AI's Apparent Danger Is Its Best Selling Point

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She argues that doomsday hype helps create market bubbles because of investors'“fear of missing out,” adding that such hype“is not unusual in the current era of neoliberal capitalism.”

Argentinian data scientist Marcelo Rinesi, who worked on external testing for OpenAI's DALL·E, has made a similar point. Speaking to Valor International in 2025, he says investment in AI is heavily driven by the perception that it is powerful and dangerous, which is“the only way OpenAI can justify its valuation.”

Major AI companies' descriptions of their capabilities also set them apart from smaller firms, which can market themselves only as useful tools rather than as powerful and potentially dangerous technology.

For individuals, companies and governments, staying out of these partnerships can mean missing the economic benefits and influence over AI's future.

Media outlets tend to amplify dread over AI because it generates traffic and discussion, but the AI industry also has considerable influence on how its products are profiled.

Research from the Reuters Institute found that nearly 60% of AI articles across six major UK news outlets focused on products, announcements, and initiatives, with a third of these outlets relying on industry sources-mostly senior executives-and describing the coverage as largely industry-led.

Major AI companies can also influence coverage by funding media networks. Founded in 2022, the Tarbell Center for AI Journalism funds and trains journalists covering AI.

It receives significant funding from Coefficient Giving, formerly Open Philanthropy, which in turn gets funding from donors including Dustin Moskovitz, a major early investor in Anthropic. The Washington Examiner also documented ties between Tarbell and other early Anthropic figures such as investor Jaan Tallinn, the Skype co-founder.

Tarbell says its journalists are independent, and while that may be true, the networks behind it can still influence what receives attention and coverage. Similar ties exist across the AI industry and media.

Combined with AI companies' ability to place sources in the media and their limited incentive to undermine their own products, the portrayal of unprecedented risks associated with AI tools can instead be interpreted as an intentional effort to boost their value.

Regulatory capture

Companies like Anthropic can also use the same philanthropic networks it indirectly supports, and other means, to influence institutions shaping AI regulation.

Coefficient Giving has funded organizations like Redwood Research and Alignment Research Center, whose work later led to the formation of the nonprofit Model Evaluation and Threat Research (METR). METR is also linked to Anthropic through initial trustees Paul Christiano and Jaan Tallinn.

Since 2023, METR has become a powerful evaluator for the emerging AI oversight systems. Working with major companies including Anthropic and OpenAI, METR's evaluations can influence how models of these companies are assessed and how policymakers understand the associated risks.

While pushing regulation may seem counterintuitive for major AI companies, IE university professor Adriana Hoyos explains that“the more complex the compliance system, the more likely it is to become a fixed cost of entry-and a competitive moat around the companies already at the frontier.”

Security requirements may have legitimate justifications, but as government certification, restrictions on model weights, and controls on advanced chips become standardized, compliance costs may become too much for smaller rivals and startups to absorb.

Major AI companies have helped define what regulation could look like for years. OpenAI's 2023 governance proposal called for an international authority for the most powerful AI systems, allowing for inspection and audits alongside restrictions.

Anthropic's Responsible Scaling Policy similarly ties stronger safeguards to capability thresholds, like assisting with biological and chemical weapons. Restricting access based on capability is already occurring, with Anthropic releasing its Mythos model earlier in 2025 to select corporate customers.

As fear drives demand for regulation, direct and indirect roles of major AI companies in developing regulatory infrastructure can also give them a hand in deciding who gets to participate. Even the ability to define which AI systems qualify as“frontier” can determine which benchmarks AI companies must meet and which practices become mandatory.

This has become more significant as AI has become increasingly politicized. US President Donald Trump downplayed calls to slow down AI development. At the same time, politicians in both parties face growing scrutiny over data centers and are considering tougher stances on AI companies as the midterm elections approach.

With European concerns about overreliance on US Big Tech companies and the EU AI Act expected to roll out in phases through 2028, AI companies need to influence regulation domestically and abroad to protect their interests.

Costs of misunderstanding

In 2023, Politico reported that Open Philanthropy,“in concert with its web of affiliated organizations and experts, is shifting the policy conversation away from more pressing issues - including topics some leading AI firms might prefer to keep off the policy agenda.”