The New Enclosure: How AI is Privatising Our Cognitive Commons

The rolling green fields of the British countryside, crisscrossed by ancient hedgerows, evoke an image of timeless tradition. Yet, this landscape is not natural; it is the indelible mark of a profound historical transformation known as the “Enclosure Movement.” Understanding this centuries-long process is not merely an academic exercise; it could offer a chillingly prescient lens through which to view the socio-economic upheavals unfolding today as artificial intelligence reshapes our world.

The Past: When Land Became Private

For centuries, much of the arable land in Britain was managed communally under an “open-field” system. Villagers held scattered strips of land within large, unfenced fields, and crucially, they shared access to vast “commons” - lands vital for grazing animals, gathering firewood, and supplementing meagre diets. These common rights, though often informal, were the bedrock of rural survival for generations of ordinary people.

The enclosure movement, which gained significant momentum from the 12th century but reached its fever pitch between 1750 and 1860, systematically dismantled this communal system. Driven by wealthy landowners, keen to adopt new agricultural innovations and maximise profits, ‘Acts of Enclosure’ were passed by Parliament, consolidating scattered strips into large, privately owned farms, ring-fenced by hedges and stone walls.

The economic rationale seems very reasonable: enclosed land allowed for efficient crop rotation, selective breeding, and greater productivity, fueling Britain’s agricultural revolution. But the social cost was immense. Smallholders, unable to afford the fencing and legal fees, were often forced to sell their plots. The landless poor, stripped of their vital common rights, lost their means of subsistence. They swelled the ranks of wage-dependent agricultural labourers or migrated to nascent industrial towns, forming the proletariat that would power the factories of the Industrial Revolution.

Enclosure concentrated immense wealth and power in the hands of a few, while simultaneously creating a dispossessed, mobile labour force. It was a profound act of privatisation, transforming a shared resource into a controlled asset, and irrevocably altering the fabric of society.

The Present: Enclosing the Cognitive Commons

Now, let’s fast forward. Today, we are witnessing a similar, epoch-defining enclosure: not of physical land, but of our cognitive and creative commons.

For decades, the internet fostered an illusion of infinite, shared digital space. Public web data, open-source code, academic research, artistic styles, and the collective intellectual output of humanity forms a vast, freely accessible resource. This was our modern “commons,” a space for learning, creating, and connecting.

However, a new class of ‘Platform Lords’ and Tech Oligarchs has emerged. They are using this public intellectual commons to train sophisticated Artificial Intelligence models. These Large Language Models (LLMs), image generators, and predictive algorithms ingest unimaginable quantities of data, distilling the essence of human knowledge and creativity. Once trained, these powerful models are then enclosed behind proprietary APIs, patents, and paywalls, transforming a public resource into a private, revenue-generating asset.

Consider the parallels:

The Commons: Our shared digital and intellectual legacy (public data, open-source knowledge, collective human skills).
The Hedges/Enclosure Acts: Proprietary AI models, APIs, and patents that privatise access and control over this synthesised knowledge.
The Landowning Gentry: A handful of tech giants who own the foundational AI models, dictating the terms of their use and accumulating unprecedented wealth.
The Displaced Commoners: Millions of knowledge and creative workers - copywriters, paralegals, translators, customer service agents, coders, even artists, whose skills are being devalued, augmented, or outright automated by AI.

Just as the agricultural revolution demanded a re-evaluation of land ownership, the AI revolution demands we reckon with the ownership and control of intelligence itself.

The Future: Emerging Outcomes and Urgent Questions

If history is any guide, the consequences of this new enclosure will be profound and far-reaching. We can project several emerging social, economic, and employment outcomes:

The land enclosures created a ‘useless class’ of people whose traditional way of life was rendered obsolete. AI threatens to do the same for a significant portion of the cognitive workforce. Without intervention, society could polarise into:

The AI Owners: A tiny elite controlling the foundational models and deriving immense profits.
The AI Users: Highly skilled professionals who leverage AI as a powerful tool to augment their capabilities, often at the highest echelons of society.
The AI Displaced: A vast population whose jobs have been automated, forced into low-wage service or ‘gig’ work, or struggling to find purpose in a world that no longer values their traditional skills.

The deeper crisis here is not just economic, but existential.

For many, professional identity is intrinsically linked to self-worth. If traditional avenues for meaningful work diminish, how do we foster social cohesion and individual purpose?

Urgent Question: How do we decouple human value from economic output? One way would be to elevate the status of non-market activities like caregiving, community building, and creative pursuits, recognising them as essential to a flourishing society.

2. Extreme Wealth Concentration & the Productivity Paradox

AI promises unprecedented productivity gains, leading to massive corporate profits and economic growth. However, if these gains are captured almost exclusively by the owners of the AI, we face (even more) extreme wealth concentration. We could enter an era of a “productivity paradox,” where GDP soars, but median wages stagnate or decline, and prosperity becomes increasingly uneven.

Urgent Question: How do we ensure the wealth generated by AI is broadly distributed? Could we fundamentally rethink our taxation systems? A ‘robot tax’ or a tax on AI-driven corporate profits could fund new social safety nets. Policies that mandate profit sharing or foster employee ownership of AI-powered enterprises could also distribute the benefits more widely. Relying on “policy” and governmental intervention is a mistake as these are driven by the commercial needs of the country-as-a-business.

3. The Redefinition of Work & Education

The enclosure movement created a mobile, flexible labour force for factories. AI will redefine ‘work’ itself, shifting it from performing tasks to defining problems, asking the right questions, and orchestrating complex systems. The most valuable human skills will be those AI cannot replicate: critical thinking, emotional intelligence, complex problem-solving, ethical reasoning, and genuine, novel creativity. Not to mention manual or hands-on work which robotics can’t (yet) replicate.

Urgent Question: How do we prepare society for this new landscape of work? Our education systems, currently geared towards churning out task-doers, must undergo radical reform. I think most would argue that this is not a new need, however for this specific situation, we need to teach meta-skills: how to learn, how to adapt, how to collaborate with AI, and how to maintain uniquely human capacities in an increasingly automated world. Lifelong learning, heavily subsidised and widely accessible, will become not a luxury, but a societal necessity.

Learning from History to Chart a New Course

The lesson of the land enclosures is not that technological progress is inherently good or bad, but that its societal impact is profoundly shaped by the policy choices we make. The Gutenberg parallel offers another historical lens on this same pattern — how transformative technology can both democratise and concentrate power. The original enclosures were driven by economic efficiency but resulted in widespread suffering and social dislocation because the benefits were not equitably shared, and the dispossessed had little voice or recourse.

We stand at a similar precipice today. The AI enclosure is already underway. We cannot, and should not, stop the advance of this powerful technology. But we absolutely can, and must, decide how its immense benefits are distributed and how its inevitable disruptions are managed.

Ignoring these parallels risks repeating history’s mistakes on an infinitely larger scale. Proactive, ethical, and visionary policy-making is not just desirable; it is essential to prevent a future where a few thrive on the enclosed cognitive commons, while the many are left searching for purpose and sustenance in the digital wilderness.