Chapter 2 Exercises: A Brief History of Data and Society

These exercises move from foundational recall through analysis and synthesis. Work through them sequentially or focus on the sections most relevant to your learning goals. Exercises marked with an asterisk (*) are especially suited for group discussion.

Part A: Conceptual Review

2.1. Define "census" in its original Latin meaning and explain why that etymology matters for understanding the relationship between data collection and power.

2.2. The chapter identifies four recurring dynamics across the history of data and society: the Ratchet Effect, Dual Use, the Governance Lag, and the Burden Falls Downward. In your own words, define each dynamic and provide one historical example for each that was not used in the chapter.

2.3. What is the distinction between descriptive and predictive analytics? Why does the chapter argue that this shift is particularly consequential for governance?

2.4. Explain the concept of "digital enclosure" and how it differs from earlier forms of data collection in terms of scale, awareness, and consent.

2.5. What does "information asymmetry" mean in the context of platform capitalism? How does it differ from information asymmetry in the ancient census?

2.6. What is the "data provenance crisis" introduced by generative AI, and why does it represent a qualitatively different challenge from earlier data governance problems?

Part B: Applied Analysis

2.7. The Domesday Book has been called both a "masterpiece of medieval administration" and "an instrument of conquest." Using evidence from Section 2.1.2, explain how both descriptions can be simultaneously true. What does this tell us about the dual-use nature of data systems?

2.8. In Section 2.2.1, the chapter argues that the British colonial census in India didn't just record caste — it constructed caste as a pan-Indian system. Explain the mechanism by which data collection can transform the social reality it claims to merely describe. Can you identify a contemporary parallel?

2.9.* Eli describes his experience with ShotSpotter sensors in Section 2.6.2. Analyze this vignette using the concept of a "feedback loop." Draw a diagram showing how the system reinforces its own predictions, and identify at least two points where the loop could be interrupted.

2.10. Mira realizes in Section 2.4.3 that VitraMed's health risk score functions similarly to a FICO credit score. Using the four principles identified in that section (Reduction, Opacity, Consequentiality, Disparate Impact), compare the FICO score to a hypothetical health risk score. Where are the parallels strongest? Where do health scores raise additional concerns that credit scores do not?

2.11. The chapter provides a table in Section 2.5.2 showing the evolution of data collection relationships from pre-internet to platform era. Extend this table by adding a row for the "AI Era" (Section 2.7). Who is the data collector? Who is the data subject? What characterizes the relationship?

2.12. Francis Galton developed correlation and regression analysis partly in service of eugenics (Section 2.2.2). Dr. Adeyemi argues this doesn't invalidate the tools but "demands that we approach quantitative methods with awareness of their origins." Do you agree with her position? Under what circumstances, if any, should the origins of a methodology affect our willingness to use it?

Part C: Real-World Application

2.13. Choose a data collection system you interact with regularly (e.g., a social media platform, a fitness tracker, a university learning management system, a ride-sharing app). Analyze it through the lens of the four recurring dynamics from Section 2.8.1: - How does it exhibit the Ratchet Effect? - What are its dual uses (beneficial and harmful)? - Where does governance lag behind its capabilities? - Who bears the costs and who reaps the benefits?

2.14.* The 1965 National Data Center proposal (Section 2.4.2) was defeated partly due to public concern about government surveillance. Today, private companies hold far more personal data than the proposed National Data Center would have. Why did the public resist government consolidation of data but largely accept corporate consolidation? Is this distinction rational?

2.15. Identify a current technology company or government program that you believe illustrates the "governance lag." Describe the technology, explain what governance mechanisms exist (if any), and propose what governance innovations might help close the gap.

2.16. The chapter notes that the internet "was not destined to become a surveillance infrastructure" (Section 2.5.2). Research one alternative business model for internet services (e.g., the original Wikipedia model, subscriber-funded journalism, cooperative platforms, public-option social media). How would this model change the data collection dynamics described in the chapter?

2.17. Visit a website you use frequently and read its full privacy policy. How long is it? How readable is it? What data does it claim to collect? Does it mention any of the historical governance mechanisms discussed in the chapter (e.g., Fair Information Practice Principles, consent requirements, data minimization)? Write a one-page analysis.

Part D: Synthesis and Critical Thinking

2.18. The chapter deliberately avoids a "progress narrative" — the idea that data technology has gotten steadily better over time. Instead, it emphasizes recurring patterns. Do you think this framing is accurate or overly pessimistic? Can you construct an argument that the history of data and society is* a progress narrative? What evidence supports each interpretation?

2.19. Consider the following claim: "IBM's role in the Holocaust was no different from a gun manufacturer's role in a shooting. The company made a general-purpose tool; what the customer did with it was not IBM's responsibility." Using evidence from Section 2.3.2 and the ethical framework from Chapter 1, construct arguments both for and against this claim. Which do you find more persuasive, and why?

2.20.* Technological determinism holds that technology shapes society in ways that are largely independent of human choices. The chapter pushes back against this view (see the "Common Pitfall" box in Section 2.5.2). But is there a version of technological determinism that has some validity? Can you identify cases where a technology's characteristics made certain social outcomes highly likely, even if not inevitable?

2.21. The chapter draws parallels between colonial census-taking and modern algorithmic classification. Critics of such analogies argue that comparing contemporary tech companies to colonial regimes trivializes colonialism. Defenders argue that recognizing structural similarities is essential for preventing future harm. Write a 500-word essay evaluating when historical analogies illuminate and when they mislead.

2.22. Using the Applied Framework from Section 2.9, analyze one of the following contemporary data governance debates: - Facial recognition technology in public spaces - Social media platforms' collection of children's data - Employer monitoring of remote workers - Government use of location data during a public health emergency

For each step of the framework (historical precedent, who benefited, governance response, similarities/differences, likely outcomes), provide a substantive answer.

Part E: Research and Extension

2.23. Research the history of the Social Security Number in the United States. When was it introduced, and for what purpose? How has its use expanded over time? How does its history illustrate the Ratchet Effect? Write a 750-word historical brief.

2.24. The chapter mentions the Fair Credit Reporting Act (1970) and the Privacy Act (1974) as governance responses to the database era. Choose one of these laws and research its current effectiveness. Has it kept pace with technological change? What amendments or successor legislation have been proposed or enacted? Prepare a two-page policy brief.

2.25. Investigate a data collection controversy in a country other than the United States or United Kingdom (e.g., India's Aadhaar system, China's Social Credit System, Estonia's digital identity program, Kenya's Huduma Namba). How does the controversy reflect the recurring dynamics identified in Section 2.8.1? How do cultural, political, and economic context change the analysis? Present your findings in a five-minute oral presentation or a 1000-word report.

2.26.* Conduct a "data archaeology" of your own digital life. Using account settings, privacy dashboards, and data download tools (available from most major platforms), compile an inventory of what data has been collected about you by at least three different services. Compare the scale and granularity of this data to the data collected by any historical census discussed in the chapter. Write a reflective essay (500-750 words) on what you discovered.

2.27. The chapter ends with Dr. Adeyemi's observation that "every era of unchecked data power has eventually produced a governance response." Research one historical governance response not discussed in the chapter (e.g., Sweden's Data Act of 1973, Germany's Federal Data Protection Act of 1977, the OECD Privacy Guidelines of 1980). What crisis or controversy prompted it? How effective was it? What lessons does it offer for current governance debates? Write a 1000-word research brief with at least five scholarly sources.

Exercises 2.9, 2.14, 2.18, 2.20, and 2.26 work particularly well as in-class discussions or collaborative assignments.