Private AI governance vs. military-industrial power: Who shapes the future of autonomous systems?

Indigenous frameworks reject the commodification of knowledge central to Anthropic’s corporate model, instead emphasizing relational accountability and consent in AI development. The Pentagon’s militarized approach to AI mirrors historical patterns of resource extraction and cultural erasure, such as the US military’s use of Indigenous lands for testing grounds. Both entities operate within a paradigm of domination that contrasts sharply with Indigenous worldviews, where technology is a tool for communal flourishing rather than profit or control. The absence of Indigenous voices in this debate reflects a broader erasure of epistemologies that prioritize harmony over hierarchy.

The Pentagon-Anthropic dispute echoes Cold War-era conflicts between military research (e.g., ARPANET) and corporate tech expansion (e.g., IBM’s early computing dominance), but with AI as the new frontier. Historically, private companies have often been co-opted by state security apparatuses, as seen with Google’s Project Maven or Palantir’s surveillance contracts. The tension between Pentagon and Anthropic is not new—it’s a recurring pattern where state and corporate actors compete for control over transformative technologies, often at the expense of public oversight. This dispute also parallels 19th-century debates over railroad monopolies, where infrastructure control determined economic and political power.

In China, AI governance is framed through the lens of 'social credit' systems and state-led innovation, where control is centralized but justified as serving collective stability. European approaches, like the EU AI Act, emphasize risk-based regulation and human rights, reflecting a post-colonial sensitivity to tech imperialism. Meanwhile, in India, debates focus on digital public infrastructure and the need to prevent foreign corporate dominance over AI systems critical to governance. These cross-cultural models reveal that 'control' is not a monolithic concept but a contested terrain shaped by historical trauma, colonial legacies, and developmental priorities.

The scientific consensus highlights that AI systems are not neutral tools but artifacts shaped by training data, funding sources, and institutional incentives. Research shows that militarized AI (e.g., autonomous weapons) increases the risk of escalation and reduces transparency, while corporate-controlled AI prioritizes scalability over safety. Studies on algorithmic bias demonstrate that both Pentagon and Anthropic systems disproportionately harm marginalized communities due to flawed data collection and deployment practices. The lack of independent auditing in this dispute underscores a systemic failure to apply scientific rigor to AI governance.

Artists and spiritual traditions have long warned about the dehumanizing effects of unchecked technological control, from Mary Shelley’s *Frankenstein* to Buddhist teachings on the 'three poisons' (greed, hatred, delusion) in AI design. Indigenous artists like James Luna have critiqued how military-industrial complexes co-opt cultural narratives to justify surveillance and extraction. Meanwhile, Afrofuturist visions, such as those by Octavia Butler, imagine AI as a tool for communal liberation rather than domination, offering a counter-narrative to Pentagon-Anthropic power struggles. These perspectives frame the dispute as a spiritual crisis—one where humanity’s relationship with technology determines its soul.

Scenario modeling suggests that if Pentagon-Anthropic dynamics prevail, AI will evolve into a bifurcated system: one optimized for surveillance and warfare, the other for profit-driven automation, with little space for democratic input. A more equitable future would require decentralized governance models, such as open-source AI cooperatives or municipal data trusts, to counterbalance state-corporate duopolies. Historical precedents like the internet’s early open architecture (pre-commercialization) show that alternative models are possible but require proactive policy interventions. Without such measures, the current dispute will lock in path dependencies that are irreversible for generations.

Marginalized communities—particularly Black, Indigenous, and Global South populations—are the most vulnerable to the Pentagon-Anthropic power struggle, as their data is extracted without consent and their lives are surveilled under the guise of 'security.' Labor movements, such as those in tech (e.g., Google’s 2022 walkouts) and content moderation (e.g., African workers for Silicon Valley firms), highlight how AI governance is also a class struggle. Feminist scholars have critiqued how militarized AI reinforces patriarchal control, while disability rights advocates warn about the exclusionary design of autonomous systems. The absence of these voices in the debate ensures that solutions will remain extractive and oppressive.