Further Reading: Chapter 11 — The Data Economy

Arranged from most accessible to most technical. Annotations describe both content and the specific insight each source adds to chapter themes.

1. Zuboff, Shoshana. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs, 2019.

The foundational text for understanding surveillance capitalism as an economic logic rather than merely a technology problem. Zuboff's argument is dense and ambitious — the book runs nearly 700 pages — but rewards careful reading. Begin with Chapters 1–3 (the logic of behavioral surplus), Chapter 8 (the Google origin story), and Chapter 17 (the theory of instrumentarian power). This book provides the theoretical architecture for much of Part 3 and all of Chapter 34. Indispensable for the field.

2. Pasquale, Frank. The Black Box Society: The Secret Algorithms That Control Money and Information. Harvard University Press, 2015.

A crucial complement to Zuboff, Pasquale focuses on the opacity of the algorithmic systems that process behavioral data — the "black boxes" that make consequential decisions about creditworthiness, search rankings, and reputation without meaningful transparency. Particularly relevant to Chapter 11's discussion of the data pipeline and the downstream consequences of data analysis. Accessible legal scholarship with strong empirical grounding.

3. Turow, Joseph. The Daily You: How the New Advertising Industry Is Defining Your Identity and Your Worth. Yale University Press, 2011.

A pioneering study of behavioral advertising before "surveillance capitalism" became common vocabulary. Turow's journalism-grounded account of the advertising ecosystem — how data is collected, what it is used for, and how the industry understands its practices — remains highly relevant. His concept of "social discrimination" through targeted pricing anticipates the "redlining 2.0" discussion in Chapter 14. The most accessible entry point in this list.

4. O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown, 2016.

A data scientist's account of how algorithmic models — built on behavioral data — produce discriminatory, self-reinforcing, and opaque consequences in areas including employment, education, credit, and criminal justice. O'Neil's concept of "weapons of math destruction" (WMDs) — models that are opaque, scaled, and destructive — provides a useful analytical framework for evaluating data pipeline outputs. Highly readable; essential context for Chapters 11 and 36.

5. Federal Trade Commission. Data Brokers: A Call for Transparency and Accountability. FTC, May 2014.

The FTC's landmark report on the data broker industry, based on a year-long study of nine major companies. Provides the most comprehensive regulatory account of what data brokers actually collect, from where, and how they use and sell it. Includes specific case studies and policy recommendations. Essential primary source for understanding the regulatory landscape. Available free from ftc.gov.

6. Duhigg, Charles. "How Companies Learn Your Secrets." New York Times Magazine, February 16, 2012.

The article that introduced most general readers to the Target pregnancy prediction case. Readable and well-reported, it illustrates the power of behavioral inference from retail purchase data and the specific analytics techniques that produce it. A useful case study in the move from observed to inferred data. Freely available online.

7. Solove, Daniel J. The Digital Person: Technology and Privacy in the Information Age. NYU Press, 2004.

Although published before the smartphone era, Solove's account of the legal and philosophical dimensions of data collection remains foundational. His typology of privacy violations — information collection, information processing, information dissemination, and invasion — provides a structured framework for analyzing the harms the data economy produces. Particularly relevant to the aggregation problem and the limits of individual consent models.

8. Simon, Herbert A. "Designing Organizations for an Information-Rich World." In Computers, Communications, and the Public Interest, edited by Martin Greenberger. Johns Hopkins University Press, 1971.

The primary source for Simon's "poverty of attention" thesis — the foundational economic concept underlying the attention economy. A short essay, academically written but accessible. Worth reading in the original to understand how the attention economy concept predates the internet by several decades, illustrating the theme of historical continuity.

9. Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press, 2021.

Crawford's analysis of the AI systems that increasingly process behavioral data situates the data economy within broader systems of extraction — environmental, labor, and political. Her chapter on "Data" provides a critical perspective on how behavioral data is framed as a natural resource while the work of producing it is rendered invisible. Connects Chapter 11's economics to Part 6's analysis of algorithmic systems.

10. Strahilevitz, Lior Jacob. "Toward a Positive Theory of Privacy Law." Harvard Law Review 126, no. 7 (2013): 2010–2042.

An influential legal scholarship article that develops a positive (descriptive) theory of how privacy law actually works versus how it is supposed to work. Strahilevitz's framework for understanding the gap between legal protection and practical exposure is particularly useful for evaluating the data broker regulatory landscape. More technical than the journalistic sources but accessible to careful undergraduate readers.

11. Westin, Alan F. Privacy and Freedom. Atheneum, 1967.

The foundational modern account of privacy as the control of information about oneself, published before the data economy existed in recognizable form. Westin's framework — privacy as a condition of autonomy, intimacy, and democratic participation — provides the normative foundation for evaluating the data economy's consequences. Reading this alongside Zuboff illuminates how much and how little has changed in fifty years of privacy theory.

Further Reading | Chapter 11 | Part 3: Commercial Surveillance