The Princeton Dialogues in AI and Work is a research agenda investigating what algorithmic and predictive data-driven tools mean to stakeholders across society. Building on prior work in the Dialogues in AI and Ethics case study series, the current phase of research takes an empirical, sociotechnical focus on how the different communities will interact with, be represented by, and be implicated by, algorithmic technologies in different ways. These studies will be undertaken through the lens of work, where “work” is broadly understood to encompass entrepreneurial organizations, gig labor, and the work of governance. Through this effort, we seek to understand the goals, incentives, and constraints of a broader ecosystem of stakeholders and how these different stakeholder perspectives can be incorporated into novel strategies for designing, building, and governing algorithmic systems which can more equitably serve all.

Elizabeth leads the Dialogues in AI and Work team which also includes CITP members Amy Winecoff and Orestis Papakyriakopoulos. Elizabeth will present brief work-in-progress overviews of three projects currently underway in AI and Labor, AI and Startups, and Explainable AI in City Agencies. This presentation also serves as a call to action. We seek engagement with impacted communities in these spaces and invite interested parties to reach out to the Dialogues team. Please contact Elizabeth Watkins, ew4582@princeton.edu, Amy Winecoff, aw0934@princeton.edu  or Orestis Papakyriakopoulos, orestis@princeton.edu to become involved.

Bio:

Elizabeth Anne Watkins is a postdoctoral research associate at CITP, also affiliated with the Princeton Human-Computer Interaction group (HCI). She studies work and technology, and completed her doctoral degree at Columbia University where she was advised by David Stark. Trained as an organizational sociologist in the field of communications, she uses interviews, analysis of online communities, and surveys to understand how people interpret and strategize around the algorithmic tools they use in their work.

With a special interest in the sociotechnical nexus of AI, usable security, and privacy, her dissertation examined facial recognition in spaces of algorithmic management. She has published or presented at the conferences on Computer-Human Interaction (CHI), Computer-Supported Cooperative Work (CSCW), Algorithmic Fairness, Accountability, and Transparency (FAccT), the security conference USENIX and co-located workshop USENIX FOCI, and the annual meetings of the Academy of Management (AOM) and the Society for the Social Studies of Science (4S). She holds a master’s degree from the Massachusetts Institute of Technology (MIT), and is also a researcher at the Tow Center for Digital Journalism, a member of the Columbia Center on Organizational Innovation, and an affiliate at the Data & Society Research Institute.

To request accommodations for a disability please contact Jean Butcher, butcher@princeton.edu, at least one week prior to the event.

This seminar will not be recorded.