r/LeftistsForAI

This is something I've been saying for a long time. But it's interesting that it's coming from the slavemaster general himself... ​​​

a founder of ArtCraft used Claude to replace the entire adobe software suite, legally. because it’s ai generated, it’s also in the public domain and absolutely free forever. this would be the first case of ai undermining techno feudalism.

I’ve been thinking about the intellectual commons as a form of collective productive capital, and I’ve run into what seems like an interesting contradiction in how we assign value to knowledge within the attention economy.

The classical tragedy of the commons describes a situation where individually rational consumption of a shared resource produces collectively destructive outcomes. But knowledge is fundamentally different from a pasture or fishery. It’s largely nonrivalrous. My use of an idea doesn’t diminish your ability to use it.

The potential tragedy, then, isn’t overconsumption of knowledge. It’s the underproduction of the intellectual variation, criticism, and refinement necessary for knowledge to continue developing.

Consider the marketplace of ideas as an economic system.

Participants can perform several different functions:
Discovery: Generating new hypotheses, interpretations, and conceptual frameworks.
Refinement: Challenging existing ideas, testing their assumptions, identifying contradictions, and producing better explanations.
Replication: Preserving, communicating, and distributing existing ideas to new audiences.
All three functions have legitimate social value. There’s nothing inherently parasitic about intellectual replication. Civilization would be impossible if every generation had to independently rediscover calculus.

But these functions aren’t rewarded equally.

In the attention economy, the primary market signal isn’t necessarily whether an idea is correct, useful, or has been meaningfully improved. It’s whether the idea successfully captures and retains attention.

A familiar proposition, repeated persuasively, can generate greater economic and social returns than the difficult work of demonstrating why that proposition is incomplete.

This creates an unusual free-rider problem.

Participants can enjoy the social rewards of distributing established ideas without bearing the costs of independently validating or refining them.

More importantly, the economic system distributing those rewards has relatively little incentive to distinguish between genuine intellectual progress and successful rhetorical reproduction.

A provocative argument might receive a million impressions. A careful correction might receive a thousand. The resulting disparity says considerably more about persuasive capacity than epistemic quality.

This isn’t simply a complaint about misinformation, or people repeating talking points. It’s a structural problem in how the intellectual commons is governed.

If the individually rational strategy is to amplify ideas that already command attention, the system may progressively favor convergence around established narratives over the exploration of competing explanations.

Consensus becomes self-reinforcing, not necessarily because a proposition has survived rigorous criticism, but because repetition establishes familiarity, familiarity establishes credibility, and credibility encourages further repetition.

In evolutionary terms, we’re selecting ideas for reproductive success within an attention market rather than selecting primarily for explanatory fitness.

And novelty by itself isn’t a solution. A marketplace saturated with novel but poorly examined ideas can be just as epistemically unproductive as one dominated by established orthodoxy.

The important variable isn’t the quantity of ideas. It’s the capacity of the system to generate, preserve, test, and select meaningful variation.

This becomes particularly interesting with generative AI.

We’re approaching a situation where the marginal cost of producing and replicating persuasive intellectual content can become extremely low, while the cost of independently validating that content remains comparatively high.

AI could dramatically expand our capacity for intellectual refinement by making experimentation, synthesis, and criticism cheaper. But the same technology could also overwhelm the commons with increasingly sophisticated reproductions of existing ideas.

Which outcome dominates may depend less on the intelligence of the systems than on the economic incentives governing their deployment.

If attention remains the principal measure of success, the technology could accelerate intellectual convergence just as easily as intellectual discovery.

So perhaps the tragedy of the intellectual commons is that the institutions which monetize the distribution of knowledge have incentives that are increasingly disconnected from the production of better knowledge.

And that raises what I think is the interesting political-economic question:

If knowledge is a collectively accumulated productive resource, but access to attention determines which contributions receive recognition and economic rewards, does control over the attention economy become a form of control over the intellectual means of production?

More importantly, how do we structure an intellectual commons where discovery, independent criticism, and refinement remain viable collective activities, rather than expensive public goods subsidizing an economy built around their replication?

I’m interested in whether this is best understood as a free-rider problem, an institutional failure of epistemic selection, or a fundamentally different kind of commons problem.

Brewster Kahle started planning the Internet Archive (creators of the Wayback Machine) in 1980 at the MIT AI lab, when he figured that machines worth talking to would need a library to learn from. Forty-six years later, he says the biggest obstacle to that future is a handful of companies that want to control information instead of selling it.

We recorded this conversation live at DWeb Camp 2026 outside Berlin. We talk about where the early web went wrong and what Europe's copyright carve-out could mean for public AI. Brewster also argues that small-scale capitalism belongs on the list of civilizational infrastructure, and tells the story of the credit union he tried to start after the 2008 crisis.

Brewster Kahle is the founder of the Internet Archive and a longtime advocate for the decentralized web.

I understand the optimistic interpretation of this quote, but public access is a lot different than control.

Risk of dependency, concentration of power, and inequality all exist, no?

Who sets the prices? Will certain individuals and institutions not have greater access to this “intelligence” due to their financial situation?

"The same technology that could create the most powerful surveillance state in history could also create unprecedented tools for decentralisation.

For centuries, political organisation was constrained by the limits of human coordination. A community could debate, but only a limited number of people could participate meaningfully. A movement could collect information, but analysing enormous quantities of information required specialists. A cooperative could manage itself, but as it grew larger, administration became increasingly difficult. Scale almost inevitably created hierarchy.

Artificial intelligence changes the economics of coordination."

Would you agree with either sides conclusion, do you support Yangs policy of UBI, or do you think these people are naively trusting of AI development?

Holly Li of OpenAI Dots demo fame.