Artificial Intelligence: The AI fairytale
Overthe course of the 2000s, Big Tech platforms established themselveson this foundationthrough searchengines, social mediaplatforms, marketplaces, ad exchanges and much more. They invested in research and development to enable faster andmore ambitiousdata collectionandprocessing, and to build and maximize computational infrastructures and techniques that could facilitate such collection and"use"of data. Economies of scale, network effects and the self-reinforcing dynamics of communication infrastructures enabled the firms early to this toxic model to establish monopoly dominance. This was aided by theU.S.government’s use of soft power, trade agreements and imperial dominance to ensure that the EU and other jurisdictions adopted theU.S.paradigm.
This history helps explain whythe majority ofthe world’sBig Techcorporations are based in theU.S., with the rest emerging from China. TheU.S.got a head start, via military infrastructureand neoliberal policies and investment, while China built a self-contained market capable of supporting its own platformsandwith its own norms for content that further limited external competition. Which also means that the story of the EU "stifling innovation via regulation" is both wrong and suspiciously self-serving when it comes from the mouths of tech giants and theiraccessories.
Here you might pause, reflect and ask: But what does this sordid history have to do with AI? Well, it has everything to do with AI.
In 2012, right as the surveillance platforms were cementing their dominance, researchers published a very important paper on AI image classification, which kicked off the current AI goldrush.The paper showed that a combination of powerful computers and huge amounts of datacould significantly improve the performance of AI techniques–techniques thathad beencreated in the late 1980s. In other words, what was new in 2012were notthe approaches to AI–the methods and procedures. What "changed everything" over the last decade was the staggering computational and data resources newly available, and thus newly able to animate old approaches.
Put another way, the current AI craze isa resultofthetoxic surveillance business model. It is not due to novel scientific approaches that,like the printing press,fundamentally shifted a paradigm. And while new frameworks and architectures have emerged in the intervening decade, this paradigm still holds:It’s the data andcomputational powerthat determine whowinsand who loses.
What we call AI today grew out of this toxic modeland must be understood primarily as a way of marketing the derivatives of mass surveillance and concentrated platform and computational power.Currently, there are only a small handful of firms–based in theU.S.and China– thathave the resources to create and deploy large-scale AI from start to finish. These are the cloud and platform monopolies,those that established themselves early on the backs of the surveillance business model. Everyone else is licensing infrastructure, scrambling for data and struggling to find market fit without massive cloud infrastructures,through which AI can be licensed to customers,or massive platforms,into which AI can be integrated as a feature or service touching billions of people.
This is why even the most successful AI"startups" – likeOpen AI, MistralandInflection–are ultimatelyjustbarnacles on thevasthull of the Big Tech ship,the Microsoft ship, in their case. It’s why Anthropicshouldbe understood as a kind of subsidiary of Google and Amazon.
In addition to the current technologies that are being called "AI," we also need to look at the AI narrative itself, the story thatisanimating marketing and hype today. How is this marketing term being deployed? Byweavingquasi-religious tales about conscious computersandartificial general intelligence,aboutsmall elves that sit in our pocket, cateringto our every desirelike personal servants,massive companies have paved the way for unprecedented dominance.
Bypresentingtheir products and services as the apex of "human progress" and "scientific advancement," these companies and their boosters are extending their reach and control into nearly all sectors of lifeandacross nearly every region on earth, in addition toproviding the infrastructure for governments, corporations, media and militaries. They are selling the derivatives of the toxic surveillance business model as the product of scientific innovation.
And they are working to convince us that probabilistic systems that recognize statistical patterns in massive amounts of data are objective, intelligent and sophisticated tools capable of nearly any function imaginable.Certainlymore capable thanusmere mortals.As such,we should step aside and trust our business to them.
This is incredibly dangerous. The metastatic shareholder-drivencapitalisticpursuit of endless growth and revenue that ultimately propels these massive corporations frequently diverges from the path toward alivablefuture.
