Being Human in the Age of AI, Part 6: The Artificial Family
In last week's newsletter, I explored the deep connection between artificiality and the human experience, emphasizing that "We have always been artificial." This perspective places AI within the long tradition of humanity's use of tools, from ancient cave paintings to today's advanced technologies, arguing that to truly understand AI, we need to recognize it as a continuation of our historical efforts to extend our capabilities.
Which brings me to the recent history: in modern knowledge industries, the traditional distinctions between labor and capital are increasingly blurred. Knowledge workers straddle these roles, creating a new kind of economic elite. However, this shift also introduces precariousness because of the volatile nature of digital platforms and investor whims.
Not surprisingly, knowledge workers (and I am one of them) spend enormous resources on their children, to optimize them for economic success, a process that mirrors algorithmic ways of data optimization, now pervasive in both professional and personal spheres.
Read on for this week's update on the book I am writing with Richard Russell.
I said this last week, and I am going to repeat this once again:
We have always been artificial.
Artificiality is not a new state of affairs: it's part of the history of humanity as such. And we won't understand what AI is and what it could become unless we place it on the longue duree of artificiality. Think back to those first painted hands pressed against a cave wall. Wasn't that, in its own way, a kind of artificial intelligence? A preservation of gesture and presence outside of the immediate moment; an externalized echo of the self. The desire to communicate, to leave a mark, is intertwined with our instinct to create tools, to externalize ourselves through technology.
In our drive to build tools, to manipulate the world around us, we leave an ever-expanding artificial residue. It shapes us even as we shape it. Today's AIs may be complex, their responses seemingly spontaneous, yet they remain artifacts of our own desires and limitations. They are mirrors in a way, reflecting not only our technical prowess but our blind spots, our biases, our eternally unfinished selves. Now, having said that, I am going to take a detour which may seem like it has nothing to do with AI. Stay with me.
There's some irony to the etymology of 'economics.' It has roots in the Ancient Greek word "oikonomia" (οἰκονομία).
- "Oikos" (οἶκος) means "house" or "household."
- "Nemein" (νÎμειν) means "to manage" or "to distribute."
So the original meaning of "oikonomia" referred to "household management." This involved the efficient allocation of a household's resources to meet its needs. Except that economics as a discipline (and the economy as a social phenomenon) has historically neglected the household. It concentrates on production and consumption, stuff made by laborers in factories and sold in markets, all male preserves (historically speaking), while it completely neglects the unpaid - and gendered - labor in the household that sustains this economy of production. The household remains the specter haunting the spreadsheets of economics. Within its walls, we find not only the unpaid labor that fueled the "productive" economy but the very source of that productivity – the bodies and minds of workers. Yet, these are sidelined as 'women's work', a nebulous category dismissed as outside the purview of serious economic study.
Production is accounted for in the economy, while reproduction isn't.
But let's linger in this discomforting irony. If economics truly concerned itself with efficiency, with maximizing well-being, wouldn't it prioritize the very site of human creation? The feeding, clothing, nurturing, and educating done within the home is not a mere precursor to economic value creation, it IS economic value creation. To call it otherwise is a sleight of hand, a magician's trick that obscures the very source of a nation's wealth. It's precisely because production appropriates capital (the stock of future workers, aka children) and labor (unpaid work by women) from reproduction that it's able to sustain itself - capital is always borrowing from the future to fund the present (climate activists know that all too well!). This division is no accident of history. The disavowal of 'reproduction' allowed the exploitation of a vast, unpaid labor force under the banner of love, duty, or biological destiny. The rise of the capitalist economy depended on this sleight of hand, one that continues to perpetuate not only gendered oppression but also a fundamental misunderstanding of what fuels a thriving society. That's it from me on this topic; feminist critiques of economics have said everything there's to be said. Read Sylvia Federici's "Caliban and the Witch" for one take on how the division between production and reproduction was created.
Fast forward a couple of hundred years, and the most profitable sectors of the economy are the knowledge industries: technology and finance, with academia being their poor cousin. In these industries, the distinction between capital and labor as well as that between production and reproduction is losing force. A startup founder coding a web app (as Zuckerberg was famously portrayed) is both labor and capital. You could argue that:
The programmer may be a laborer to the extent their output belongs to Google or Facebook or your choice of Megacorp, but they are capitalists to the extent they own their brain and that brain can travel from Megacorp A to Megacorp B. They are more like the ancillary firms that serve the Detroit Big-3 than they are like the workers on the assembly line.
In a return to feudal social relations, intermarriage between knowledge workers and the reproduction of their main capital (their brains) is central to the new elites. Which explains their self-segregation in certain cities (the infamous creative class) and the enormous investment in their children's lives.
The boundaries blur, and a new caste system arises. The knowledge worker, wielding code and concepts as their weapons, straddles a strange divide. It's a position at once envied and precarious. They hold the keys to the kingdom, but the kingdom itself may shift at any moment. Algorithms change, platforms rise and fall, and yesterday's hottest skill becomes tomorrow's obsolete code.
In this landscape, the old divisions seem less potent. The knowledge worker can both create and own the means of production. But it's an ownership wrapped in a strange dependence - the dependence on ever-evolving infrastructure, on the whims of investors, on the fleeting favor of markets and algorithms. It's a position akin to a feudal lord, beholden to a greater power, but with a scrap of autonomy carved out within their niche domain.
And so, the knowledge worker seeks to perpetuate their unique capital – the ever-sharpening mind. It's a form of reproduction as vital to success as the inheritance of land in ages past.
We see it in the curated childhoods, the elite schools, the careful optimization of young minds for the specific rigors of the knowledge economy. The playground becomes a microcosm of networking, of building the social capital so crucial for future opportunities. Commentators have noticed that AI has precursors in certain modern institutions such as the bureaucracy that aggregate information and make decisions using those aggregates. I am here to tell you that the most common institutional precursor to AI, one in which almost everyone reading this essay is a participant, is the modern knowledge worker family.
That modern family is an engine of optimization. It's not merely about raising individuals; it's about creating portfolios of achievement tailored for a system designed to spot and reward certain forms of hyper-competence. Think about it: the relentless drive to unearth hidden opportunities, to curate the perfect mix of challenge and enrichment, mirrors the logic of the algorithm. It's a micro-level data collection program, amassing metrics and building predictive models about a child's trajectory. We quantify play into "developmental milestones", repackage hobbies as "leadership potential", and see extracurriculars as future resume fodder.
School choice becomes a complex exercise in risk assessment and investment strategy. We pore over rankings, debate pedagogy, and obsess about peer groups as if we were managing a hedge fund. The stakes feel incredibly high, for in this new economy, educational trajectory is the gateway to future capital accumulation. All those hours spent researching the best school districts, the most attractive private schools, the most enriching learning opportunities and extra-curricular activities, the (over) scheduling of children's days to the last minute, STEM tutors and college-prep counselors, club soccer and model UN:
The intelligent home and the school system are where most of us learn to perform information aggregation and optimization functions day in and day out. Is it any surprise that education has been the target of AI for the very longest time?
The ‘knowledge worker family’ returns economics back to its etymological roots - the science of managing the household with data and optimization. There’s even a book about treating the family like a business. The kind of child we want to raise in such a family is the kind who goes on to work at Google or Goldman-Sachs or the World Bank - in other words, a child whose IQ is optimized in exactly the ways in which AI is intelligent.
IQ is AI before AI, isn’t it?
I am done with my detour into the genesis of artificiality and will be back to articulating the sections of the book next week. Not because artificiality has been dealt with (far from it!), but because it needs standalone treatment - I will get to that once I am done with the book summary.