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Template:M intro technology rumours of our demise: Difference between revisions
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These are the artists for whom the improbability engine worked its magic, even if not in their lifetimes. But how many undiscovered Nietzsches, Blakes and Dickinsons are there, who never caught the light, and now lie lost, sedimented into unreachably deep strata of the human canon? How many ''living'' artists are brilliantly ploughing an under-appreciated furrow, cursing their own immaculate Bayesian priors? How many solitary geniuses are out there who, as we speak, are galloping towards an obscurity a [[large language model]] might save them from? | These are the artists for whom the improbability engine worked its magic, even if not in their lifetimes. But how many undiscovered Nietzsches, Blakes and Dickinsons are there, who never caught the light, and now lie lost, sedimented into unreachably deep strata of the human canon? How many ''living'' artists are brilliantly ploughing an under-appreciated furrow, cursing their own immaculate Bayesian priors? How many solitary geniuses are out there who, as we speak, are galloping towards an obscurity a [[large language model]] might save them from? | ||
(I know of at least one: | (I know of at least one: legendary rockabilly singer [[Daniel Jeanrenaud]], known to his fans as the [[Camden Cat]], who for thirty years has plied his trade with a beat up acoustic guitar on the Northern Line, and once wrote and recorded one of the great rockabilly singles of all time. Here it is on {{Plainlink|1=https://soundcloud.com/thecamdencats/you-carry-on?si=24ececd75c0540faafd470d822971ab7|2=SoundCloud}}.) | ||
Digression over. | |||
=== If AI is just a cheapest-to-deliver strategy you are doing it wrong === | === If AI is just a cheapest-to-deliver strategy you are doing it wrong === | ||
{{quote| | {{quote| | ||
{{D|Cheapest-to-deliver|/ˈʧiːpɪst tuː dɪˈlɪvə/|adj}} | {{D|Cheapest-to-deliver|/ˈʧiːpɪst tuː dɪˈlɪvə/|adj}} | ||
Of the range of possible ways of discharging a [[contractual]] | Of the range of possible ways of discharging a [[contract|contractual obligation]], the one that will cost you the least and irritate your customer the most should you choose it.}} | ||
Imagine personal [[large language model]], private to a single client user — free, therefore, of data privacy concerns — that would pattern-match purely by reference to its client’s actual reading and listening history, | Imagine a personal [[large language model]], private to a single client user — free, therefore, of data privacy concerns — that would pattern-match purely by reference to its client’s actual reading and listening history, prompts, instructions and to the recommendations of pattern-matched like-minded readers, which searched through the entire human creative ''oeuvre'' — the billions of books, plays, films, recordings and artworks, known and not, that already exist — and, instead of using them to generate random mashups, would be designed to return works of as yet undiscovered delight? | ||
''This is not just the Spotify recommendation algorithm'', as occasionally delightful as that is. Like any commercial algorithm, that has its own primary goal: revenue maximisation. “Client delight” may be a necessary by-product, but only as far as it intersects with that primary commercial goal. As long as clients are delighted ''enough'' to keep listening, the algorithm doesn’t care ''how'' delighted they are. As with the JC’s school exam grades: anything more than 51% is wasted effort.<ref>Try as he might, the JC was never able to persuade his dear old ''Mutti'' about this.</ref> | |||
'' | Commercial algorithms need only follow a ''[[cheapest to deliver]]'' strategy: they “[[satisfice]]”. Being targeted primarily at revenue optimisation, they will tend to converge upon what is likely to be popular, because that is easier to find. Rather than scanning the entire depth of human content, skim the top and keep the punters happy enough. | ||
This, by the way, has been the tale of the collaborative internet: despite Chris Anderson’s wishful forecast in 2006<ref>[[The Long Tail: How Endless Choice is Creating Unlimited Demand]]''(2006)''</ref> that global interconnectedness would change economics forever; that suddenly it was costless for niche suppliers to service the long, diverse, tail of global demand | |||
This is a counsel of preferring the average reader’s personal “[[cheesecake for the brain]]”. This, as per {{author|Anita Elberse}}’s [[Blockbusters: Why Big Hits and Big Risks are the Future of the Entertainment Business|''Blockbusters'']], targeted will have had the counter-intuitive effect of ''truncating'' the “[[long tail]]” of consumer choice. A sensible use for this technology would ''extend'' it. | |||
In any case, if artificial intelligence is so spectacular, shouldn’t we be a bit more ambitious in our expectations about what it could do for us? Isn’t “giving you the bare minimum you’ll take to keep stringing you along” just a little ''underwhelming''? | In any case, if artificial intelligence is so spectacular, shouldn’t we be a bit more ambitious in our expectations about what it could do for us? Isn’t “giving you the bare minimum you’ll take to keep stringing you along” just a little ''underwhelming''? | ||
==== LibraryThing ==== | The sheer processing power required to run a large learning model is likely to be | ||
====LibraryThing==== | |||
A rudimentary version of this exists in the [https://www.librarything.com/ LibraryThing] recommendation engine: you upload all the books in your personal library, score them 1-5, and it will match your library with other like-minded users on the site. The non-matched books from libraries of similar users are often a revelation. It isn’t wildly clever '''—''' LibraryThing has been around for nearly twenty years and doesn’t, as far as I know, use AI, but the scope if it did, is huge. | A rudimentary version of this exists in the [https://www.librarything.com/ LibraryThing] recommendation engine: you upload all the books in your personal library, score them 1-5, and it will match your library with other like-minded users on the site. The non-matched books from libraries of similar users are often a revelation. It isn’t wildly clever '''—''' LibraryThing has been around for nearly twenty years and doesn’t, as far as I know, use AI, but the scope if it did, is huge. | ||
==== This is something humans cannot do ==== | ====This is something humans cannot do==== | ||
This role — seeking out delightful new human endeavours — would be a valuable role ''that is quite beyond the capability of any group of humans'' and which would not devalue, much less usurp the value of human intellectual capacity. Rather, it would ''empower'' it. | This role — seeking out delightful new human endeavours — would be a valuable role ''that is quite beyond the capability of any group of humans'' and which would not devalue, much less usurp the value of human intellectual capacity. Rather, it would ''empower'' it. | ||
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Information technology has done a fabulous job of alleviating boredom, by filling our empty moments with a 5-inch rectangle of gossip, outrage and titillation, but it has done little to nourish the intellect. This is a function of the choices me have made. They, in turn are informed by the interests. Maybe we are missing something by never being bored. Maybe that is a clear space where imagination can run wild. Perhaps being fearful of boredom, by constantly distracting ourselves from our own existential anguish, we make ourselves vulnerable to this two-dimensional online world. | Information technology has done a fabulous job of alleviating boredom, by filling our empty moments with a 5-inch rectangle of gossip, outrage and titillation, but it has done little to nourish the intellect. This is a function of the choices me have made. They, in turn are informed by the interests. Maybe we are missing something by never being bored. Maybe that is a clear space where imagination can run wild. Perhaps being fearful of boredom, by constantly distracting ourselves from our own existential anguish, we make ourselves vulnerable to this two-dimensional online world. | ||
===A real challenger bank=== | ===A real challenger bank=== | ||
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''This is what machine-oriented solutions inevitably do''. Even ones using [[artificial intelligence]]. (''Especially'' ones using [[artificial intelligence]].) Machines are cheap, quick and easy solutions to hard problems. Everyone who takes the same easy solution will end up at the same place — a traffic jam — a local maximum that, as a result, will be systematically driven into the ground by successive, mediocre market entrants seeking to get a piece of the same action. | ''This is what machine-oriented solutions inevitably do''. Even ones using [[artificial intelligence]]. (''Especially'' ones using [[artificial intelligence]].) Machines are cheap, quick and easy solutions to hard problems. Everyone who takes the same easy solution will end up at the same place — a traffic jam — a local maximum that, as a result, will be systematically driven into the ground by successive, mediocre market entrants seeking to get a piece of the same action. | ||
''In principle'', humans can make “educated improvisations” in the face of unexpected opportunities in a way that machines can’t. < | ''In principle'', humans can make “educated improvisations” in the face of unexpected opportunities in a way that machines can’t. <ref>Sure: machines can make random improvisations, and after iterating for long enough may arrive at the same local maxima, but undirected evolution is extraordinarily inefficient way to “frig around and find out”.</ref> | ||
There is an ineffable, valuable role optimising those machines, adjusting them, steering them, directing them, feeding in your human insight optimising for the environment as it evolves. | There is an ineffable, valuable role optimising those machines, adjusting them, steering them, directing them, feeding in your human insight optimising for the environment as it evolves. | ||
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You will have built carbon-based Turing machines. We already know that humans are bad at being computers. ''That is why we build computers''. But if we raise our children to be automatons they won’t be good at human magic either. | You will have built carbon-based Turing machines. We already know that humans are bad at being computers. ''That is why we build computers''. But if we raise our children to be automatons they won’t be good at human magic either. | ||
Nor, most likely, will the leaders of banking organisations who employ them. These executives will have made it to the top of their respective greasy poles by steadfast demonstration of the qualities to which their organisations aspire. If a bank elevates algorithms over all else, you should expect its chief executive to say things like, “tomorrow, we will have ''robots behaving like people”. This can only be true, or a good thing, ''if you expect your best people to behave like robots''. | Nor, most likely, will the leaders of banking organisations who employ them. These executives will have made it to the top of their respective greasy poles by steadfast demonstration of the qualities to which their organisations aspire. If a bank elevates algorithms over all else, you should expect its chief executive to say things like, “tomorrow, we will have ''robots behaving like people”. This can only be true, or a good thing, ''if you expect your best people to behave like robots''.'' | ||
Robotic people do not generally have a rogue streak. They are not loose cannons. They no not call “bullshit”. They do not question their orders. They do not answer back. | Robotic people do not generally have a rogue streak. They are not loose cannons. They no not call “bullshit”. They do not question their orders. They do not answer back. | ||
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And so we see: financial services organisations do not value people who do. They value the ''fearful''. They elevate the rule-followers. They distrust “human magic”, which they characterise as human ''weakness''. They find it in the wreckage of [[Enron]], or [[Financial disasters roll of honour|Kerviel]], or [[Madoff]], or [[Archegos]]. Bad apples. [[Operator error]]. They emphasise this human stain over the failure of management that inevitably enabled it. People who did not play by the rules over systems of control that allowed, .or even obliged, them to. | And so we see: financial services organisations do not value people who do. They value the ''fearful''. They elevate the rule-followers. They distrust “human magic”, which they characterise as human ''weakness''. They find it in the wreckage of [[Enron]], or [[Financial disasters roll of honour|Kerviel]], or [[Madoff]], or [[Archegos]]. Bad apples. [[Operator error]]. They emphasise this human stain over the failure of management that inevitably enabled it. People who did not play by the rules over systems of control that allowed, .or even obliged, them to. | ||
The run [[post mortem]]s: with the rear-facing forensic weaponry of [[internal audit]], [[external counsel]] they reconstruct the [[fog of war]] and build a narrative around it. The solution: ''more systems. More control. More elaborate algorithms. More rigid playbooks. The object of the exercise: eliminate the chance of human error. Relocate everything to process. | The run [[post mortem]]s: with the rear-facing forensic weaponry of [[internal audit]], [[external counsel]] they reconstruct the [[fog of war]] and build a narrative around it. The solution: ''more systems. More control. More elaborate algorithms. More rigid playbooks. The object of the exercise: eliminate the chance of human error. Relocate everything to process.'' | ||
Yet the accidents keep coming. Our [[financial crashes roll of honour]] refers. They happen with the same frequency, and severity, notwithstanding the additional sedimentary layers of machinery we develop to stop them. | Yet the accidents keep coming. Our [[financial crashes roll of honour]] refers. They happen with the same frequency, and severity, notwithstanding the additional sedimentary layers of machinery we develop to stop them. | ||
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Thus, Cryan says and Evidence Lab implies: ''prepare for the coming of the machines''. Automate ''every'' process. Reduce the cost line. Remove people, because when they come for us, ''Amazon won’t be burdened by people''. | Thus, Cryan says and Evidence Lab implies: ''prepare for the coming of the machines''. Automate ''every'' process. Reduce the cost line. Remove people, because when they come for us, ''Amazon won’t be burdened by people''. | ||
===Yes, bank tech is rubbish=== | ===Yes, bank tech is rubbish === | ||
To be sure, the tech stacks of most banks ''are'' dismal. Most are sedimented, interdependent concatenations of old mainframes, Unix servers, IBM 386s, and somewhere in the middle of the thicket will be a wang box from 1976 with a CUI interface that can’t be switched off without crashing the entire network. These patchwork systems are a legacy of dozens of mergers and acquisitions and millions of lazy, short-term decisions to patch obsolescent systems with sellotape and glue rather than overhauling and upgrading them properly. | To be sure, the tech stacks of most banks ''are'' dismal. Most are sedimented, interdependent concatenations of old mainframes, Unix servers, IBM 386s, and somewhere in the middle of the thicket will be a wang box from 1976 with a CUI interface that can’t be switched off without crashing the entire network. These patchwork systems are a legacy of dozens of mergers and acquisitions and millions of lazy, short-term decisions to patch obsolescent systems with sellotape and glue rather than overhauling and upgrading them properly. | ||
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Bank technology is not, of itself, a competitive threat. It is just the ticket to play. | Bank technology is not, of itself, a competitive threat. It is just the ticket to play. | ||
=== Yes, bank staff are rubbish === | === Yes, bank staff are rubbish=== | ||
Now, to lionise the human spirit ''in the abstract'', as we do, is not to say we should sanctify bank employees as a class ''in the particular''. The JC has spent a quarter century among them. They — we — may be unusually paid, for all the difference we make to the median life on planet Earth, but we are not unusually gifted or intelligent. | Now, to lionise the human spirit ''in the abstract'', as we do, is not to say we should sanctify bank employees as a class ''in the particular''. The JC has spent a quarter century among them. They — we — may be unusually paid, for all the difference we make to the median life on planet Earth, but we are not unusually gifted or intelligent. | ||
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Just as you shouldn’t confuse products with services, also don’t confuse services with products. There are parts of the client life cycle that feel tedious, high cost, low value things — client onboarding — that are unusually formative of a client’s impression during onboarding. Precisely because they have the potential to be so painful, and they crop up at the start of the relationship. Turning these into client selling points — can you imagine legal docs being a ''marketing'' tool? — can turn this into a service. Treating an opportunity to handhold a new client as a product and not an opportunity to relationship build misses a trick. | Just as you shouldn’t confuse products with services, also don’t confuse services with products. There are parts of the client life cycle that feel tedious, high cost, low value things — client onboarding — that are unusually formative of a client’s impression during onboarding. Precisely because they have the potential to be so painful, and they crop up at the start of the relationship. Turning these into client selling points — can you imagine legal docs being a ''marketing'' tool? — can turn this into a service. Treating an opportunity to handhold a new client as a product and not an opportunity to relationship build misses a trick. | ||
<references /> | |||