Christine T. Wolf

Christine T. Wolf is a Research Staff Member at IBM Research, Almaden (San Jose, CA). Her research investigates how people make sense of (and transform) emergent technologies through everyday practice. Adapting techniques from PD, her work currently focuses on the incorporation of data analytics into organizational work practices and draws on perspectives from information systems (IS), computer-supportive cooperative work (CSCW), and technology policy. She has co-organized workshops at iConference and the Participatory Design Conference (PDC).

Haiyi Zhu

Haiyi Zhu is an assistant professor in the computer science department at the University of Minnesota, Twin Cities. Her research integrates social science theories, design methods, and machine learning to build better large-scale socio-technical systems. One of her ongoing projects is to propose and validate a new method for developing intelligent algorithms, which she called “Value-Sensitive Algorithm Design”. The method engages relevant stakeholders in the early stages of algorithm creation and incorporates stakeholders’ tacit values, knowledge, and insights into the process of creating an algorithm. She has received Best Paper Honorable Mention in CHI’ 2018, CHI’ 2016, CHI’2013, CSCW’2012, Newell Allen Research Award 2016, Human Factor Prize in 2013, and NSF CRII award 2016. She received a PhD in Human-Computer Interaction from Carnegie Mellon University.

Julia Bullard

Julia Bullard is an assistant professor at the University of British Columbia iSchool (Library, Archival and Information Studies) where she examines how communities instantiate their values in infrastructure, particularly through the design of knowledge organization systems. One of her current concerns is how communities negotiate between automated and conventional methods in creating and maintaining large-scale metadata systems and what methods of participation make community-supported systems trustworthy and legitimate. She holds a PhD in Information Studies from the University of Texas at Austin and an MA in Cultural Studies & Critical Theory from McMaster University.

Min Kyung Lee

Min Kyung Lee is a research scientist in Human-Computer Interaction in the Machine Learning Department at Carnegie Mellon University. Dr. Lee has conducted some of the first studies that empirically examine the social implications of algorithms’ emerging roles in management and governance in society, looking at how people perceive algorithms and how we can design fairer and more trustworthy algorithmic services that work in the real world. Dr. Lee is a Siebel Scholar and has received several best paper and honorable mention awards in venues such as CHI, CSCW, DIS and HRI, as well as an Allen Newell Award for Research Excellence. She is an associate editor of the ACM Transactions on Human-Robot Interaction. Her work has been featured in media outlets such as the New York Times, New Scientist, and CBS. She received a PhD in Human-Computer Interaction and an MDes in Interaction Design from Carnegie Mellon.

Jed R. Brubaker

Jed R. Brubaker is an assistant professor in Information Science at the University of Colorado Boulder where he studies how identity is designed, represented, and experienced in socio-technical systems. His current work focuses on the design of algorithmic interaction design (AIxD) and how to improve the design of social algorithms to better understand for the social nuances of data.  He has co-organized workshops at CHI and ICWSM.

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