Bøger i Strong Ideas serien

Why technology is not an end in itself, and how cities can be "smart enough," using technology to promote democracy and equity.

From baby pictures in the cloud to a high school's digital surveillance system: how adults unwittingly compromise children's privacy online.

In an effort to keep up with a world of too much, life hackers sometimes risk going too far.

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.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.

"Argues that what makes AI socially relevant and useful is not intelligence at all but something even more human: communication. If machines are going to improve their ability to address ever more important human issues, it will not be because they have learned to think like people, but because we have learned to communicate with them"--

"The book offers a framework for how to make innovation leaps more likely - and shows how radically improved technology can help solve the major challenges the world currently faces"--