Chapter 2: Further Reading

A Brief History of Data and Society

An annotated guide to key sources for deeper exploration of the themes covered in this chapter, organized by topic. Entries marked with a star are especially recommended as entry points.

Ancient and Medieval Data Collection

Scott, James C. Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. New Haven: Yale University Press, 1998.

Scott's landmark study examines how states make populations "legible" through standardized measurement, census-taking, and classification. His concept of "legibility" — the process by which complex, local realities are simplified into categories a state can read and act upon — is essential background for understanding every era discussed in this chapter. The book ranges from Prussian forestry to Soviet collectivization, showing how the drive to simplify and quantify has both enabled governance and produced catastrophic failures.

Higgs, Edward. The Information State in England: The Central Collection of Information on Citizens since 1500. Basingstoke: Palgrave Macmillan, 2004.

A detailed history of how the English state collected information on its citizens from the Tudor period through the twentieth century, including the Domesday Book's legacy, parish registers, the development of vital statistics, and the modern census. Useful for students interested in the deep institutional history of data collection in a single national context.

Colonial Statistics and Scientific Racism

Dirks, Nicholas B. Castes of Mind: Colonialism and the Making of Modern India. Princeton: Princeton University Press, 2001.

Dirks argues that the British colonial census transformed the caste system from a flexible set of local social practices into a rigid, pan-Indian hierarchy. Essential reading for understanding how data collection can construct the social reality it claims to describe — a theme with direct relevance to contemporary algorithmic classification.

Desrosières, Alain. The Politics of Large Numbers: A History of Statistical Reasoning. Translated by Camille Naish. Cambridge, MA: Harvard University Press, 2002.

A comprehensive history of how statistics emerged as both a science and a tool of governance, from early state arithmetic through probability theory to modern statistical inference. Desrosières shows how the development of statistical methods was inseparable from the political contexts in which they were deployed — including colonialism, public health, and economic planning.

Saini, Angela. Superior: The Return of Race Science. Boston: Beacon Press, 2019.

An accessible and rigorously researched account of the history and persistence of scientific racism, including Galton's role in founding eugenics. Saini traces the connection between historical racial classification and contemporary genetic research, showing how the legacy of race science continues to shape data practices today.

The Punch Card Era and the Holocaust

Black, Edwin. IBM and the Holocaust: The Strategic Alliance Between Nazi Germany and America's Most Powerful Corporation. Expanded edition. Washington, D.C.: Dialog Press, 2012.

The definitive account of IBM's role in providing data processing technology to the Nazi regime. Black draws on extensive archival research to document how custom-designed punch card systems facilitated the identification, expropriation, deportation, and extermination of European Jews. Essential reading for any serious engagement with the ethics of technology provision. The expanded edition includes additional documentation discovered after the original 2001 publication.

Aly, Gotz, and Karl Heinz Roth. The Nazi Census: Identification and Control in the Third Reich. Philadelphia: Temple University Press, 2004.

A focused study of how the Nazi regime used census data and population registration systems as instruments of persecution. Complements Black's corporate focus with a detailed analysis of the state's administrative machinery.

The Database State and Privacy Law

Rule, James B. Privacy in Peril: How We Are Sacrificing a Fundamental Right in Exchange for Security and Convenience. New York: Oxford University Press, 2007.

Rule, a sociologist who has studied privacy and surveillance for decades, provides a historical account of how personal data systems evolved from paper files to electronic databases and how governance mechanisms have struggled to keep pace. Particularly strong on the National Data Center debate and the development of the Fair Information Practice Principles.

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

Solove traces the evolution of the "digital person" — the data double constructed from records held by government agencies, corporations, and data brokers. The book bridges the database era and the internet era, showing how legal frameworks designed for one technological context have been stretched to cover another.

The Internet and Surveillance Capitalism

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

The most influential account of how technology companies transformed personal data into a new form of capital. Zuboff's concept of "surveillance capitalism" — an economic logic that claims human experience as free raw material for commercial extraction and prediction — has become a foundational term in data ethics discourse. Dense but rewarding; Chapter 3 ("The Discovery of Behavioral Surplus") is an essential starting point and connects directly to Section 2.5.2 of this chapter.

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

Pasquale examines how opaque algorithmic systems in finance, search, and reputation scoring operate beyond public scrutiny. The book's analysis of credit scoring algorithms connects directly to Section 2.4.3's discussion of FICO and the principles of reduction, opacity, consequentiality, and disparate impact.

Big Data, Prediction, and Feedback Loops

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

A highly readable account of how predictive models in policing, education, hiring, and insurance create feedback loops that disproportionately harm marginalized communities. O'Neil, a mathematician, combines technical understanding with compelling case studies. Her analysis of predictive policing resonates directly with Eli's ShotSpotter experience in Section 2.6.2.

Eubanks, Virginia. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York: St. Martin's Press, 2018.

Eubanks examines three case studies — an automated welfare eligibility system in Indiana, a coordinated entry system for homeless services in Los Angeles, and a predictive child abuse model in Allegheny County, Pennsylvania — showing how data systems designed to help vulnerable populations can instead surveil and punish them. A powerful illustration of the "Burden Falls Downward" dynamic.

AI, Generative AI, and Data Provenance

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

Crawford maps the material infrastructure of AI — from lithium mines to data labeling warehouses to server farms — showing that artificial intelligence is neither artificial nor particularly intelligent but rather a system of extraction and power. Her historical framing connects AI to earlier systems of classification and resource exploitation discussed in this chapter.

Benjamin, Ruha. Race After Technology: Abolitionist Tools for the New Jim Code. Cambridge: Polity Press, 2019.

Benjamin coined the term "the New Jim Code" to describe how technology reproduces racial hierarchies under the guise of innovation. The book connects the history of scientific racism (Section 2.2.2) to contemporary AI systems, arguing that racial bias is not a bug but a feature of technologies designed within and for unequal societies.

Broad Overviews

Bridle, James. New Dark Age: Technology and the End of the Future. London: Verso, 2018.

A provocative essay collection arguing that the proliferation of data and computational thinking has not made the world more comprehensible but less so. Bridle's discussion of "computational thinking" as a worldview — and its limitations — provides a philosophical counterweight to techno-optimism.

These readings are recommendations, not requirements. Start with the sources most relevant to your interests and the questions that provoked you most in this chapter. For students working on exercises from Part E (Research and Extension), the sources above provide strong starting points for deeper investigation.