In May 2024, the Saint Pierre International Security Center (SPCIS) launched the “Global Tech Policy at the Forefront” series, featuring conversations with leading experts on the impact of emerging technologies—such as AI, blockchain, biometrics, and robotics—on global governance and public policy. These interviews are shared across SPCIS platforms, including WeChat, the website, and LinkedIn.
On October 17th, we had the pleasure of speaking with Professor Kean Birch, Director of the Institute for Technoscience & Society at York University, Canada, where he also holds the Ontario Research Chair in Science Policy. With a career that spans studies in biotechnology, biofuels, and low-carbon technologies, Birch is now primarily focused on the political economy of personal data and the expanding influence of Big Tech in the digital economy. His research explores data assetization—the process of turning personal data into economic assets.
In this interview, Birch shares his thoughts on the growing assetization of personal data, Big Tech’s rent-seeking practices, the challenges posed by generative AI, and the future of data governance. His insights offer a critical perspective on the governance of data and digital assets, highlighting the socio-economic implications of emerging technologies and the need for stronger regulatory frameworks. All content has been reviewed and authorized by Kean Birch.
Naikang: Good morning, Professor Birch. Thank you for joining us today. Let’s start by discussing your work and recent research. Specifically, could you explain what you mean by “techno-scientific capitalism”?
Prof. Kean Birch: Thank you for the invitation, Naikang. I’ve been working in the field of Science and Technology Studies for over 20 years, especially the study of the entanglement of technoscience and finance which I define as techno-scientific capitalism. The field of STS examines the social, political, and economic forces shaping science and technology, as well as their implications for society, politics, and the economy. For the last six or seven years, my research has focused on data, particularly around the political economy of data.
Currently, I’m interested in personal data and its role in techno-scientific capitalism. My theoretical work looks at assetization and rent-seeking practices, or rentiership—essentially how economic rents are constructed and extracted from data. On the practical side, I explore how personal data are controlled, especially by large tech companies. I’ve recently published a book, Data Enclaves, which discusses how control over data has become concentrated within these “big tech” firms, especially U.S. companies like Apple, Amazon, Alphabet (Google), Meta, and Microsoft. These firms hold immense market power, and data is central to their value.
Naikang: Could you explain the different ways these companies profit from data? Do they all follow the same model?
Prof. Birch: While we often group them under the term “big tech,” they operate differently. The term “big tech” refers to their scale and influence, which makes it difficult for competitors to challenge them. But they are not homogeneous. For example, companies like Apple have a “closed ecosystem” model, where they tightly control their hardware, software, and services. Amazon, on the other hand, benefits from economies of scale, which allows it to dominate sectors by securing cheaper financing.
Google’s model is driven by user engagement, specifically through personal data acquired via its services. For instance, they spend billions to secure default search engine status on devices like iPhones. This strategy is about acquiring “traffic”—or users—whose data can then be monetized, mainly through online advertising.
Increasingly, tech firms ‘game’ the economy—they reflexively seek to understand how the economy works and adjust their strategies and practices to benefit themselves. For example, there are allegations of big tech companies using competitor data to create their own superior products, exploiting their market position.
Naikang: You’ve also mentioned the concept of “parasitic innovation.” Could you elaborate on that?
Prof. Birch: Parasitic innovation refers to the way some companies extract value from users without necessarily providing corresponding benefits. A clear example is how many digital products are sold not as goods but as services bound by restrictive licenses. For instance, when you buy an e-book, you’re not really buying it—you’re licensing it, and the provider can control how you use it. This extends to other products like printers, where manufacturers can limit their functionality unless you use their specific, often expensive, supplies.
This model constrains users by limiting their ability to fully own and control the products they purchase. It’s a growing issue in sectors like agriculture, where farmers are bound by software licenses that prevent them from repairing their own equipment.
Naikang: Let’s talk about emerging technologies like AI. How do you see artificial intelligence, particularly generative AI, fitting into this landscape? Does it intensify rent-seeking behavior?
Prof. Birch: Generative AI is particularly fascinating but also problematic. Its political economy revolves around compute—the massive amount of data and expensive computational power required to train these models. While generative AI has gained significant attention, its practical use cases are still limited. I’ve found it largely ineffective myself for professional tasks like research because it often generates incorrect or misleading information. The same applies elsewhere, such as legal work where lawyers have got in trouble for using it.
Generative AI also relies heavily on free access to data, including copyrighted material, which raises legal and ethical concerns. If courts rule in the future that companies can no longer use copyrighted material without permission, the cost of training AI models will skyrocket. Moreover, the infrastructure needed to support generative AI—such as data centers and computing power—demands enormous energy, which could have serious environmental and economic implications.
Naikang: Given the challenges surrounding data governance, what policy recommendations would you suggest to ensure data is used responsibly and for the public good?
Prof. Birch: I believe the market-driven approach to data governance has failed to adequately protect individuals. One solution I propose is the creation of a data wealth fund, modeled after natural resource wealth funds like Norway’s oil fund. The idea is to treat data as a public asset. Companies that collect data would be required to deposit it into a national data wealth fund. This data could then be used under strict conditions, ensuring transparency and accountability.
Such a system would be based on creating a public entity – arms-length from government - to regulate who can access data and for what purposes, while also generating revenue through fees or licenses. Citizens could also have a say in how their data is used, potentially preventing its exploitation for purposes like facial recognition without consent.
Naikang: But given the cross-border nature of data, how would this work internationally?
Prof. Birch: It’s true that data transcends national borders, but countries can still impose regulations on companies that operate within their jurisdiction. The EU’s General Data Protection Regulation (GDPR) is a good example of how national or regional regulations can have global influence. Companies that want to operate within the EU must comply with GDPR, and we could apply similar principles to data governance on a national level.
Naikang: Thank you, Professor Birch, for sharing your valuable insights on the complexities of data governance, the role of Big Tech, and the evolving landscape of digital capitalism. This conversation has been incredibly thought-provoking, and I believe our audience will greatly benefit from your analysis. We’ll prepare the transcript and send it to you for review. I hope this is just the beginning of an ongoing dialogue, perhaps with a future guest lecture at SPCIS.
Prof. Birch: Thank you, Naikang. It’s been a pleasure discussing these important issues. I look forward to continuing the conversation in the future. Have a great day!
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