Data Feminism For Ai
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Data Feminism
Cutting edge strategies for thinking about data science and data ethics through an intersectional feminist lens. “Without ever finger-wagging, Data Feminism reveals inequities and offers a way out of a broken system in which the numbers are allowed to lie.”—WIRED Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism 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. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.
Artificial Knowing
Artificial Knowing challenges the masculine slant in the Artificial Intelligence (AI) view of the world. Alison Adam admirably fills the large gap in science and technology studies by showing us that gender bias is inscribed in AI-based computer systems. Her treatment of feminist epistemology, focusing on the ideas of the knowing subject, the nature of knowledge, rationality and language, are bound to make a significant and powerful contribution to AI studies. Drawing from theories by Donna Haraway and Sherry Turkle, and using tools of feminist epistemology, Adam provides a sustained critique of AI which interestingly re-enforces many of the traditional criticisms of the AI project. Artificial Knowing is an esential read for those interested in gender studies, science and technology studies, and philosophical debates in AI.
Invisible Women
Author: Caroline Criado Perez
language: en
Publisher: Random House
Release Date: 2019-03-07
*THE SUNDAY TIMES NUMBER ONE BESTSELLER* *OVER A MILLION COPIES SOLD* Discover the shocking gender bias that affects our everyday lives in this groundbreaking gift of a book. 'Nothing delights me more than a well-written and well-researched book that teaches you and never bores you' Chimamanda Ngozi Adichie 'HELL YES. This is one of those books that has the potential to change things - a monumental piece of research' Caitlin Moran Imagine a world where... · Your phone is too big for your hand · Your doctor prescribes a drug that is wrong for your body · In a car accident you are 47% more likely to be injured. If any of that sounds familiar, chances are you're a woman. From government policy and medical research, to technology, workplaces, and the media. Invisible Women reveals how in a world built for and by men we are systematically ignoring half of the population, often with disastrous consequences. Caroline Criado Perez brings together for the first time an impressive range of case studies, stories and new research from across the world that illustrate the hidden ways in which women are forgotten, and the profound impact this has on us all. Find out more in Caroline's new podcast, Visible Women. 'A book that changes the way you see the world' Sunday Times 'Revelatory, frightening, hopeful' Jeanette Winterson