Make no mistake—AI is owned by Big Tech

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Make no mistake—AI is owned by Big Tech

By Amba Kak et. al., | MIT Technology Review | December 5, 2023

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In the context of the current paradigm of building larger- and larger-scale AI systems, there is no AI without Big Tech. With vanishingly few exceptions, every startup, new entrant, and even AI research lab is dependent on these firms. All rely on the computing infrastructure of Microsoft, Amazon, and Google to train their systems, and on those same firms’ vast consumer market reach to deploy and sell their AI products. 

Indeed, many startups simply license and rebrand AI models created and sold by these tech giants or their partner startups. This is because large tech firms have accrued significant advantages over the past decade. Thanks to platform dominance and the self-reinforcing properties of the surveillance business model, they own and control the ingredients necessary to develop and deploy large-scale AI. They also shape the incentive structures for the field of research and development in AI, defining the technology’s present and future. 

Concentrated power isn’t just a problem for markets. Relying on a few unaccountable corporate actors for core infrastructure is a problem for democracy, culture, and individual and collective agency. Without significant intervention, the AI market will only end up rewarding and entrenching the very same companies that reaped the profits of the invasive surveillance business model that has powered the commercial internet, often at the expense of the public. 

For companies hoping to build base models, there is little alternative to working with either Microsoft, Google, or Amazon.  Many open-source AI projects operate through compute credits, revenue sharing, or other contractual arrangements with tech giants that grapple with the same structural dependencies. In addition, Big Tech has a long legacy of capturing, or otherwise attempting to seek profit from, open-source development. Open-source AI can offer transparency, reusability, and extensibility, and these can be positive. But it does not address the problem of concentrated power in the AI market. 

Regulation could help, but government policy often winds up entrenching, rather than mitigating, the power of these companies as they leverage their access to money and their political clout.  But it’s clear we need to go much further. Now’s the time for a meaningful and robust accountability regime that places the interests of the public above the promises of firms not known for keeping them. 

3 key takeaways from the article

1. In the context of the current paradigm of building larger- and larger-scale AI systems, there is no AI without Big Tech. With vanishingly few exceptions, every startup, new entrant, and even AI research lab is dependent on these firms. All rely on the computing infrastructure of Microsoft, Amazon, and Google to train their systems, and on those same firms’ vast consumer market reach to deploy and sell their AI products. 
2. Concentrated power isn’t just a problem for markets. Relying on a few unaccountable corporate actors for core infrastructure is a problem for democracy, culture, and individual and collective agency. 
3. Regulation could help, but government policy often winds up entrenching, rather than mitigating, the power of these companies as they leverage their access to money and their political clout.  But it’s clear we need to go much further. Now’s the time for a meaningful and robust accountability regime that places the interests of the public above the promises of firms not known for keeping them.

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Topics:  Technology, Artificial Intelligence, Regulation, Competition