Outstanding Academic Titles 2023: Technology, Data, and Algorithms

Every December, Choice publishes its highly anticipated Outstanding Academic Title award winners. These books go through a battery of evaluations to determine their merit. Below are five award-winning books along with their Choice reviews. These books were especially selected for LibTech Insights readers. Besides great additions to your library collections, they promise to make excellent personal reading this winter. ❄️

1. Algorithms for the people : democracy in the age of AI
Simons, Josh. Princeton, 2023

Cover of Algorithms for the People

While there are technology underpinnings to this book, its real subject is the politics of technology regulation. Increasingly, social and political decisions are made based on algorithms as applied to large data sets. Also increasingly, the algorithms are developed using machine learning, i.e., techniques for discovering patterns in data in order to make predictions. The first half of Algorithms for the People describes a systematic political theory of machine learning in general, and the second half focuses on the technical details in the context of Facebook and Google. Simons is a research fellow at Harvard who was a founding member of Facebook’s Responsible Artificial Intelligence (AI) team. Given the real-world implications of technology-based decision-making and the public’s heightened awareness of the influence of AI in society, this book is an important contribution to the literature. This reviewer’s reading concurs with the dust cover copy: “instead of examining the impact of technology on democracy, [the author] explores how to put democracy at the heart of AI governance.” This book should be in all technology and social science collections.

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2. Geek girls : inequality and opportunity in Silicon Valley
Twine, France Winddance. New York University, 2022

Cover for Geek Girls

Geek Girls is a critical, significant sociological work on structural inequality in technology occupations. Drawing on her extensive ethnographic interviews and framing those experiences within an intersectional lens, Twine (Univ. of California, Santa Barbara) provides a multi-vocal account of the sexism and racism present in Silicon Valley and contributes a seminal book that will advance readers’ understanding of occupational inequality beyond the technology industry. Twine uses her deep ethnographic data from women across the spectrum of gender, racial, and ethnic identities and countries of origin to illustrate nuanced concepts—e.g., the glass wall, bonding capital, geek capital, and first- and second-generation technology workers—that reproduce systemic inequities pertaining to gender and race. The author carefully demonstrates how “myths,” such as leaky pipelines and meritocracy, can obscure the larger systemic inequality at play and how social capital and networks reinforce that same inequality. She also shares insights into ways to address this inequity based on her interviews with women in Silicon Valley. This book is a must-read for anyone interested in systemic inequality in work and occupations.

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3. The magic of technology : the machine as a transformation of slavery
Hornborg, Alf. Routledge, 2022

The philosophy of technology has concentrated the sharpest minds of every epoch, from Karl Marx, Lewis Mumford, and Martin Heidegger to Herbert Marcuse. In this text, Hornborg carved out an innovative path to reconceptualize technology as socioenvironmental metabolism. Hornborg rejects prevalent assumptions about technology being a product of human ingenuity, politically neutral, an autonomous agent, and emancipatory. He focuses on the “physical constitution of technology” and envisions embodied nature transferred from colonies to the metropole. He then casts his critical gaze on the “social constitution of technology” and sees embodied labor and even time and space shifted from economic peripheries to the capitalist core. Hornborg attributes such transfer of nature, labor, and time and space to unequal ecological exchange (i.e., trade) relations. He blames technology fetishization for deflecting attention from its physical and social constitution. He demonstrates that technology continues to be an instrument of enslavement, replacing traditional slavery with wage labor. Surveillance capitalism and Foucauldian disciplinary regimes drive workers to accept servitude as wage laborers. This work, dense in scholarship, grounded in high theory, and rich in empirics, is destined to become a classic. It should be in graduate collections covering environmental anthropology, environmental theory, history, Marxism, engineering, and science and technology studies.

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4. Private is political : networked privacy and social media
Marwick, Alice E. Yale, 2023

Book cover of The Private Is Political

This book aims to shift discussion of privacy and information security from the realm of personal and individual responsibility to the dependence of privacy on social networks and political action. It will enrich every reader’s understanding of privacy and the social conventions that misleadingly treat privacy as each individual’s own responsibility while simultaneously entwining and monetizing their personal information in unavoidable networks. Marwick (Univ. of North Carolina) makes excellent use of feminist and other social analyses in documenting how social networks and conventions incorporate inequitable power relations, which disadvantage and jeopardize many marginalized demographics. The analyses and arguments are well researched, documented, and above all cogently and convincingly presented. This work will be a point of reference for all subsequent scholarly, journalistic, and political discussions of privacy and the dangers inappropriately mined and shared personal information pose. The clear presentation of research also makes it an appropriate introduction to the topics covered. It should be in every library collection.

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5Data science in context : foundations, challenges, opportunities
Alfred Z. Spector et al Cambridge, 2022

Book cover of Data Science in Context

This book has four parts and four notable authors: Spector (visiting scholar, MIT; formerly, Google); Norvig (distinguished education fellow, Stanford Univ.; Google); Wiggins (Columbia Univ.; the New York Times); (Wing, Columbia Univ.). Part 1 argues that although the definition of data science has no consensus, a working definition can be “the study of extracting value from data—value in the form of insight and conclusions” (p. 7). The text explains that data science combines three fields: statistics, operations research, and computing. Part 2 discusses six data science applications, to which an “analysis rubric” consisting of seven considerations for evaluating any application is applied. Three are implementation-oriented elements: tractable data, the technical approach, and dependability. The other four are requirements-oriented: understandability, clear objectives, toleration of failures, and issues of risk and ethics. Part 3 deals with challenges in building data science applications, providing detailed discussion of each of the seven facets of the analysis rubric. Part 4 discusses the need to improve understanding by broadening educational opportunities in data science, especially by using data science and technology in teaching data science. The book concludes with summary recommendations and should be required reading for anyone interested in data science, whether as learner, researcher, or policy maker.

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