Reading list
This is a list of core texts about algorithmic biases and other topics covered in this book. For a living bibliography, please join our Zotero library.
- Andrejevic, M. (2020). Automated media. Routledge.
- Aradau, C. (2022). Algorithmic reason: The new government of self and other. University Press.
- Aral, S. (2020). The Hype Machine: How Social Media Disrupts Our Elections, Our Economy, and Our Health–And How We Must Adapt. Crown/Archetype.
- Browne, S. (2015). Dark matters: On the surveillance of blackness. Duke University Press.
- Burgess, J., Albury, K., McCosker, A., & Wilken, R. (2022). Everyday data cultures. Polity.
- Cheney-Lippold, J. (2017). We are data: Algorithms and the making of our digital selves. New York University Press.
- Crawford, K. (2021). Atlas of AI. Yale University Press.
- Dencik, L., Hintz, A., Redden, J., & Treré, E. (2022). Data Justice. SAGE.
- Diakopoulos, N. (2019). Automating the news: How algorithms are rewriting the media. Harvard University Press.
- D’Ignazio, C., & Klein, L. F. (2020). Data feminism. The MIT Press.
- Dubber, M. D., Pasquale, F., & Das, S. (2020). The Oxford handbook of ethics of AI. Oxford University Press.
- Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor, St. Martin’s Press.
- Goodman, M. (2015). Future crimes: Everything is connected, everyone is vulnerable, and what we can do about it. Doubleday.
- Harari, Y. N. (2016). Homo Deus: A Brief History of Tomorrow. McClelland & Stewart.
- Hayles, N. K. (2012). How we think: Digital media and contemporary technogenesis. University of Chicago Press.
- Hefner, P. (2022). Human becoming in an age of science, technology, and faith. Lexington Books/Fortress Academic.
- Kaplan, J. (2016). Artificial intelligence: What everyone needs to know. Oxford University Press.
- Kitchin, R. (2014). The Data revolution: Big data, open data, data infrastructures and their consequences. SAGE.
- Kurzweil, R. (2000). The age of spiritual machines: When computers exceed human intelligence. Penguin.
- Langlois, G., Redden, J., & Elmer, G. (2015). Compromised data: From social media to big data. Bloomsbury Academic, an imprint of Bloomsbury Publishing Inc.
- Livermore, D. A. (2022). Digital, diverse & divided: How to talk to racists, compete with robots, and overcome polarization. Berrett-Koehler Publishers.
- Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press.
- O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown.
- O’Neil, C. (2022). The Shame machine: Who profits in the new age of humiliation. Crown.
- Panda, S. K. (2022). The new advanced society: Artificial intelligence and industrial Internet of Things paradigm. Wiley.
- Pariser, E. (2011). The Filter bubble: How the new personalized web Is changing what we read and how we think. Penguin.
- Perez, C. C. (2019). Invisible momen: Data bias in a world designed for men. Abrams.
- Pink, S. (2022). Everyday automation: Experiencing and anticipating emerging technologies. Routledge.
- Ramsay, S. (2011). Reading machines: Toward an algorithmic criticism. University of Illinois Press.
- Scherz, P. (2022). Tomorrow’s troubles: Risk, anxiety, and prudence in an age of algorithmic governance. Georgetown University Press.
- Schneider, S. (2019). Artificial you: AI and the future of your mind. University Press.
- Smith, M. (2015). Targeted: How technology is revolutionizing advertising and the way companies reach consumers. American Management Association.
- Shepard, M. (2022). There are no facts: Attentive algorithms, extractive data practices, and the quantification of everyday life. MIT Press.
- Strengers, Y. (2020). The smart wife: Why Siri, Alexa, and other smart home devices need a feminist reboot. The MIT Press.
- Zerilli, J. (2021). A citizen’s guide to artificial intelligence. MIT Press.
- Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. Public Affairs.
