The existential threat of artificial stupidity

Bodies, Minds, and the Artificial Intelligence Industrial Complex, part seven
Also published on Resilience.

One headline about artificial intelligence gave me a rueful laugh the first few times I saw it.

With minor variations headline writers have posed the question, “What if AI falls into the wrong hands?”

But AI is already in the wrong hands. AI is in the hands of a small cadre of ultra-rich influencers affiliated with corporations and governments, organizations which collectively are driving us straight towards a cliff of ecological destruction.

This does not mean, of course, that every person working on the development of artificial intelligence is a menace, nor that every use of artificial intelligence will be destructive.

But we need to be clear about the socio-economic forces behind the AI boom. Otherwise we may buy the illusion that our linear, perpetual-growth-at-all-costs economic system has somehow given birth to a magically sustainable electronic saviour.

The artificial intelligence industrial complex is an astronomically expensive enterprise, pushing its primary proponents to rapidly implement monetized applications. As we will see, those monetized applications are either already in widespread use, or are being promised as just around the corner. First, though, we’ll look at why AI is likely to be substantially controlled by those with the deepest pockets.

“The same twenty-five billionaires”

CNN host Fareed Zakaria asked the question “What happens if AI gets into the wrong hands?” in a segment in January. Interviewing Mustafa Suleyman, Inflection AI founder and Google DeepMind co-founder, Zakaria framed the issue this way:

“You have kind of a cozy elite of a few of you guys. It’s remarkable how few of you there are, and you all know each other. You’re all funded by the same twenty-five billionaires. But once you have a real open source revolution, which is inevitable … then it’s out there, and everyone can do it.”1

Some of this is true. OpenAI was co-founded by Sam Altman and Elon Musk. Their partnership didn’t last long and Musk has founded a competitor, x.AI. OpenAI has received $10 billion from Microsoft, while Amazon has invested $4 billion and Alphabet (Google) has invested $300 million in AI startup Anthropic. Year-old company Inflection AI has received $1.3 billion from Microsoft and chip-maker Nvidia.2

Meanwhile Mark Zuckerberg says Meta’s biggest area of investment is now AI, and the company is expected to spend about $9 billion this year just to buy chips for its AI computer network.3 Companies including Apple, Amazon, and Alphabet are also investing heavily in AI divisions within their respective corporate structures.

Microsoft, Amazon and Alphabet all earn revenue from their web services divisions which crunch data for many other corporations. Nvidia sells the chips that power the most computation-intensive AI applications.

But whether an AI startup rents computer power in the “cloud”, or builds its own supercomputer complex, creating and training new AI models is expensive. As Fortune reported in January, 

“Creating an end-to-end model from scratch is massively resource intensive and requires deep expertise, whereas plugging into OpenAI or Anthropic’s API is as simple as it gets. This has prompted a massive shift from an AI landscape that was ‘model-forward’ to one that’s ‘product-forward,’ where companies are primarily tapping existing models and skipping right to the product roadmap.”4

The huge expense of building AI models also has implications for claims about “open source” code. As Cory Doctorow has explained,

“Not only is the material that ‘open AI’ companies publish insufficient for reproducing their products, even if those gaps were plugged, the resource burden required to do so is so intense that only the largest companies could do so.”5

Doctorow’s aim in the above-cited article was to debunk the claim that the AI complex is democratising access to its products and services. Yet this analysis also has implications for Fareed Zaharia’s fears of unaffiliated rogue actors doing terrible things with AI.

Individuals or small organizations may indeed use a major company’s AI engine to create deepfakes and spread disinformation, or perhaps even to design dangerously mutated organisms. Yet the owners of the AI models determine who has access to which models and under which terms. Thus unaffiliated actors can be barred from using particular models, or charged sufficiently high fees that using a given AI engine is not feasible.

So while the danger from unaffiliated rogue actors is real, I think the more serious danger is from the owners and funders of large AI enterprises. In other words, the biggest dangers come not from those into whose hands AI might fall, but from those whose hands are already all over AI.

Command and control

As discussed earlier in this series, the US military funded some of the earliest foundational projects in artificial intelligence, including the “perceptron” in 19566 and WordNet semantic database beginning in 1985.7

To this day military and intelligence agencies remain major revenue sources for AI companies. Kate Crawford writes that the intentions and methods of intelligence agencies continue to shape the AI industrial complex:

“The AI and algorithmic systems used by the state, from the military to the municipal level, reveal a covert philosophy of en masse infrastructural command and control via a combination of extractive data techniques, targeting logics, and surveillance.”8

As Crawford points out, the goals and methods of high-level intelligence agencies “have spread to many other state functions, from local law enforcement to allocating benefits.” China-made surveillance cameras, for example, were installed in New Jersey and paid for under a COVID relief program.9 Artificial intelligence bots can enforce austerity policies by screening – and disallowing – applications for government aid. Facial-recognition cameras and software, meanwhile, are spreading rapidly and making it easier for police forces to monitor people who dare to attend political protests.

There is nothing radically new, of course, in the use of electronic communications tools for surveillance. Eleven years ago, Edward Snowden famously revealed the expansive plans of the “Five Eyes” intelligence agencies to monitor all internet communications.10 Decades earlier, intelligence agencies were eagerly tapping undersea communications cables.11

Increasingly important, however, is the partnership between private corporations and state agencies – a partnership that extends beyond communications companies to include energy corporations.

This public/private partnership has placed particular emphasis on suppressing activists who fight against expansions of fossil fuel infrastructure. To cite three North American examples, police and corporate teams have worked together to surveil and jail opponents of the Line 3 tar sands pipeline in Minnesota,12 protestors of the Northern Gateway pipeline in British Columbia,13 and Water Protectors trying to block a pipeline through the Standing Rock Reservation in North Dakota.14

The use of enhanced surveillance techniques in support of fossil fuel infrastructure expansions has particular relevance to the artificial intelligence industrial complex, because that complex has a fierce appetite for stupendous quantities of energy.

Upping the demand for energy

“Smashed through the forest, gouged into the soil, exploded in the grey light of dawn,” wrote James Bridle, “are the tooth- and claw-marks of Artificial Intelligence, at the exact point where it meets the earth.”

Bridle was describing sudden changes in the landscape of north-west Greece after the Spanish oil company Repsol was granted permission to drill exploratory oil wells. Repsol teamed up with IBM’s Watson division “to leverage cognitive technologies that will help transform the oil and gas industry.”

IBM was not alone in finding paying customers for nascent AI among fossil fuel companies. In 2018 Google welcomed oil companies to its Cloud Next conference, and in 2019 Microsoft hosted the Oil and Gas Leadership Summit in Houston. Not to be outdone, Amazon has eagerly courted petroleum prospectors for its cloud infrastructure.

As Bridle writes, the intent of the oil companies and their partners includes “extracting every last drop of oil from under the earth” – regardless of the fact that if we burn all the oil already discovered we will push the climate system past catastrophic tipping points. “What sort of intelligence seeks not merely to support but to escalate and optimize such madness?”

The madness, though, is eminently logical:

“Driven by the logic of contemporary capitalism and the energy requirements of computation itself, the deepest need of an AI in the present era is the fuel for its own expansion. What it needs is oil, and it increasingly knows where to find it.”15

AI runs on electricity, not oil, you might say. But as discussed at greater length in Part Two of this series, the mining, refining, manufacturing and shipping of all the components of AI servers remains reliant on the fossil-fueled industrial supply chain. Furthermore, the electricity that powers the data-gathering cloud is also, in many countries, produced in coal- or gas-fired generators.

Could artificial intelligence be used to speed a transition away from reliance on fossil fuels? In theory perhaps it could. But in the real world, the rapid growth of AI is making the transition away from fossil fuels an even more daunting challenge.

“Utility projections for the amount of power they will need over the next five years have nearly doubled and are expected to grow,” Evan Halper reported in the Washington Post earlier this month. Why the sudden spike?

“A major factor behind the skyrocketing demand is the rapid innovation in artificial intelligence, which is driving the construction of large warehouses of computing infrastructure that require exponentially more power than traditional data centers. AI is also part of a huge scale-up of cloud computing.”

The jump in demand from AI is in addition to – and greatly complicates – the move to electrify home heating and car-dependent transportation:

“It is all happening at the same time the energy transition is steering large numbers of Americans to rely on the power grid to fuel vehicles, heat pumps, induction stoves and all manner of other household appliances that previously ran on fossil fuels.”

The effort to maintain and increase overall energy consumption, while paying lip-service to transition away from fossil fuels, is having a predictable outcome: “The situation … threatens to stifle the transition to cleaner energy, as utility executives lobby to delay the retirement of fossil fuel plants and bring more online.”16

The motive forces of the artificial industrial intelligence complex, then, include the extension of surveillance, and the extension of climate- and biodiversity-destroying fossil fuel extraction and combustion. But many of those data centres are devoted to a task that is also central to contemporary capitalism: the promotion of consumerism.

Thou shalt consume more today than yesterday

As of March 13, 2024, both Alphabet (parent of Google) and Meta (parent of Facebook) ranked among the world’s ten biggest corporations as measured by either market capitalization or earnings.17 Yet to an average computer user these companies are familiar primarily for supposedly “free” services including Google Search, Gmail, Youtube, Facebook and Instagram.

These services play an important role in the circulation of money, of course – their function is to encourage people to spend more money than they otherwise would, for all types of goods or services, whether or not they actually need or even desire more goods and services. This function is accomplished through the most elaborate surveillance infrastructures yet invented, harnessed to an advertising industry that uses the surveillance data to better target ads and to better sell products.

This role in extending consumerism is a fundamental element of the artificial intelligence industrial complex.

In 2011, former Facebook employee Jeff Hammerbacher summed it up: “The best minds of my generation are thinking about how to make people click ads. That sucks.”18

Working together, many of the world’s most skilled behavioural scientists, software engineers and hardware engineers devote themselves to nudging people to spend more time online looking at their phones, tablets and computers, clicking ads, and feeding the data stream.

We should not be surprised that the companies most involved in this “knowledge revolution” are assiduously promoting their AI divisions. As noted earlier, both Google and Facebook are heavily invested in AI. And Open AI, funded by Microsoft and famous for making ChatGPT almost a household name, is looking at ways to make  their investment pay off.

By early 2023, Open AI’s partnership with “strategy and digital application delivery” company Bain had signed up its first customer: The Coca-Cola Company.19

The pioneering effort to improve the marketing of sugar water was hailed by Zack Kass, Head of Go-To-Market at OpenAI: “Coca-Cola’s vision for the adoption of OpenAI’s technology is the most ambitious we have seen of any consumer products company ….”

On its website, Bain proclaimed:

“We’ve helped Coca-Cola become the first company in the world to combine GPT-4 and DALL-E for a new AI-driven content creation platform. ‘Create Real Magic’ puts the power of generative AI in consumers’ hands, and is one example of how we’re helping the company augment its world-class brands, marketing, and consumer experiences in industry-leading ways.”20

The new AI, clearly, has the same motive as the old “slow AI” which is corporate intelligence. While a corporation has been declared a legal person, and therefore might be expected to have a mind, this mind is a severely limited, sociopathic entity with only one controlling motive – the need to increase profits year after year with no end. (This is not to imply that all or most employees of a corporation are equally single-minded, but any noble motives  they may have must remain subordinate to the profit-maximizing legal charter of the corporation.) To the extent that AI is governed by corporations, we should expect that AI will retain a singular, sociopathic fixation with increasing profits.

Artificial intelligence, then, represents an existential threat to humanity not because of its newness, but because it perpetuates the corporate imperative which was already leading to ecological disaster and civilizational collapse.

But should we fear that artificial intelligence threatens us in other ways? Could AI break free from human control, supersede all human intelligence, and either dispose of us or enslave us? That will be the subject of the next installment.


1  GPS Web Extra: What happens if AI gets into the wrong hands?”, CNN, 7 January 2024.

2 Mark Sweney, “Elon Musk’s AI startup seeks to raise $1bn in equity,” The Guardian, 6 December 2023.

3 Jonathan Vanian, “Mark Zuckerberg indicates Meta is spending billions of dollars on Nvidia AI chips,” CNBC, 18 January 2024.

4 Fortune Eye On AI newsletter, 25 January 2024.

5 Cory Doctorow, “‘Open’ ‘AI’ isn’t”, Pluralistic, 18 August 2023.

6 “New Navy Device Learns By Doing,” New York Times, July 8, 1958, page 25.

7 “WordNet,” on Scholarly Community Encyclopedia, accessed 11 March 2024.

8 Kate Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence, Yale University Press, 2021.

9 Jason Koehler, “New Jersey Used COVID Relief Funds to Buy Banned Chinese Surveillance Cameras,” 404 Media, 3 January 2024.

10 Glenn Greenwald, Ewen MacAskill and Laura Poitras, “Edward Snowden: the whistleblower behind the NSA surveillance revelations,” The Guardian, 11 June 2013.

11 The Creepy, Long-Standing Practice of Undersea Cable Tapping,” The Atlantic, Olga Kazhan, 16 July 2013

12 Alleen Brown, “Pipeline Giant Enbridge Uses Scoring System to Track Indigenous Opposition,” 23 January, 2022, part one of the seventeen-part series “Policing the Pipeline” in The Intercept.

13 Jeremy Hainsworth, “Spy agency CSIS allegedly gave oil companies surveillance data about pipeline protesters,” Vancouver Is Awesome, 8 July 2019.

14 Alleen Brown, Will Parrish, Alice Speri, “Leaked Documents Reveal Counterterrorism Tactics Used at Standing Rock to ‘Defeat Pipeline Insurgencies’”, The Intercept, 27 May 2017.

15 James Bridle, Ways of Being: Animals, Plants, Machines: The Search for a Planetary Intelligence, Farrar, Straus and Giroux, 2023; pages 3–7.

16 Evan Halper, “Amid explosive demand, America is running out of power,” Washington Post, 7 March 2024.

17 Source:, 13 March 2024.

18 As quoted in Fast Company, “Why Data God Jeffrey Hammerbacher Left Facebook To Found Cloudera,” 18 April 2013.

19 PRNewswire, “Bain & Company announces services alliance with OpenAI to help enterprise clients identify and realize the full potential and maximum value of AI,” 21 February 2023.

20 Bain & Company website, accessed 13 March 2024.

Image at top of post by Bart Hawkins Kreps from public domain graphics.