Behavioral Advertising Map

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The Squeeze Goal: data Reasonable interpretation — A defensible reading of the evidence, not a single documented result.

Behavioral-surplus harvesting

also: surveillance capitalism · data extraction · behavioral surplus

Your behavior — clicks, dwell time, location, social graph — is captured as raw material well beyond what is needed to provide the service, then refined into predictions about you that are sold. The product is partly a means of producing that surplus.

Vulnerabilities it exploits

  • Status-quo bias & the default effect

    Robust evidence strength: Well-replicated or backed by strong primary evidence.

    Samuelson & Zeckhauser (1988); Johnson & Goldstein, “Do Defaults Save Lives?” Science (2003)

    People disproportionately stick with pre-selected options. The default effect is robust and economically large (e.g., organ-donation opt-in vs. opt-out), which is exactly why pre-checked boxes and opt-out defaults are so powerful.

The evidence

What we actually know

Shoshana Zuboff (2019) Contested evidence strength: Failed or seriously challenged replication — flagged, not settled.

“The Age of Surveillance Capitalism”

PublicAffairs

Argues surveillance capitalism ‘unilaterally claims human experience as free raw material,’ declaring the excess ‘proprietary behavioral surplus’ traded in ‘behavioral futures markets.’ A powerful theoretical lens; parts are contested by economists.

Tim Wu (2016) Mixed evidence strength: Cited, but of uneven or debated replication strength.

“The Attention Merchants”

Knopf

A historical account of business models that capture and resell human attention, linking advertising history to the modern feed. Strong framing source rather than experimental evidence.

In the wild

  • A free app whose real business is the granular behavioral profile it builds and monetizes, not the nominal service it offers.

    Zuboff (2019) on ‘proprietary behavioral surplus’ fed into ‘prediction products.’

  • Default-on tracking and pre-granted permissions that most users never change.

The antidotes

What helps

Evidence-backed

  • Strong privacy defaults and data-minimization (the GDPR/CPRA model) cut the surplus at the source rather than after the fact.

Practical / common-sense

  • Audit and revoke app permissions, opt out of cross-app tracking, and prefer services whose business model isn’t your data.

Where the law stands

Different rules in different places

The rules are not the same everywhere — and they move. We show each jurisdiction separately rather than implying one global rulebook.

  • EUIn force

    GDPR (data minimization, purpose limitation, consent)

    Limits collection to what is necessary and requires a lawful basis — directly constraining surplus harvesting.

  • USIn force

    California CPRA/CCPA

    Grants opt-out of sale/sharing and limits dark-pattern consent; no comprehensive US federal privacy law yet.