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New Books in Language

Jennifer Petersen, "How Machines Came to Speak: Media Technologies and Freedom of Speech" (Duke UP, 2022)

Apr 14, 2022
43:50

In How Machines Came to Speak: Media Technologies and Freedom of Speech (Duke University Press, 2022), Jennifer Petersen constructs a genealogy of how legal conceptions of “speech” have transformed over the last century in response to new media technologies. Drawing on media and legal history, Petersen shows that the legal category of speech has varied considerably, evolving from a narrow category of oratory and print publication to a broad, abstract conception encompassing expressive nonverbal actions, algorithms, and data. She examines a series of pivotal US court cases in which new media technologies—such as phonographs, radio, film, and computer code—were integral to this shift. In judicial decisions ranging from the determination that silent films were not a form of speech to the expansion of speech rights to include algorithmic outputs, courts understood speech as mediated through technology. Speech thus became disarticulated from individual speakers. By outlining how legal definitions of speech are indelibly dependent on technology, Petersen demonstrates that future innovations such as artificial intelligence will continue to restructure speech law in ways that threaten to protect corporate and institutional forms of speech over the rights and interests of citizens.

Jennifer Petersen is an Associate Professor of Communication at the Annenberg School for Communication and Journalism at the University of Southern California. She is the director of the graduate certificate program in Science and Technology Studies and is affiliated with the Center for Law, History, and Culture. Before arriving at USC, she worked at the University of Virginia, where she was an affiliate with the Department of Women, Gender, and Sexuality. She is also a former Lenore Annenberg and Wallis Annenberg Fellow in Communication at the Center for Advanced Studies in the Behavioral Sciences (CASBS) at Stanford University.

Austin Clyde is a Ph.D. candidate at the University of Chicago Department of Computer Science. He researches artificial intelligence and high-performance computing for developing new scientific methods. He is also a visiting research fellow at the Harvard Kennedy School's Science, Technology, and Society program.

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