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AI Through the Experts’ Eyes: Communicating Complex Ideas (Composition, Literacy, and Culture) - Softcover

Book 81 of 87: Composition, Literacy, and Culture

Gallagher, John R.

 
9780822968047: AI Through the Experts’ Eyes: Communicating Complex Ideas (Composition, Literacy, and Culture)

Synopsis

AI Through the Experts’ Eyes reveals the humanity behind artificial intelligence. John R. Gallagher foregrounds practitioners’ stories and the real-life culture from which these disruptive technologies emerge. Representing reality to computers is at the heart of AI, and Gallagher spotlights the challenges of doing so under the combined pressures of the break-neck pace of these technologies’ growth and ever-present hype, both external and internal. Drawing on more than 100 interviews with AI scientists and practitioners, the author showcases the ways AI researchers face these challenges through writing and communicating their findings, including how they define terms, work in teams, share their research, and approach ethics.

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About the Author

John R. Gallagher is professor of English at the University of Illinois, Urbana-Champaign, where he also is a faculty affiliate at the School of Information Sciences. He is the author of Case Study Research in the Digital Age and Update Culture and the Afterlife of Digital Writing. He fuses qualitative inquiry with natural language processing and machine learning to study social media.

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From the Introduction

It’s a quiet Monday morning in January at the University of Illinois Urbana-Champaign (UIUC). I arrive a bit early for the weekly re-search group meeting, sliding a few broken chairs off to the side. The room features a rectangular table with a projector on top and a wall-mounted screen. There are several windows letting in the winter sun. It warms the utilitarian room. Fifteen undergraduate and graduate students quietly trickle into the room. Everyone sheds their winter coats. The two women sit on opposite sides of the table. This morning, two graduate students will present their results to this small but engaged research group studying computer vision, a subfield in artificial intelligence (AI).
The primary purpose of this meeting is to refine the students’ re-search while soliciting suggestions for future experiments. In computer vision, goals include automatically detecting images of people, road signs, or objects. During the first presentation, which is a computer vision model involving the accuracy rates of an image-object detector, the student spends four minutes explaining one equation: identifying each variable along with its significance, all while sharing how the results compare to other research in the field.
Everyone in the room listens intently. Such discussions of the math are frequently met with fear or boredom by much of the public. As a result, math can be perceived to have almost magical properties when applied to such complex systems. There is no obfuscation in the presentation or follow-up questions. Everyone is open about the math. Direct and honest, there is no hint of AI hype.

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