Resources for Exploring the Benefits and Drawbacks of AI

February 1, 2024

Like many other law librarians this past year, I am trying to figure out how to teach my students about generative AI. Large language model chatbots like ChatGPT, Bing Chat, Bard, and more offer both new possibilities and new challenges for legal research. Cautionary tales have emerged, but so have potential benefits. Major legal databases are working to incorporate LLMs into their platforms, and our students should be prepared to see them in practice and should understand both the benefits and the drawbacks of these systems.

Every month seems to bring new developments; recently Lexis+ released its AI product to law librarians, faculty, and students while Westlaw released Ask Practical Law AI to academic accounts.

Though generative AI is new, writing about AI more generally is not. I’ve been building a reading list over the past year to better understand, use, and teach AI products in my role as a law librarian and legal research professor. The following is a list of works that I’ve either read or would like to read to help me understand the consequences of artificial intelligence for law and society:

Algorithms of Oppression: How Search Engines Reinforce Racism, Safiya Umoja Noble. New York University Press, 2018.

Noble argues that data discrimination is a real problem and examines how the combination of private interests and the monopoly of a small number of search engines lead to a biased set of algorithms that discriminate against people of color.

Artificial Unintelligence: How Computers Misunderstand the World, Meredith Broussard. MIT Press, 2018.

Broussard explores different aspects of AI, including how it works, examples of when and how it doesn’t work, and argues that we should not assume that technology is always a solution.

The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence, Kate Crawford. Yale University Press, 2021.

Crawford argues that AI is a technology of extraction, and that the structures that allow for the creation of AI are fueling a shift towards inequity.

Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor, Virginia Eubanks. St. Martin’s Press, 2018.

Eubanks explores the effects of algorithms and other technological tools on the poor and working class in the United States.

Computer Power and Human Reason: From Judgment to Calculation, Joseph Weizenbaum. Penguin, 1976.

Though originally published in 1976, Weizenbaum’s examination of computer intelligence remains relevant. Weizenbaum created the first chatbot in 1966, and this work reflects on its interactions with humans, connecting this early experiment with larger concerns about technology’s impact on society.

Data Cartels: The Companies That Control and Monopolize Our Information, Sarah Lamdan. Stanford University Press, 2023.

Lamdan examines the small number of companies that control, mine, analyze, and commodify most of our legal information, arguing that they perpetuate social inequality and should be better regulated by treating information as a public good.

The Eye of the Master: A Social History of Artificial Intelligence, Matteo Pasquinelli. Verso Books, 2023.

In a long ranging work covering the history of artificial intelligence, Pasquinelli examines the role of labor in the development of AI, suggesting that it is a key way of understanding the development and future of artificial intelligence systems.

The Hank Show, McKenzie Funk. MacMillan, 2023.

Funk explores the life of Hank Asher, a computer programmer who pioneered the creation of data brokerage, where major databases pull together information from different sources and fuel today’s surveillance state.

New Dark Age: Technology and the End of the Future, James Bridle. Verso Books, 2019.

Bridle contests the idea that more and better data can help us understand the world around us, and instead demonstrates how technological complexity actually makes our world less transparent.

Programmed Inequality: How Britain Discarded Women Technologists and Lost Its Edge in Computing, Mar Hicks. MIT Press, 2017.

Hicks tells the story of the British computing industry in the second half of the twentieth century, beginning when it was on the cutting edge and ending with its virtual extinction. One of the major reasons for this loss was the neglect and marginalization of women in the field, and Hicks shows how clinging to a myth of meritocracy in tech has consequences for economic and technological development.

Race After Technology: Abolitionist Tools for the New Jim Code, Ruha Benjamin. Polity, 2019.

Benjamin demonstrates how numerous technologies, including algorithms, work to reify and amplify discrimination and racial hierarchies.

Unmasking AI: My Mission to Protect What is Human in a World of Machines, Joy Buolamwini. Penguin Random House, 2023.

Buolamwini is the founder of the Algorithmic Justice League and a major figure in the fight to regulate AI. In this book, she explores her journey through robotics and computer science and the fight against the racial and gender biases encoded in our technological systems.

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Cathy O’Neil. Broadway Books, 2017.

 O’Neil explores the many ways that algorithms are used in modern society and their effects, in particular the ways in which they reinforce discrimination and undermine democracy.

Your Computer is On Fire, ed. Thomas Mullaney, Benjamin Peters, Mar Hicks, and Kavita Phillips. MIT Press, 2021.

This collection of essays explores several key myths about computing: it argues that nothing is truly virtual and all aspects of computing have both a material reality and material consequences, that computers are perpetuating inequality in a variety of ways, and that these inequities are only increasing in effect.