While I don’t necessarily agree with all points made by these respective works, I have found them valuable for expanding (and challenging) my thinking on the human side of data-intensive systems. This list is neither static, nor frequently updated, but I always appreciate suggestions. Titles are written in the French grammatical style generally because that is the singular piece of French grammar that I quite like.

Labor perspective of digital piecework and/or modern computing:

  • Work without the workers (Peter Jones)
  • Behind the screen (Sarah T. Roberts)
  • Ghost work (Mary Gray, Siddharth Suri)
  • Encoding race, encoding class (Sareeta Amrute)
  • What you are getting wrong about Appalachia (Elizabeth Catte)

Critiques of modern data-intensive systems:

  • Race after technology (Ruha Benjamin)
  • Algorithms of oppression (Safiya Noble)
  • Automating inequality (Virginia Eubanks)
  • Weapons of math destruction (Cathy O’Neil)
  • Everybody lies (Seth Stephens-Davidowitz)
  • Invisible women (Caroline Criado Pérez)
  • Data feminism (Catherine D’Ignazio, Lauren Klein)

Environmental impact of data-intensive systems:

  • Atlas of AI (Kate Crawford) [chapter 1]
  • The politics of bitcoin (David Golumbia)

Technical inspections of data and missing data:

  • Redacted (Lilly Irani, Jesse Marx)
  • Artificial unintelligence (Meredith Broussard)
  • All data are local (Yanni Loukissas)

Techno-solutionism approaches to bias and their critiques:

  • The ethical algorithm (Michael Kearns, Aaron Roth)
  • The promise of access (Daniel Greene)
  • The internet police (Nate Anderson)

Historical (or situated) discussions of computing ethos:

  • From counterculture to cyberculture (Fred Turner)
  • Your computer is on fire (Mar Hicks, Thomas S. Mullaney, Benjamin Peters, Kavita Philip)
  • Silicon values (Jillian York)

Complexity of data terminology, use, and preservation:

  • Native American DNA (Kim Tallbear)
  • Data is never raw (Lisa Gitelman, ed.)
  • Cloud ethics (Louise Amoore)

Data literacy, communicating data, and data ownership:

  • W. E. B. Du Bois’s Data Portraits: Visualizing Black America
  • How charts lie (Albert Cairo)

Data interaction monologues:

  • Blockchain chicken farm (Xiaowei Wang)
  • Living in data (Jer Thorp)