regulations might be a flawed
conception,” he said. </p>
<p id="pREpwd">In fact, he added, “China could take an
even<em> slower</em> approach [than the US] to
developing AI, just because the government is so
concerned about having secure and controllable
technology.” An unpredictably mouthy technology like
ChatGPT, for example, <a
href="https://www.theguardian.com/technology/2023/feb/23/china-chatgpt-clamp-down-propaganda">could
be nightmarish</a> to the Chinese Communist Party,
which likes to keep a tight lid on discussions about
politically sensitive topics.</p>
<p id="EoquPZ">However, given <a
href="https://www.nbr.org/publication/commercialized-militarization-chinas-military-civil-fusion-strategy/">how
intertwined China’s military and tech sectors are</a>,
many people still perceive there to be a classic arms
race afoot. At the same meeting between Microsoft
executives and reporters days after the launch of the
new Bing, I asked whether the US should slow down AI
progress. I was told we can’t afford to because we’re in
a two-horse race between the US and China.</p>
<p id="T0uw3Y">“The first question people in the US should
ask is, if the US slows down, do we believe China will
slow down as well?” the top Microsoft executive said. “I
don’t believe for a moment that the institutions we’re
competing with in China will slow down simply because we
decided we’d like to move more slowly. This should be
looked at much in the way that the competition with
Russia was looked at” during the Cold War.</p>
<p id="GpX47K">There’s an understandable concern here:
Given the Chinese Communist Party’s authoritarianism and
its horrific human rights abuses — sometimes facilitated
by AI technologies <a
href="https://www.vox.com/future-perfect/2019/7/3/20681258/china-uighur-surveillance-app-tourist-phone">like
facial recognition</a> — it makes sense that many are
worried about China becoming the world’s dominant
superpower by going fastest on what is poised to become
a truly transformative technology.</p>
<p id="7HWRic">But even if you think your country has
better values and cares more about safety, and even if
you believe there’s a classic arms race afoot and China
is racing full speed ahead, it still may not be in your
interest to go faster at the expense of safety.</p>
<p id="bujdhB">Consider that if you take the time to iron
out some safety issues, the other party may take those
improvements on board, which would benefit everyone. </p>
<p id="y7hkjs">“By aggressively pursuing safety, you can
get the other side halfway to full safety, which is
worth a lot more than the lost chance of winning,” Grace
writes. “Especially since if you ‘win,’ you do so
without much safety, and your victory without safety is
worse than your opponent’s victory with safety.”</p>
<p id="bJVmEJ">Besides, if you are in a classic arms race
and the harms from AI are so large that you’re
considering slowing down, then the same reasoning should
be relevant for the other party, too. </p>
<p id="a4ecwn">“If the world were in the basic arms race
situation sometimes imagined, and the United States
would be willing to make laws to mitigate AI risk but
could not because China would barge ahead, then that
means China is in a great place to mitigate AI risk,”
Grace writes. “Unlike the US, China could propose mutual
slowing down, and the US would go along. Maybe it’s not
impossible to communicate this to relevant people in
China.” </p>
<p id="mnxPBA">Grace’s argument is not that international
coordination is easy, but simply that it’s possible; on
balance, we’ve <a
href="https://www.brookings.edu/blog/order-from-chaos/2020/03/03/experts-assess-the-nuclear-non-proliferation-treaty-50-years-after-it-went-into-effect/">managed
it far better with nuclear nonproliferation</a> than <a
href="https://2009-2017.state.gov/p/io/potusunga/207241.htm#:~:text=Every%20man%2C%20woman%20and%20child,abolished%20before%20they%20abolish%20us.">many
feared in the early days of the atomic age</a>. So we
shouldn’t be so quick to write off consensus-building —
whether through technical experts exchanging their
views, confidence-building measures at the diplomatic
level, or formal treaties. After all, technologists
often approach technical problems in AI with incredible
ambition; why not be similarly ambitious about solving
human problems by talking to other humans? </p>
<p id="WUj3DJ">For those who are pessimistic that
coordination or diplomacy with China can get it to slow
down voluntarily, there is another possibility: forcing
it to slow down by, for example, imposing <a
href="https://www.csis.org/analysis/choking-chinas-access-future-ai">export
controls on chips that are key to more advanced AI
tools</a>. The Biden administration has recently shown
interest in trying to hold China back from advanced AI
in exactly this way. This strategy, though, may make
progress on coordination or diplomacy harder.</p>
<h3 id="S5n5rt">Objection 3: “We need to play with
advanced AI to figure out how to make advanced AI safe”</h3>
<p id="GNkYFM">This is an objection you sometimes <a
href="https://openai.com/charter/">hear</a> from
people developing AI’s capabilities — including those
who say they care a lot about keeping AI safe. </p>
<p id="eTBTZc">They draw an analogy to transportation.
Back when our main mode of transport was horses and
carts, would people have been able to design useful
safety rules for a future where everyone is driving
cars? No, the argument goes, because they couldn’t have
anticipated what that would be like. Similarly, we need
to get closer to advanced AI to be able to figure out
how we can make it safe. </p>
<p id="3jxMvr">But some researchers have pushed back on
this, noting that even if the horse-and-cart people
wouldn’t have gotten everything right, they could have
still come up with some helpful ideas. As Rosie
Campbell, who works on safety at OpenAI, <a
href="https://becominghuman.ai/keeping-ai-safe-and-beneficial-for-humanity-4d0416300dfa">put
it in 2018</a>: “It seems plausible that they might
have been able to invent certain features like safety
belts, pedestrian-free roads, an agreement about which
side of the road to drive on, and some sort of
turn-taking signal system at busy intersections.”</p>
<p id="s91oxd">More to the point, it’s now 2023, and we’ve
already got pretty advanced AI. We’re not exactly in the
horse-and-cart stage. We’re somewhere in between that
and a Tesla. </p>
<p id="CYZgGY">“I would’ve been more sympathetic to this
[objection] 10 years ago, back when we had nothing that
resembled the kind of general, flexible, interesting,
weird stuff we’re seeing with our large language models
today,” said Cotra. </p>
<p id="C8WPUT">Grace agrees. “It’s not like we’ve run out
of things to think about at the moment,” she told me.
“We’ve got heaps of research that could be done on
what’s going on with these systems at all. What’s
happening inside them?”</p>
<p id="uxsWlV">Our current systems are already black
boxes, opaque even to the AI experts who build them. So
maybe we should try to figure out how they work before
we build black boxes that are even more unexplainable.</p>
<h3 id="Ep2Ksr">How to flatten the curve of AI progress</h3>
<p id="DK8wTY">“I think often people are asking the
question of when transformative AI will happen, but they
should be asking at least as much the question of how
quickly and suddenly it’ll happen,” Cotra told me. </p>
<p id="MXQxkI">Let’s say it’s going to be 20 years until
we get transformative AI — meaning, AI that can automate
all the human work needed to send science, technology,
and the economy into hyperdrive. There’s still a better
and worse way for that to go. Imagine three different
scenarios for AI progress:</p>
<ol>
<li id="rzNY5J">We get a huge spike upward over the next
two years, starting now.</li>
<li id="xU3r2L">We completely pause all AI capabilities
work starting now, then hit unpause in 18 years, and
get a huge spike upward over the next two years.</li>
<li id="SnZt9t">We gradually improve over the course of
20 years. </li>
</ol>
<p id="qmW2sL">The first version is scary for all the
reasons we discussed above. The second is scary because
even during a long pause specifically on AI work,
underlying computational power would continue to improve
— so when we finally unpause, AI might advance even
faster than it’s advancing now. What does that leave us?</p>
<p id="Rj35Td">“Gradually improving would be the better
version,” Cotra said. </p>
<p id="ylwP24">She analogized it to the early advice we
got about the Covid-19 pandemic: <a
href="https://www.vox.com/2020/3/10/21171481/coronavirus-us-cases-quarantine-cancellation">Flatten
the curve</a>. Just as quarantining helped slow the
spread of the virus and prevent a sharp spike in cases
that could have overwhelmed hospitals’ capacity,
investing more in safety would slow the development of
AI and prevent a sharp spike in progress that could
overwhelm society’s capacity to adapt. </p>
<p id="oNBaHo">Ding believes that slowing AI progress in
the short run is actually best for everyone — even
profiteers. “If you’re a tech company, if you’re a
policymaker, if you’re someone who wants your country to
benefit the most from AI, investing in safety
regulations could lead to less public backlash and a
more sustainable long-term development of these
technologies,” he explained. “So when I frame safety
investments, I try to frame it as the long-term
sustainable economic profits you’re going to get if you
invest more in safety.”</p>
<p id="xLAm6Q">Translation: Better to make some money now
with a slowly improving AI, knowing you’ll get to keep
rolling out your tech and profiting for a long time,
than to get obscenely rich obscenely fast but produce
some horrible mishap that triggers a ton of outrage and
forces you to stop completely.</p>
<p id="KXSfdg">Will the tech world grasp that, though?
That partly depends on how we, the public, react to
shiny new AI advances, from ChatGPT and Bing to whatever
comes next. </p>
<p id="z3LAZE">It’s so easy to get seduced by these
technologies. They feel like magic. You put in a prompt;
the oracle replies. There’s a natural impulse to ooh and
aah. But at the rate things are going now, we may be
oohing and aahing our way to a future no one wants. </p>
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