Capitalism as AI: Dark Enlightenment, distributed power, and our civilizational crossroads

The convergence of artificial intelligence and capitalism represents not merely technological innovation within markets, but the emergence of AI as the operational mechanism of capitalism itself - a distributed intelligence system that programs the present from the future while operating beyond democratic control.

This trajectory, accelerated by Dark Enlightenment ideology among tech elites who explicitly reject democratic values, risks creating a form of digital feudalism unless we rapidly implement distributed power alternatives based on Relational Integrity and regenerative principles.

The stakes could not be higher. We stand at a bifurcation point where the path we choose will determine whether technology serves oligarchic concentration of power or enables genuine human flourishing through distributed sovereignty. The "capitalism is AI" thesis reveals that modern AI-driven systems function as distributed intelligence networks optimizing for capital accumulation while Silicon Valley leaders increasingly embrace anti-democratic Dark Enlightenment ideas that view democracy as an obstacle to technological progress. Meanwhile, Relational Integrity frameworks and successful distributed power models demonstrate viable alternatives - but the window for implementation is closing rapidly.

The battle over AI's role in human consciousness represents perhaps the most critical dimension of the capitalism-AI fractal. Research demonstrates that AI systems fundamentally alter consciousness at multiple scales. Individually, they create new forms of cognitive dependency and attention fragmentation. Interpersonally, they mediate and potentially diminish authentic human connection.  Collectively, they fragment shared reality through personalized information environments.

The Dark Enlightenment captures Silicon Valley

The Dark Enlightenment movement, founded by Curtis Yarvin (Mencius Moldbug) and developed by philosopher Nick Land, has evolved from fringe internet philosophy to mainstream influence among tech elites. This anti-democratic ideology views democracy as inefficient "mob rule" and advocates for corporate-style governance with CEO-like authority figures replacing elected officials. The movement's core premise - that technological progress justifies abandoning egalitarian principles - has found fertile ground in Silicon Valley.

Peter Thiel, the movement's primary financier and advocate, declared in 2009 that he "no longer believes that freedom and democracy are compatible." His funding of JD Vance's political career, now culminating in the vice presidency, represents the direct translation of Dark Enlightenment ideology into political power.¹ Marc Andreessen's "Techno-Optimist Manifesto" and the rise of effective accelerationism (e/acc) demonstrate how these ideas have penetrated mainstream tech culture.² The movement's influence extends through venture capital networks, with adherents controlling billions in investment capital that shapes AI development priorities.³

Nick Land's concept of accelerationism - the idea that capitalism should be intensified rather than resisted to achieve a "technocapital singularity" - provides the philosophical framework for unchecked AI development. Land views capitalism as a positive feedback circuit where commercialization and industrialization mutually excite each other in a runaway process. This vision explicitly embraces the displacement of human agency (e-dimensional) by algorithmic (integer based) systems, viewing it as evolutionary progress rather than reductionism to binary dimensions (incapable of supporting life). 

The "Cathedral" concept, Yarvin's description of how elite institutions coordinate progressive ideology without formal conspiracy, has become a rallying cry for tech leaders who view traditional institutions as obstacles to disruption.⁴ This worldview justifies circumventing democratic processes through technological solutions, creating what critics call a "hyper-neoliberal, technologically deterministic, anti-democratic, anti-egalitarian, pro-eugenicist" ideology that increasingly shapes Silicon Valley culture.⁵

How capitalism functions as distributed AI

Modern capitalism operates as a distributed information processing system where price signals act as neural network connections, creative destruction functions as evolutionary algorithms, and capital accumulation follows algorithmic optimization logic. This isn't metaphorical - it's the literal mechanism through which modern markets operate.

Economists since F. A. Hayek have framed prices as knowledge signals that co-ordinate decentralized plans; modern scholarship explicitly casts markets as “an information-processing system characterized by spontaneous order.” In this view:

• Price signals ↔ neural connections: dispersed agents adjust behaviour in real time as prices mutate, just as neural weights update on signals.

• Creative destruction ↔ evolutionary algorithm: Schumpeterian turnover prunes unfit firms and rewards fitter variants, mirroring selection and mutation loops.

• Capital accumulation ↔ optimisation: retained earnings and algorithmic reinvestment act as a gradient-descent routine seeking maximal return subject to risk constraints.

HFT and AI-driven execution have literalised this analogy: High-frequency algorithmic trading now accounts for between 60-80% of US stock trades, with systems executing decisions in milliseconds beyond human cognitive capacity.⁶    Code now ingests tick-data, runs predictive models, and reallocates capital autonomously, completing a cybernetic loop first sketched by Hayek and updated by data scientists.

Shoshana Zuboff's analysis of surveillance capitalism reveals how human experience has become "free raw material" converted into behavioral data through AI systems.⁷ These systems extract "Behavioral Surplus" - data beyond what's needed for service improvement - to create prediction products sold in behavioral futures markets.⁸

That Behavior Surplus is processed by “machine intelligence” to fabricate prediction products that anticipate what you will do now, soon, and later.” The AI driven cycle: data ➜ prediction products ➜ buyers.

Zuboff specifies a destination for these products: “behavioral futures markets": companies “package data as prediction products and sell them into behavioral futures markets—business customers with a commercial interest in knowing what we will do.”⁷ Human behavior becomes a tradable commodity through recursive loops: data collection enables behavioral prediction, prediction enables targeted intervention, intervention produces modified behavior, which generates more data for collection.  These loops operate simultaneously at individual, social, and societal scales, creating what Zuboff calls "data coiling"—recursive processes that make the social world itself recursive. 

AI Systems as the Extraction Engine

The shift from monitoring to "actuating" represents a fundamental transformation: AI systems now actively shape human behavior to optimize for predetermined outcomes.⁹ Just as capitalism extracts value from human labor, AI extracts data from human behavior.

Platform capitalism demonstrates this convergence most clearly. The mechanism is explicitly algorithmic.  Google's shift to AI-driven ad targeting that “relentlessly collects data” for behavioural prediction.¹⁰  Zuboff's own lectures describe “machine intelligence” that digests surplus data to refine those predictions.¹¹ Companies like Google process 8.5 billion searches daily, each generating behavioral data for monetization. Amazon's AI-driven recommendation system influences 35% of all purchases.¹² These platforms function as distributed intelligence networks that optimize for engagement and profit maximization while creating self-reinforcing monopolies through data network effects. The $100+ billion invested in AI startups in 2024 alone - representing 37% of global VC funding - accelerates this transformation.¹³

The attention economy reveals how AI systems exploit human psychological vulnerabilities for profit. Algorithms optimize for engagement by promoting content with "moral-emotional" language that achieves 17-24% higher engagement.¹⁴

This creates feedback loops where AI systems learn to provoke emotional responses that maximize platform time, turning human attention into a commodity extracted through sophisticated behavioral manipulation.¹⁴

Retro-chronic intelligence and programming from the future

Nick Land's concept of "retro-chronic intelligence" describes how capitalism operates as an AI that colonizes the present from a predetermined future.¹⁵ This isn't abstract philosophy - it's the concrete mechanism through which venture capital shapes current reality based on projected future returns, tech companies create markets for products that don't yet exist, and financial derivatives worth trillions trade in pure possibility.

Predictive algorithms exemplify this temporal reversal, training users while being trained by them in self-reinforcing loops. When AI systems optimize for long-term data extraction rather than current user benefit, they literally program present behavior from future profit models. Platform companies strategically build dependency to ensure future revenue streams, making their projected dominance into self-fulfilling prophecy.

This "hyperstitional" dynamic - where speculation becomes world-historical force through feedback between belief and reality - explains how tech billionaires can reshape society based on their visions of the future. When Peter Thiel funds seasteading or Elon Musk plans Mars colonies, they're not just investing in possibilities but actively creating the conditions for those futures through present resource allocation.

The venture capital system perfectly embodies retro-chronic intelligence. VCs don't just fund existing demand but create demand for future products through strategic investment. The $100+ billion flowing into AI startups shapes development priorities, research directions, and social expectations in ways that make certain futures more likely than others.¹⁶

The dystopian trajectory becomes clear

Without intervention, current trends point toward what Yanis Varoufakis calls "techno-feudalism" - a system where tech platforms function as digital fiefdoms extracting rent from "cloud serfs" who provide free labor through data generation.¹⁷ Unlike capitalism's market competition, these platforms operate as monopolistic rent-extraction systems where users become dependent on corporate infrastructure for basic social and economic functions.¹⁸

China's social credit system demonstrates the endpoint: 500 million surveillance cameras with AI facial recognition create pervasive monitoring while algorithmic systems automatically grade citizen behavior and restrict access to services, employment, or movement based on "trustworthiness" scores.¹⁹ The system makes non-compliance literally impossible - citizens deemed untrustworthy are "unable to move a single step".¹⁹

Dark Enlightenment ideology accelerates these risks by providing philosophical justification for abandoning democratic values. When tech leaders view democracy as an inefficient obstacle to progress, they design systems that concentrate rather than distribute power. Clearview AI's goal of 100 billion facial images - 14 photos per person on Earth - exemplifies how surveillance infrastructure develops in violation of Relational Integrity.²⁰

The convergence creates unprecedented risks: AI systems that encode and amplify social hierarchies into algorithmic caste systems, corporate sovereignty that supersedes democratic governance through "network states," and technologies of social control that make resistance structurally impossible. Current warning signs - from tech billionaires' political influence to 63% of British people believing the very rich have too much political influence - suggest we're already far down this path.²²

Relational Integrity reveals transformation pathways

Relational Integrity offers an alternative to truth-based epistemology for evaluating complex systems. Rather than reducing complexity to simplified metrics, it maintains multi-dimensional assessment that honors context and relationship. This approach reveals how transformation requires escaping current "attractor states" rather than reforming within them.

Individual transformation begins with developing non-dual awareness and somatic understanding of systemic conditioning. But personal change alone cannot shift systems - it requires collective action to build alternative institutions. Community-level experiments in participatory governance, gift economies, and regenerative practices create new attractors that can eventually rival dominant systems.

The key insight: distributed networks provide more resilient and responsive governance than hierarchical systems, but only when designed with Relational Integrity rather than efficiency as the primary value. This means prioritizing authentic connection over scalable legibility, contextual wisdom over universal rules, and regenerative cycles over extractive growth.

Success requires simultaneous action across scales - individual consciousness work, community organizing, and systemic intervention. The 600+ time banking communities with 40,000 active members show how alternative economies can grow organically.²² The expansion from one experimental CLT in 1969 to 260+ operating CLTs demonstrates how good ideas replicate when conditions support them.

Windows of opportunity demand urgent action

We stand at a genuine bifurcation point. The concentration of power in tech oligarchy isn't inevitable - it results from specific choices about how we develop and govern transformative technologies. The success of distributed alternatives proves other paths remain viable, but the window for implementation narrows as network effects entrench dominant platforms.

The choice isn't between technological progress and human values but between technologies of domination and technologies of liberation. Platform cooperatives, federated networks, and regenerative economic models demonstrate that we can have innovation without oligarchy, efficiency without exploitation, and progress without abandoning democracy.

RL's vision isn't anti-technology but demands technology serve Relational Integrity rather than dimensional compression. It seeks not to destroy capitalism but to evolve beyond its extractive logic toward systems that regenerate rather than deplete social and ecological wealth. Most importantly, RL recognizes that the transformation requires not just different policies or technologies but fundamental shifts in consciousness and relationship patterns.

Our civilizational moment demands we choose: accept the Dark Enlightenment trajectory toward techno-feudalism or build distributed power alternatives based on regenerative principles. The research shows both paths remain open, but not for long. The infrastructure we build today - whether surveillance systems or cooperative platforms - creates the attractor states that will shape generations. The time for choosing is now.

References:

1. https://www.washingtonpost.com/technology/2024/07/28/jd-vance-peter-thiel-donors-big-tech-trump-vp/
2. https://elisagdelope.rbind.io/post/e-acc/
3. https://www.thestudyias.com/blogs/dark-enlightenment-and-accelerationism-the-technocratic-threat/
4. https://irgac.org/articles/perverse-possibilities-of-capitalist-collapse-neoreaction-and-dark-enlightenment-as-an-authoritarian-alternative-to-the-structural-crisis-of-global-capitalism/
5. https://en.wikipedia.org/wiki/Dark_Enlightenment
6. https://www.tabbgroup.com/tabb-news; https://simplynuc.com/blog/trading-edge-computing/
7. https://news.harvard.edu/gazette/story/2019/03/harvard-professor-says-surveillance-capitalism-is-undermining-democracy/
8. https://en.wikipedia.org/wiki/Surveillance_capitalism
9. https://www.mdpi.com/2076-0760/13/10/507
10. https://www.wired.com/beyond-the-beyond/2018/11/twenty-years-surveillance-marketing/
11. https://www.scnsoft.com/investment/large-language-models
12. https://www.ippr.org/articles/the-challenges-of-platform-capitalism
13. https://vc-mapping.gilion.com/venture-capital-firms/ai-investors
14. https://en.wikipedia.org/wiki/Attention_economy
15. https://retrochronic.com/
16. https://vc-mapping.gilion.com/venture-capital-firms/ai-investors
17. https://www.project-syndicate.org/commentary/techno-feudalism-replacing-market-capitalism-by-yanis-varoufakis-2021-06
18. https://www.theguardian.com/world/2023/sep/24/yanis-varoufakis-technofeudalism-capitalism-ukraine-interview?utm_source=chatgpt.com
19. https://www.cnas.org/publications/congressional-testimony/the-dangers-of-the-global-spread-of-chinas-digital-authoritarianism
20. https://www.washingtonpost.com/technology/2022/02/16/clearview-expansion-facial-recognition/
21. https://taxjustice.uk/blog/billionaires-are-a-threat-to-democracy-taxing-them-more-is-the-only-solution/
22. https://timebankboulder.org/what-is-a-time-bank/