Tech&Society: Data, Compute, Labour: On the Political Economy of AI
Aspen Institute España and Fundación Telefónica held the fourth and last session of the 2020 edition of the Tech&Society Program last, Tuesday 1st of December with a debate entitled “Data, Compute, Labour: On the Political Economy of AI” with Nick Srnicek, lecturer in Digital Economy at King’s College London. Isabel Cruz-Conde, Program Director at Aspen Institute España moderated the session.
Description of the session:
Pivotal to the future of the political economy of artificial intelligence (AI)—and indeed, the future of the current technology giants—is the question of whether or not AI is a centralizing technology. When we turn to the existing research on AI’s impact on the economy, however, nearly all the attention has been on what we might call the automation / productivity channel, with discussion centered around whether, when, and how the spread of machine learning will automate and/or augment existing jobs. In this reading, AI is simply another labor saving / augmenting technology in a long line of such technologies. Much less attention has been given to how the nature of AI today may facilitate the concentration of capital, but this neglect has important consequences. For instance, one of the common arguments made by the defenders of today’s technology giants is that their monopoly power is more precarious than it appears because of the ever-present threat of a disruptive innovation. IBM’s mainframe monopoly lost out to personal computers; Microsoft’s personal computing powerhouse lost out to mobile; and today’s monopolies will eventually see similar disruption. Yet if the next major technologies are, for example, capital-intensive and have high barriers to entry, then we have good reason to believe disruption is unlikely. An understanding of the political economy of AI is therefore essential for understanding the stability of the current balance of power—and also for determining how the tech giants are consolidating power and acting strategically today. This knowledge is also crucial to our understanding of how the centralization of capital will play out across the global economy as American and Chinese platforms expand across the planet. In response to this gap in the literature, this talk examined the question of AI centralization in light of three key inputs: data, compute, and labor. Each of these inputs offers important insights into the global political economy of AI and its future trajectories.
Nick Srnicek (Canada, 1982) is a lecturer in Digital Economy at King’s College London. He holds a PhD in International Relations and was editor of Millennium: Journal of International Studies. Srnicek investigates around the interaction between the political economy and new digital technologies. In his articles he analyses the threats and opportunities of the new economic-social scene following the appearance of the digital with a radical break perspective. In this direction, he is co-author of ACCELERATE: A Manifesto for an Accelerationist Politics (2013) together with Alex Williams, which made a major impact worldwide and was translated into several languages. He also co-authored Inventing the Future: Postcapitalism and a World without Work (Verso, 2017), where the two explore a re-structuring of the labour market in which people are liberated thanks to technological intervention. The latest book he has published in Spain is Platform Capitalism (Theory Redux, 2016). He is currently working on his new publication After Work: The Fight for Free Time (Verso, 2019), together with Helen Hester. He participated as a speaker at the 1st Open City Biennial of Thought in Barcelona.