smart & responsible communities & cities

We explore how emerging intelligent technologies can support more equitable progress in society.

Research Overview

We are building fundamental understandings of how people perceive algorithms and developing systems that allow people and algorithms together to make better decisions than either one could achieve alone. Drawing from our research, we work with communities to design services that promote fair, equitable progress and civic engagement.

Our projects below demonstrate what we are currently excited about.

Socius: Improving Community Services

How can we improve service delivery for the homeless population by learning and modeling their location-based needs? [Learn more]

Fair algorithms: Donation Allocation

How can we design a fair allocation algorithm for food donation? [Learn more]

Perceptions of algorithms

How do people perceive algorithmic decisions as compared to human decisions? [Learn more]


If you are interested in joining us drop us a line

Min Kyung Lee

Research Scientist

Ji Tae Kim


Anuraag Jain

HCI & Computer Science

Previous Members

These are students who worked with us over a year.

Su Baykal

Psychology & HCI

Eunsol Byun

Design & HCI

Nathaniel Fruchter

Decision Science

Vincent Kang

Computer Science

Daniel Kusbit

Ethics, History and Public Policy

Evan Metsky

Cognitive Psychology & HCI

Lisa Otto


Dylan Steele

Physics & Computer Science


Tsai, H., Shoukry, Y., Lee, M. K., and Raman, V. (2017). Towards a Socially Responsible Smart City: Dynamic Resource Allocation for Smarter Community Service. To appear in BuildSys 2017.

Lee, M. K., Kim, J. & Lizarondo, L. (2017). A human-centered approach to algorithmic services: Considerations for fair and motivating smart community service management that allocates donations to non-profit organizations. In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2017), 3365-3376.

Lee, M. K. and Baykal, S. (2017). Algorithmic mediation in group decisions: Fairness perceptions of algorithmically mediated vs. discussion-based social division. In Proceedings of the ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW 2017), 1035-1048. Best Paper Honorable Mention

Lee, M. K. (2017). Algorithmic bosses, robotic colleagues: Toward human-centered algorithmic workplaces. In XRDS: Crossroads, The ACM Magazine for Students, 23(2), 42-47.

Lee, M. K., Kusbit, D., Metsky, E. and Dabbish, L. (2015). Working with machines: The impact of algorithmic, data-driven management on human workers. In Proceedings of the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2015), 1603-1612 [PDF]

Make an Impact

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Sponsors & Partners

Here are our sponsors and partners.