Hosted by Eleanor Drage and Kerry Mackereth, The Good Robot is a podcast which explores the many complex intersections between gender, feminism and technology. In this episode we talk to Meredith Broussard, data journalism professor at the Arthur L. Carter Institute at New York University. She's also the author of Artificial Unintelligence, which made waves following its release in 2018 by claiming that AI was nothing more than really fancy math. We talk about why we need to bring a little bit more friction back into technology and her latest book More Than a Glitch, which argues that AI that's not designed to be accessible is bad for everyone, in the same way that raised curbs between the pavement and the street that you have to go down to cross the road makes urban outings difficult for lots of people, not just wheelchair users. Data journalist Meredith Broussard is an associate professor at the Arthur L. Carter Journalism Institute of New York University, research director at the NYU Alliance for Public Interest Technology, and the author of several books, including More Than a Glitch: Confronting Race, Gender, and Ability Bias in Tech and Artificial Unintelligence: How Computers Misunderstand the World.

Long before the technology even existed in the real world, the concept of artificial intelligence has long been a topic of fixation for writers. From cautionary tales and science fiction epics to nonfictional explorations of the implications of AI in our modern world, artificial intelligence seems to be an endlessly fascinating subject of books both big and small. As such, there are all kinds of truly exceptional books about artificial intelligence out there for you to read, enjoy, and maybe even learn a thing or two from. As to be expected, these books about artificial intelligence truly run the gamut. Beyond simply falling under both fiction and nonfiction, artificial intelligence books cover topics ranging from the future to the past, from work to society, from computing to critiques… and all sorts of other topics along the way.

One of the more startling and instructive documentaries of the recent past is 2020's Coded Bias, which explores a thorny dilemma: in modern society, artificial-intelligence systems increasingly govern and surveil people's lives--algorithms now routinely make decisions about health care, housing, insurance, education, employment, banking, and policing--yet racial and gender biases are deeply embedded in many of these AI systems (for more background, read "Artificial Intelligence and Ethics," January-February 2019, page 44). The film, which premiered at Sundance and is now streaming on Netflix, begins with MIT Media Lab researcher and MIT doctoral candidate Joy Buolamwini recounting an experience from her first semester there in 2015: working on an art project that used AI facial-recognition software, she was confused at first when the computer didn't seem to register her face. During a striking moment early in the documentary, Buolamwini, who is African American, demonstrates the problem: holding a white mask over her own face, she turns toward her computer, which trills and lights up in response; when she lowers the mask, the computer sits eerily silent. The documentary presents a damning portrait of AI's flaws and the efforts under way to improve them, weaving together research and interviews of those who study the field, including several with Harvard connections: Berkman Klein faculty associate Zeynep Tufekci, former Nieman visiting fellow Amy Webb, data scientist Cathy O'Neil, Ph.D. '99, author of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016). Buolamwini herself is a former Adams House tutor (and performed her spoken-word poem, "AI, Ain't I A Woman?" at a Harvard conference in 2019).

In Artificial Unintelligence: How Computers Misunderstand the World, Meredith Broussard adds to the growing literature exploring the limits of artificial intelligence (AI) and techno-solutionism, furthermore showing how its socially-constructed nature replicates existing structural inequalities. Calling for greater racial and gender diversity in tech, the book offers a timely, accessible and often entertaining account that sets the record straight on what current approaches to AI are and are not capable of delivering, writes Nikita Aggarwal. This post originally appeared on LSE Review of Books. If you would like to contribute to the series, please contact the managing editor of LSE Review of Books, Dr Rosemary Deller, at lsereviewofbooks@lse.ac.uk. You don't need to speak Italian to know that something's not quite right.

Computers may one day be able to reason exactly as humans do, but will they ever be as dumb? I had always thought that was impossible. The other day, I was in Penn Station on my way home from work. A team of scientists had set up a table with a laptop running the latest pattern-recognition software, and they were asking passersby to suggest questions for the computer. With twenty minutes on my hands, I asked it to find the best place for me to sit while waiting for my train.