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OPINION
Artificial intelligence

Smarter machines risk creating
dumber humans
The exciting and impressive use of new, powerful AI models could cause
harm to individuals and society
JOHN THORNHILL

W

henoneofGoogle’s
senior researchers asked
thecompany’s
LaMDA
chatbot whether it was a“philosophical zombie” (exhibiting
human-like behaviour without having
any inner life, consciousness orsentience) it replied: “Of course not.”Unconvinced, Blaise Aguera y Arcas
asked the AI-enabled chatbot how
he could know this was true. “You’ll
just have to take my word for it. You
can’t ‘prove’ you’re not a philosophicalzombie either,” LaMDA answered.
Our machines are becoming smarter— and sassier — at astonishing andunnerving speed. LaMDA is one ofa new generation of large language,
or foundation, models, which use
machine learning techniques to identify
patterns of words in vast data sets
and automatically replicate them on
demand. They operate like speedy
auto-complete functions, but with noinstinctive or acquired preferences,no memory and no sense of history oridentity. “LaMDA is indeed, to use ablunt (if admittedly, humanising) term,bullshitting,” Aguera y Arcas wrote.
When OpenAI, a San Francisco-based
research company, launched one of thefirst foundation models, called GPT-3,
in 2020 it stunned many users with its
ability to generate reams of plausible
text at remarkable speed. Since then,such models have become bigger andmore powerful, expanding from text tocomputer code, images and video, too.
They are also emerging from shelteredresearch environments into the wildsof the real world and are increasingly
being deployed in marketing, finance,
scientific research and healthcare. The
critical question is how closely thesetechnological tools should be controlled.

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The risk is that smarter machines may
only make dumber humans.
The technology’s positive commercial
uses are highlighted by Kunle Olukotun,
a Stanford University professor andco-founder of SambaNova Systems, aSilicon Valley start-up that helps clients
deploy AI. “The pace of innovationand the size of the models is increasing
dramatically,” he says. “Just when youthought that we were reaching ourlimits, people come up with new tricks.”
Not only can these new models
generate text and images but interpretthem too. This enables the same system
to learn in different contexts andhandle multiple tasks. For example,
Hungary’s OTP bank is working with thegovernment and SambaNova to deploy
AI-powered services across its business.
The bank aims to use the technology toadd automated agents at its call centres,
personalise services to its 17mn retailcustomers and streamline its internal
processes by analysing documents.
“Nobody really knows what banking
will look like in 10 years’ time — or what
the technology will look like. But I am
100 per cent sure that AI will play akey role,” says Peter Csanyi, OTP’s chief
digital officer.
Some of the companies that havedeveloped powerful foundation models,such as Google, Microsoft and OpenAI,
restrict access to the technology toknown users. But others, including Meta
and EleutherAI, share it with a broader
customer base. There is a tension
between allowing outside experts to help
detect flaws and bias and preventing
more sinister use by the unscrupulous.
Foundation models may be “reallyexciting and impressive” but are open
to abuse because they are “designed tobe devious”, says Carissa Véliz, associate

professor at Oxford university’s
Institute for Ethics in AI. If trained on
historically biased datasets, foundation
models can produce harmful outputs.
They can threaten privacy by extracting
digital detail about an individual andusing bots to reshape online personas.
They can also devalue the currency oftruth by flooding the internet with fakeinformation.
Véliz makes an analogy with financialsystems: “We can trust money so longas there is not too much counterfeit.
But if there is more fake money thanreal money, the system breaks down.
We are creating tools and systems that
we cannot control.” That argues forthe implementation of randomised
control trials for foundation models
before release, she says, just as forpharmaceutical drugs.
The Stanford Institute for HumanCentred AI has pushed for thecreation of an expert review board
to set community norms, share bestpractice and agree standardised accessrules before foundation models arereleased. Democracy is not just abouttransparency and openness. It is also
about institutional design for collectivegovernance. We are, as the Stanford
institute’s Rob Reich puts it, in a race
between “disruption and democracy”.
Until effective collective governanceis put in place to control the use offoundation models, it is far from clearthat democracy will win.
john.thornhill@ft.com