W47 - Reification and Alienation under Big Data

Last week, the State Administration for Market Regulation released an antitrust draft opinion aimed squarely at major internet firms. To gauge its impact, just look back at the candlestick charts.

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

A complex individual is plastered with labels and, as a kind of data asset, is priced and traded in the market. That inevitably brings to mind the concepts of reification and alienation.

Reification and alienation are concepts from Marxist thought. To put it simply: reification is when social relations between people are transformed into relations between things — in other words, commodified exchange relations. Alienation can be understood as reducing human value to a series of data points and metrics, and using those measures to establish comparison mechanisms and even hierarchies among people.

Look at the “tags” we talk about now — aren’t they the product of that process of alienation? Whether alienation is good or bad is a far more complex question beyond this scope.

I’ll share two more viewpoints.

One comes from Li Xiang: “Platform companies are particularly powerful today because, beyond traditional economies of scale, they also possess network effects and data intelligence.” The implication is that modern monopolies are harder to confront than industrial trusts like Standard Oil.

The other comes from a somber Yuval Harari. His point is roughly that data, as the most important asset of the 21st century, makes the struggle of the masses against being marginalized comparable in scale to the 20th-century struggle against exploitation.

Viewed this way, the nature of contemporary monopolies is no longer limited to market and commercial realms.

What can we do? I’ve read some commentary and two approaches seem worthwhile: one is to assume greater responsibilities beyond commercial aims — corporate social responsibility, which my team has long emphasized. The other is decentralized analysis and decision-making, i.e., “edge intelligence” technology.