Information Asymmetry in Data Supply Chain

When upstream participants (AI trainers) lack clear understanding of downstream participants' (data collectors') true needs, quality standards, and long-term purchasing intentions, downstream actors tend to over-innovate, duplicate investments, and send false demand signals. The efficiency of a data supply chain is determined not by data volume, but by the degree of consensus between parties on true value.

Articles on this principle

• Robots Need Data, Collection Companies Proliferate: The Cost of Supply Chain Asymmetry

  When 97 companies rush to collect "robot training data" using gimmicks like free cleaning services, VR games, and remote operation—it reveals a deeper truth: nobody actually knows which data has value, or how much it's worth.