W47 - Reification and Alienation under Big Data

Last week the State Administration for Market Regulation released an antitrust draft opinion targeting major internet companies. To gauge its impact, just look at the K-line charts.

Coincidentally this week I saw our “panoramic” platform for operating users based on data; the richness of user tags exceeded my expectations. Each user’s travel routes, work details, dining preferences, and leisure activities record not only consumption and wealth but also emotions and desires.

A complex individual is covered in tags and treated as a data asset, priced and traded on the market. This inevitably makes me think of the concepts of reification and alienation.

Reification and alienation are concepts from Marxist thought. To put it simply—quite superficially—reification is the transformation of social relationships between people into relationships between things, i.e., commodified exchange relations. Alienation can be understood as reducing human value to a set of data and metrics, and using that reduction to create comparison mechanisms and even hierarchies among people.

If you look at the “tags” we talk about, aren’t they the product of the process of alienation? Whether alienation is good or bad is far more complicated and beyond this scope.

I’ll share two more perspectives.

One comes from Li Xiang: “Platform companies today are especially powerful because, beyond traditional scale effects, they also have network effects and data intelligence.” The implication is that today’s monopolies are harder to deal with than industrial trusts like Standard Oil.

The other comes from a melancholic Yuval Harari. The gist is that data, as the 21st century’s most important asset, makes the struggle between the public and the “marginalized” comparable in scale to the 20th century’s struggle against the “exploited.”

Seen this way, the nature of modern monopolies is no longer limited to markets and commerce.

What can we do? I’ve read some commentary and two approaches seem worthwhile: one is to take on more responsibilities beyond business—what my team has long emphasized as corporate social responsibility; the other is decentralized analysis and decision-making, namely “edge intelligence” technology.