User refusal to share data, not technical limits, is the core obstacle to prediction

Evidence

Of critical importance to our story is the scientists’ observation that the most challenging sources of friction here are social, not technical. Friction arises when users intentionally fail to provide information for no other reason than that they choose not to. “Unfortunately, user profile information is not always available,” the scientists warn. Users do not always “voluntarily” provide information, or “the user profile may be incomplete… and hence not comprehensive, because of privacy considerations, etc.” — Shoshana Zuboff, The Age of Surveillance Capitalism, 248

Categorization

  • DEEPTHINKING: The admission inside Google’s own patent that users’ deliberate non-compliance — their ‘friction’ — is the fundamental constraint on prediction marks an early private identification of user privacy choices as the enemy, a seed of the entire surveillance-capitalism thesis that refusal, not absence of data, is the bottleneck.
  • QUESTION: Worth chasing: How did Google’s engineering teams frame user privacy ‘friction’ internally, and did responses shift from accommodations (satisfying the friction) to circumvention (bypassing it)?
  • XREF: This ‘social, not technical, friction’ framing anticipates the book’s later account of ‘rendition’ and the assimilation-to-text, and echoes Zuboff’s broader argument that users are cast as obstacles to be overcome. — connects to: The digital divide turns on who can analyze data, not who owns it — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 288; Behavioral prediction markets treat people as raw material and targets, never as participants — Shoshana Zuboff, The Age of Surveillance Capitalism, 1029; Only legal compulsion can force access to prediction data — Shoshana Zuboff, The Age of Surveillance Capitalism, 1544 (+2 more)

Broader Connections