Five Upcoming Academic Books on Data Work, Big Tech, and Misinformation

Our most hotly anticipated books for fall!

Posted on September 2, 2026 in Blog Posts

I’ve recently become aware of the concept of “autumn creep,” the encroachment of fall aesthetics and foods into summer months. Coffee shops debut their pumpkin spice lines in August, and retail stores integrate cozy wear into their collections as early as July. But with the turning of the calendar over to September, it feels close enough to the start of autumn to run my fall/winter picks for upcoming academic titles I’m most excited for this year. I’ve combed through thousands of catalog pages to select only the most promising. 

Let’s get started! 

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Platform Extractivism: Data Work and the People Powering Artificial Intelligence, by Julián Posasa (California)  

Among the litany of critiques of social media and AI is the reliance of tech companies on highly exploited labor in the Global South. Data workers sift through graphic images and posts to train algorithms and moderate content. While exposés of these workers and their truly traumatizing circumstances sometimes appear in the headlines, they seldom receive book-length treatment. Julián Posada, an American studies professor at Yale, combines research into the Venezuelan data work sector with broader theoretical arguments about platform technologies to reveal the human costs of these technologies. 

The “invisibility” of this labor has made it difficult to advance the decolonial critiques scholars and activists have sought to mount against these technologies. Posada’s work making data work visible will hopefully add heft to this important and necessary critique. 

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Thoughtful Data: A Guide to Empathy and Equity in Data Communication, by Jonathan Schwabish and Alice Feng (Columbia) 

From what I observed across several publishers, data science is a hot field of interest, but Thoughtful Data, written by two data visualization specialists, stood out as a notable volume for librarians. Beginning with the premise that data are never neutral, this volume takes seriously the possibility of using data to advance equity and critical thinking. Its focus on data visualization as a means of data communication makes this book deeply relevant. Data visualizations are ubiquitous on social media, making data “speak for themselves,” and we need to learn how to ask hard questions of simple charts. 

Particularly for librarians who teach information literacy, this book seems like a useful guide for engaging with students as information consumers and creators. 

What Tech Calls Governing, by Adrian Daub (Stanford) 

Elon Musk’s integration into the early Trump II administration crystallized the tech sector’s ongoing move into government. Although Musk may have departed from his position at DOGE, the tech sector’s role in politics and government is likely to receive continued scrutiny during the midterm elections in November and beyond. In this short work, Daub, a humanities professor at Stanford, follows up on his earlier work, What Tech Calls Thinking (2020), to investigate how the tech elite conceives of power. 

Although Daub appears to take a granular approach to this topic—the summary mentions his analysis of billboards and YouTube channels—he offers something much bigger: the political philosophy of Big Tech.

Fear of Data: How Privacy Panic Led Tech Regulation Astray—and How to Fix It, by Omri Ben-Shahar (Harvard) 

Perhaps due to lingering millennial hipsterdom, I admit I like a good contrarian take. Ben-Shahar, a professor at the University of Chicago Law School, argues that the ideal of digital privacy fails to take on the actual problems of digital life and prevents us from implementing solutions and advances that data could make possible, for instance, identifying dangerous drivers to prevent fatal car crashes. Our ideal of privacy leads us to lump together the good and the bad in an unproductive way. Then again, his suggestion that facial recognition software can help rescue victims of sex trafficking also has to be weighed against the stories of police officers using Flock surveillance cameras to stalk their exes, complicating whether the good can truly be separated from the bad. 

While it isn’t exactly a shocker that a professor at the University of Chicago would argue for deregulation, Ben-Shahar’s book promises to create complexity in an important issue, forcing us to consider the trade-offs of privacy and the lines we want to draw.

Enjoyment Is Breaking News: How We Became Less Informed and More Divided (and How to Fix It), by Jennifer Hoewe (MIT) 

Traditional liberal notions about the relationship between the news and politics no longer seem adequate. People watch hours-long livestreams of influencers riffing on the headlines while playing video games, and some news consumers even write fan fiction about the hosts of political podcasts. In this book, Hoewe, a professor of communication at Purdue, argues that the news isn’t simply a means of becoming informed, but increasingly comes with the expectation of being entertaining as well. This entertainment bias has big ramifications for how people select their news sources and value what they encounter. 

Especially relevant to those interested in misinformation, Hoewe’s book investigates the motivations of both news consumers and the incentives of the digital platforms delivering the news, offering insight into the broader media ecosystem in which information travels and warps. 

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