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Machine learning and authoritarianism

On pg 258-259 of her Don’t Be Evil, Rana Foroohar poses a question which will become more urgent with each passing year, binding political economy and digital governance together in a way which will define the fabric of social life:

Is digital innovation best suited to an environment of decentralization, in which many firms in the private sector working under smart regulation and within a truly free marketplace are allowed to compete? Or is the best model for the future one of centralization, in which a top-down surveillance state can collect all the data it wants, and allow the companies that it has handpicked to do with it what they like?

What I find worrying is the obvious contingent compatibility between machine learning and authoritarianism. The geometric increase in the value of big data rewards centralisation, the realisation of this value depends on freedom from constraint and its impact is to empower the data-rich actors in a whole range of social, economic and political ways. As she writes later on pg 259:

Still, even if the United States were moving faster on 5G, many believe that it will be easier for a surveillance state such as China to own and harness the data that will be transferred via the 5G chips that will exist in all sorts of products from tires to tennis shoes to fetal heart monitors. That would, in turn, allow Beijing to harness the productivity benefit from such data more quickly. The key idea behind this thinking is that we’ve left the “innovation” stage of artificial intelligence use, and the only thing that matters is the data—whoever can get the most of it, wins.

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