Years ago, I read author and historian Peter Ackroyd on London’s secret subterranean history.
asserted
I → read → history
I became obsessed by the lost rivers, like the Effra and the Westbourne, still flowing in darkness beneath the city.
asserted
I → obsess → city
Since I began researching this piece, I’ve felt similarly about artificial intelligence, thinking of it as a largely invisible system spreading beneath and across London, mushrooming through boroughs and institutions, twisting into everyday lives.
asserted
I → begin → lives
Across London an AI network is already taking shape.
asserted
network → take → shape
Beneath the streets, Thames Water has more than 75,000 acoustic sensors listening for leaks (no jokes about efficacy please).
asserted
Water → have → efficacy
In Tooting, AI listens to consultations at St George’s A&E and writes the clinical notes, saving doctors an average 47 minutes per shift; across all 32 boroughs, machine learning joins up fragmented records to help London understand the journeys of people sleeping rough.
asserted
London → listen → people
In Lewisham, AI has identified more than 3,000 overlooked sites with theoretical capacity for nearly 10,000 homes; if you hang out in Croydon, you might have been one of more than 470,000 people who had their face scanned by AI-powered cameras mounted on lampposts and compared against a police watchlist.
uncertain
face → identify → watchlist
On the Tube, predictive AI spots the signs of trouble before a train, signal or escalator packs up.
asserted
train → spot → trouble
Increasingly, algorithms work out how groceries travel from store to front door.
asserted
groceries → work → door
And if you drive an electric vehicle, AI may already be deciding when your car charges.
uncertain
car → drive → vehicle
We are handing more of the reins to AI and the handover is picking up speed and scope.
asserted
handover → hand → speed
AI apocalypse
Meanwhile, it’s felt a bit like the Apocalypse Olympics.
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it → feel → Olympics
Over the past month alone, Anthropic warned that AI models are acquiring “tactical intelligence targeting and conventional weapons capabilities”.
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models → warn → targeting
OpenAI called for international standards to govern frontier AI systems, which are potentially advancing faster than humans can understand, test or control them, and Bill Gates warned that, unchecked, AI could “cause a billion deaths”.
uncertain
AI → call → deaths
All of which puts me in mind of the classic Crimewatch sign off: “Don’t have nightmares, do sleep well!”
asserted
All → put → nightmares
“The attacker only needs to get it right once”
asserted
it → need → ?
“The sci-fi scenario is not actually what we should be worried about,” says Dr Stephanie Hare, co-presenter of the BBC’s Artificial Intelligence: Decoded.
asserted
Hare → worry → Intelligence
“The very real scenarios that genuinely serious people are worried about are super basic.”
asserted
people → worry → that
The biggest risk to London, as she tells it, is good old-fashioned cybersecurity.
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she → tell → it
Most organisations “have not been keeping up with their latest cybersecurity investments”.
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organisations → keep → investments
It is a David-and-Goliath problem, except the advantage is reversed.
asserted
advantage → reverse → ?
“If you’re an institution or company, you have to defend your entire attack surface,” says Hare.
asserted
Hare → ’re → surface
“Whereas the attacker only needs to get it right once.”
asserted
it → need → ?
“Think about what that means in a city as digital as London.
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that → think → London
Imagine anything that can be hacked that you depend on,” says Hare.
asserted
Hare → imagine → that
“Imagine their bank cards don’t work anymore.
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cards → imagine → ?
Their public transport doesn’t work anymore.
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transport → work → ?
Imagine that you want to cause maximum chaos in London.
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you → imagine → London
Get into a bank so people cannot access their money and watch London lose it.”
asserted
London → get → it
Recently, the Government offered the slightly surreal advice that we should all keep an emergency supply of food and water at home.
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we → offer → home
France and Switzerland, Hare says, are far more prescriptive.
asserted
Hare → say → ?
Britain is “a bit hand-wavy; like, you should have some beans.
asserted
you → have → beans
Being an equal-opportunities catastrophist, in truth I had assumed the much-discussed “prepper pantry” was for El Niño impacts or climate-change drought.
asserted
pantry → assume → impacts
But Hare’s concern is what happens if the increasingly AI-reliant systems that get food to us stop working.
asserted
that → happen → us
Ninety-nine per cent of the 6.347 million tonnes of food and drink supplying the capital each year comes from outside the city; less than one per cent is produced here.
asserted
cent → supply → city
City Hall describes a food supply dependent on “a complex set of interdependencies and just-in-time delivery systems”.
asserted
Hall → describe → time
This summer the Mayor, Lord Khan, announced the London Resilience Unit was working on a London Food Systems Resilience Partnership, partnering with food and farming charity Sustain to prepare for disruption from “international shocks and crises”.
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Unit → announce → shocks
Plenty of Londoners are not fretting about AI, or hoarding cans of baked beans.
asserted
Plenty → fret → beans
At Weave, a recent summit held by London technology company Loomery on “building the agentic enterprise”, the excitement was about what it calls AI’s second wave.
asserted
it → hold → what
Wave one was individual productivity: AI helps us do existing work faster.
asserted
us → help → work
…and 55 more, not listed.
The Aporia
