Amid a barrage of news stories warning about superintelligent machines rendering humanity extinct, a CNN story describing the opposite scenario – one in which the US military’s reliance on brittle chatbots almost brought the US into war with China – went mostly unnoticed by the public.
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reliance → warn → public
According to him, OpenAI and Anthropic are “racing straight towards self-improving superintelligence and gambling with our lives”.
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OpenAI → accord → lives
Coxon’s description of a “terminator” scenario, a machine becoming much smarter than humanity and deciding to wipe us out, captured the public, journalists’ and politicians’ attention, stirring waves of fear-inducing, credulous reporting, and policy actions.
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description → become → reporting
California governor Gavin Newsom issued a mandate to create an “AI kill-switch”; New York governor Kathy Hochul is similarly exploring the possibility of having “AI kill-switches”; and Senator Bernie Sanders and Congressman Greg Casar introduced legislation to “ban artificial superintelligence”.
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Sanders → issue → superintelligence
While so many of us were focused on fictional superintelligent machines that we were told could hypothetically cause human extinction, however, there was a more serious story being reported.
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we → focus → extinction
A series of events almost got us to armageddon, not caused by “rogue, superintelligent AI”, but by government reliance on error-prone systems that are marketed by their manufacturers as being close to superintelligent.
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that → get → manufacturers
A CNN report published on 18 September, which hasn’t been verified by other major outlets, describes how the US “almost started a war” with China, based on an intelligence report that claimed a Chinese ship was transporting components of nuclear weapons.
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ship → publish → weapons
Military personnel made plans to intercept the Chinese vessel, complete with aircraft and soldiers ready to board the ship.
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aircraft → make → ship
A military skirmish of this kind between China and the US could quickly escalate and spiral into world war three.
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skirmish → escalate → war
It was only moments before executing on the plan that American officials further investigated the intelligence report and found that it had been generated with the use of a chatbot and contained erroneous information about the vessel’s contents.
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it → execute → contents
Unlike the terminator, “rogue AI”, scenario, this incident didn’t galvanize lawmakers into announcing calls for regulation so as to avoid potential human extinction.
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incident → galvanize → extinction
Media outlet after media outlet didn’t warn the public that we almost triggered a war against a nuclear superpower because of our military’s reliance on error-prone chatbots.
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we → warn → chatbots
We describe the large language models (LLMs) powering these chatbots as stochastic parrots, that is, models that are designed to regurgitate the patterns of the data they are trained on.
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they → describe → data
News coverage describing them as “powerful” “rogue” models that could render humanity extinct all on their own, bolsters perceptions of tools based on these models being infallible enough to merit usage in stakes as high as warfare.
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models → describe → warfare
Even CNN’s more critical coverage describes the chatbot used by the US military as presenting “profound risks” because it is “powerful, new and relatively poorly understood technology”.
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it → describe → risks
In fact, today’s LLMs and the chatbots they power are not poorly understood, nor are they powerful in the sense of being effective tools for this use case.
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they → power → case
They are systems for generating plausible looking text, built out of enormous, haphazardly collected datasets and then “fine-tuned” (that is, further trained) to be especially appealing to their intended users.
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that → generate → users
CNN wasn’t able to learn which chatbot product was used in this case, but the LLM powering the product was likely fine-tuned to output text with the stylistic hallmarks of intelligence reports.
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LLM → learn → reports
Both the basic functionality and the risks of such a model have been well-understood and well-documented for years, including in our 2021 paper On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?
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Models → understand → Parrots
Claims that system behavior is mysterious arise from deliberate mystification on the part of those selling those systems, and a misapprehension of what their output is by those procuring and using it.
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output → arise → it
Unlike the unscientific and fantastical claims of OpenAI and Anthropic CEOs and those who uncritically repeat their talking points, the harmful, and well-documented, impacts of these companies’ products have arisen because people believe that the products are superintelligent, not because they actually are.
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they → repeat → products
From “AI” scribes used by hospitals erroneously classifying patients as illicit drug users, to governments killing children after relying on “intelligence analysis” systems which mistake schools for military facilities, we are seeing the predictable harms that come from misplaced faith in unreliable automated software.
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that → use → software
Meanwhile, the marketing campaigns from the companies selling this software warn of impending superintelligence, directing our attention away from the real risk to their fantasies of doom.
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campaigns → sell → doom
It is high time for us to regulate usage of systems sold as “AI”, not because they are magical machines, but because they are error-prone products that shouldn’t be used in high stakes scenarios.
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that → regulate → scenarios
Any automation used in military, medical or other life-and-death situations must be thoroughly evaluated within its use case and paired with usage norms that keep accountability with people who have actual power to make decisions.
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who → use → decisions
As former FTC chair Lina Khan has repeatedly reminded us, there is no exemption to the law when it comes to AI: there are existing laws that federal agencies and other regulators can enforce to protect the public against the AI industry’s unsafe and unscientific practices of pushing unsound products while marketing them as “magic intelligence in the sky”.
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agencies → remind → sky
Going along with company executives and describing their products as beings with agency allows these executives to evade accountability while deceiving the public.
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executives → go → public
We call on journalists and lawmakers to hold companies accountable rather than parrot their marketing talking points.
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companies → call → points
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Timnit Gebru is executive director of Dair and author of the forthcoming book Deep Unlearning: The Radicalization of a Tech Idealist, which is available for preorders now and set to publish on 16 February.
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which → set → February
The Aporia
