Cover of Automating Inequality

Automating Inequality

Virginia Eubanks

Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. She argues that these tools create a 'digital poorhouse' that profiles, polices, and punishes the poor, operating more quickly and at greater scale than the physical poorhouses of previous generations.

5 score
#544 overall

Score based on developer article recommendations — not sales data or reviews.

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🟢 Developer Verdict

Examines how data mining, policy algorithms, and predictive models create a 'digital poorhouse' that profiles and punishes the poor.

Read this if

  • You want to understand the social impact of data science.
  • You are concerned about algorithmic bias and inequality.
  • You seek to grasp the ethical implications of tech on vulnerable groups.

Skip this for now if

  • You are looking for hands-on technical guidance or code examples.
  • You expect a deep dive into machine learning model architectures.
  • You prefer content focused on practical solutions rather than systemic issues.
Developer signal: Limited Data · 0% 1 analyzed mentions

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