"Histories and Futures of AI in the Workplace"

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While today’s conversations about how “big data” and “intelligent algorithms” are transforming the workplace can feel novel, these hopes and fears have deeper roots than we often acknowledge. By exploring the long history of AI and automation in professional settings, we can uncover lessons from the past that can guide our decisions about the future. This session will shine a light on the often-overlooked labor and expertise embedded in our technological systems, offering a richer understanding of the cultural and historical forces shaping the “AI moment” we find ourselves in today.

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Through this session, you'll:​​

1. Develop a nuanced view of how today’s technological systems build upon and reflect past innovations and challenges.

2. Recognize the hidden work and human expertise behind seemingly seamless information technologies.

3. Place current predictions about AI in the workplace within the broader sweep of past technological visions to inform more grounded and responsible action.

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Speaker Bio:

Greg Downey is an Evjue-Bascom Professor at the University of Wisconsin—Madison, in both the Information School (serving as Director from Fall 2025-present) and the School of Journalism and Mass Communication (serving as Director from 2009-2014).  He also served for a decade (2014-2024) as Associate Dean for Social Sciences in the College of Letters and Science, stewarding two dozen departments and units — including some of the largest majors at UW-Madison — comprising a budget of roughly $40 million and supporting more than 250 faculty and 725 staff. Professor Downey’s research uses historical and geographical methods to uncover and analyze “information labor” over time and space. He is the author of Telegraph Messenger Boys: Labor, Technology, and Geography 1850-1950 (2002), Closed Captioning: Subtitling, Stenography, and the Digital Convergence of Text with Television (2008), and Technology and Communication in American History (2011). Downey’s recent scholarship focuses on interdisciplinarity in academic knowledge production, the “metadata labor” of library and information science professionals, and the historical intertwining of algorithmic technology with career advising and job placement.