Data Feminism, published in 2020, sheds light on the power dynamics behind data science. The book offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science.

Invisible Women by Caroline Criado Perez is a compelling exploration of the gender data gap, exposing the consequences of ignoring women’s experiences in diverse fields such as healthcare, urban planning, and economics. A thought-provoking call for change in data-driven decision-making.

Safiya U. Noble’s ‘Algorithms of Oppression’ offers a critical analysis of how search engines perpetuate biases and discrimination, and reinforce power structures. A must-read for understanding social impact and embedded racism in technology.

Queer Data discusses the risks of failing to engage with data collection agencies for queer communities, in an age where decisions are increasingly driven by algorithms and big data. But a willingness to be classified, counted, and presented for the analysis of others also poses dangers. In three clear parts, this book first explains the history and theory of queer data and the different types available, then goes on to focus on data analysis and data application.