If you’ve had a conversation with me in the past year, odds are that AI came up. We may have talked about how AI seems to be creeping into every aspect of our lives, or how overwhelmed we are by the constant barrage of information, from both Big Tech sycophants and critics. Perhaps we discussed the technical mechanics of AI, how it’s being applied, or the impacts up and down the pipeline. Maybe we vented about widespread institutional acquiescence to the narrative that “AI is inevitable.” We might have exchanged stories about being labeled “unreasonable,” “idealistic,” even “Luddites.”
It recently dawned on me that AI would be a major topic that I will report and write about for the next decade. So I read about 150 books, reports, studies and articles to develop a concrete understanding and political orientation towards this technology that nobody can shut-up about (myself included).
What I found is evident to anybody paying attention: The most powerful corporations and their government co-conspirators wield AI as a weapon to wage class war. They are making trillion-dollar gambles that, if successful, will reap enormous profits at the expense of the rest of us.
However, these companies have shown their cards. They are deploying an unprecedented amount of capital toward data center development, placing massive bets on AI years before their business models are profitable. To rig the game, corporations are bluffing with two pervasive narratives, which are often unwittingly parroted by the otherwise well-intentioned: 1) A frictionless AI-powered future will benefit humanity (techno-optimism), and 2) We are powerless to this technological frontier (inevitability). The ubiquity of these narratives is an industry strategy to flood the zone and coax people into complacency.
But if the slog toward an AI dystopia is stunted or halted, Big Tech’s investments could spectacularly backfire, forcing companies to fold. It’s time to go all-in on AI resistance.
Introducing Ten Reasons to Resist AI
Every week for the next ten weeks, I will dissect an application or impact of AI. We will zoom-in on the corporate titans, including Palantir, Amazon, OpenAI, UnitedHealth, Google and Meta; we will also zoom-out to abolitionist frameworks, historical analyses, carceral systems, and ultimately, what it means to be human. Every article will include a snippet about sites of resistance surfacing in each arena, with resources to learn more. Additionally, I’m collaborating with the inimitable, illustrious artist Dio Cramer who is contributing original illustrations for each upcoming edition.
“The illustrations that accompany these pieces were painted by hand with hand-made watercolors — infused with human thought, care, toil, and intention.” – Dio Cramer
Without further ado, here are the subject areas for the upcoming articles:
Environment
Labor
Surveillance and Policing
Militarism
Algorithmic Racism
Health
Art and Music
Education
Media and Misinformation
Human Dignity
Many in the anti-capitalist left have an intuitive understanding of why AI is bad, even a visceral revulsion toward the concept. So why do the details matter if we already know that we’re against it? Understanding the intricacies of how AI is being deployed and becoming well-versed in the details can guide our movements’ strategies and allow us to do the work of convincing others.
My hope is that in ten weeks, you, dear reader, will be equipped with a serviceable understanding of what AI is, how it’s being applied and what it means for our movements, leaving with a reinvigorated will to resist.
An earnest plea: As corporate media capitulates to the techno-fascists and welcomes AI into the newsroom, independent journalism has never been more important. I spent five months researching and writing this series (largely unpaid) because I wanted to learn, and writing is how I process information, but I could really use your support.
If you’re able to contribute $5/month, paid subscriptions help sustain this work. As a token of my appreciation, I have a few extra treats that will be sent directly to your inbox:
“Songs to Smash a Flock Camera to (Rhetorically Speaking),” a narrative playlist of anti-AI anthems.
“The AI Resistance Required Reading List,” with the most incisive and engaging texts that helped develop this series’ political analysis.
The next two articles in the series, sent ahead of schedule.
(If accessing these articles immediately is crucial for your organizing work, but you don’t have the means to sign up for a paid subscription, please write to me. I will also be releasing the playlist and reading list for free when the series concludes.)
Free subscriptions and sharing with friends are also incredibly helpful, and I appreciate you all!
Some big-picture questions
Some recurring questions emerged as I was researching this series and discussing with others. These questions will be explored further throughout the ten parts of this series. Then, the conclusion will offer an AI resistance framework. This series won’t definitively answer all your questions, but it is my modest, dare I say “human,” intent to arm and embolden you to answer them for yourself.
How is “generative AI” different from “traditional AI?” Should we resist both?
Traditional AI systems are algorithms that compile vast quantities of data across many features (inputs), to perform a calculation that yields a simple result — usually a binary “yes/no” or a number (outputs). An example of a traditional AI system is a meteorological model that forecasts the weather using billions of data points on parameters such as humidity, temperature and wind speed. In goes meteorological data, out comes the probability that it will rain. Other traditional AI models include Palantir’s “kill lists” or UnitedHealth’s insurance-denial algorithm (we’ll get to both). Recent technological developments allow traditional AI models to collect and sort vast sums of data, and execute extraordinarily complex equations.
With corporations behind the wheel, traditional (non-generative) AI is a tremendously powerful tool to turbocharge nefarious objectives, such as building surveillance infrastructure across the world (we’ll get there too).
Generative AI algorithms also use inputs to perform a calculation, but the difference lies in the model’s outputs. Unlike traditional AI, generative AI outputs can be unpredictable and complex — a product of the billions, if not trillions, of parameters these models are trained on. Depending on how the generative AI model is prompted, it might produce an answer to a question, a college paper, an image, a video, even a (shitty) song. Generative AI systems, sometimes referred to as “large language models,” such as ChatGPT, are trained by compressing large swaths of the internet, and analyzing text for connections between words to produce these complex outputs. While some are blown away by generative AI’s ability to fabricate human ideation, others argue that this simulation is a farce. Generative AI has enormous environmental consequences, and the simultaneous lack of regulation and widespread institutional adoption, including by schools, has severe cognitive impacts.
Can AI be harnessed for good? Is “ethical AI” possible?
Perhaps the answer is yes: that we can dream of another world, with different economic, political and societal structures, and in that world AI could be a tool wielded by the masses to design climate resilient cities, cure intractable diseases, live fuller, longer lives with less toiling, more leisure, and deeper dedication to each other. However, I have seen absolutely no evidence that tech companies intend to prioritize these things. I’m not one to crush dreams, but before we imagine such a future, we must be abundantly clear about the nightmarish reality of how AI is being harnessed.
Is the technology itself the problem, or the way it’s being deployed/who is doing the deploying?
One way of understanding AI is that it is an intensifier of all things. The efficient processing of information is a potent form of power, currently harnessed by the ruling class of tech billionaires. If our north star is dismantling capitalism, then all of our movements are inextricable from AI resistance. To this aim, it is crucial to identify precisely how AI is being deployed, and by whom.
We’ll dive into the Luddite movement against 19th century industrialization in an upcoming piece on AI and labor, but for now, the Luddite orientation to automation technology can be a touchstone for AI resistance. Luddites viewed the motives of their capitalist bosses as evil, rather than the machinery itself. Unbeknownst to those who invoke the term pejoratively, Luddites demonstrated great pragmatism in their tactics, exercising extraordinary restraint to only target machines owned by bosses who were cutting workers’ wages.
Why not a more “pragmatic” demand for AI reform?
Why not focus on reining in AI through regulation and reform rather than a posture of outright rejection? It’s a question often asked by people who understand the harms of AI, but are motivated by pragmatism or persuaded by the two aforementioned narratives (inevitability and techno-optimism).
Regulation would be a welcome step to slow the most harmful applications of AI, and we will discuss campaigns for near-term reform in various arenas. But the objective of capitalism is unfettered economic growth. For their trillion dollar investments to pay off, the most powerful corporations are committed to continuously expanding the applications of AI. We might question whether meaningful regulation is attainable without transforming the economic system underpinning AI proliferation.
How do we fend off the narrative of AI inevitability?
With AI so thoroughly embedded within the technologies and structures that govern our lives, and the constant surround sound of AI marketing, it can feel like accepting AI inevitability is the only reasonable course of action. This is the precise attitude tech companies are banking on when they sign billion dollar checks for Super Bowl commercials. For people engaged in movements, it is our job to be defiant, to insist that our present circumstances are mutable, to imagine a way out, and to get there.
How does personal consumption factor in?
AI has been infused into just about every aspect of our digital world, and I’m not sure that never interfacing with AI technologies is possible. But we do have choices, and those choices do matter. One product of AI’s omnipresence is that we have ample opportunities to say no in our personal lives. Throughout this series, I’ll highlight ways that people are exercising this right, and explore the value of both personal abstinence and collective resistance.
That’s all for now! More next week.
Beautiful introduction to AI. So well researched and thoughtfully analyzed. The writing is superb.
This is a fabulous intro to what I anticipate will be an eye opening series. It’s all around us - there is no doubt! Can’t wait to read the next chapter 👏🏻