Run a Google search for “black girls” - what will you find? “Big Booty” and other sexually explicit terms are likely to come up as top search terms. But, if you type in “white girls”, the results are radically different. The suggested porn sites and un-moderated discussions about “why black women are so sassy” or “why black women are so angry” presents a disturbing portrait of black womanhood in modern society. In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities.

The Age of Surveillance Capitalism is neither a hand-wringing narrative of danger and decline nor a digital fairy tale. Rather, it offers a deeply reasoned and evocative examination of the contests over the next chapter of capitalism that will decide the meaning of information civilization in the 21st century. The stark issue at hand is whether we will be the masters of information and machines or its slaves.

What happens when artificial intelligence saturates political life and depletes the planet? How is AI shaping our understanding of ourselves and our societies? Drawing on more than a decade of research, award-winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression. This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity.

When Michael Lewis first met him, Sam Bankman-Fried was the world’s youngest billionaire and crypto’s Gatsby. CEOs, celebrities, and leaders of small countries all vied for his time and cash after he catapulted, practically overnight, onto the Forbes billionaire list. Who was this rumpled guy in cargo shorts and limp white socks, whose eyes twitched across Zoom meetings as he played video games on the side?

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we can get a job or a loan, how much we pay for health insurance—are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.

From everyday apps to complex algorithms, Ruha Benjamin cuts through tech-industry hype to understand how emerging technologies can reinforce white supremacy and deepen social inequity. Benjamin argues that automation, far from being a sinister story of racist programmers scheming on the dark web, has the potential to hide, speed up, and deepen discrimination while appearing neutral and even benevolent when compared to the racism of a previous era.

A bold call to reexamine how our government operates—and sometimes fails to—from President Obama’s former deputy chief technology officer and the founder of Code for America.

In 2021 cryptocurrency went mainstream. Giant investment funds were buying it, celebrities like Tom Brady endorsed it, and TV ads hailed it as the future of money. Hardly anyone knew how it worked—but why bother with the particulars when everyone was making a fortune from Dogecoin, Shiba Inu, or some other bizarrely named “digital asset”? As he observed this frenzy, investigative reporter Zeke Faux had a nagging question: Was it all just a confidence game of epic proportions? What started as curiosity—with a dash of FOMO—would morph into a two-year globe-spanning quest.

To most of us, it seems like recent developments in artificial intelligence emerged out of nowhere to pose unprecedented threats to humankind. But to Dr. Joy Buolamwini, who has been at the forefront of AI research, this moment has been a long time in the making.

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."

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

Does your job make a meaningful contribution to the world? In the spring of 2013, David Graeber asked this question in a playful, provocative essay titled “On the Phenomenon of Bullshit Jobs”. It went viral. After a million online views in 17 different languages, people all over the world are still debating the answer.

You may be surprised to learn that microchips are the new oil—the scarce resource on which the modern world depends. Today, military, economic, and geopolitical power are built on a foundation of computer chips. Virtually everything—from missiles to microwaves—runs on chips, including cars, smartphones, the stock market, even the electric grid. Until recently, America designed and built the fastest chips and maintained its lead as the #1 superpower, but America’s edge is in danger of slipping, undermined by players in Taiwan, Korea, and Europe taking over manufacturing.

In PALO ALTO, the first comprehensive, global history of Silicon Valley, Malcolm Harris examines how and why Northern California evolved in the particular, consequential way it did, tracing the ideologies, technologies, and policies that have been engineered there over the course of 150 years of Anglo settler colonialism, from IQ tests to the "tragedy of the commons," racial genetics, and "broken windows" theory.

Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week's meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts' predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight.