Who I Am
I am currently a Postdoctoral Researcher at Microsoft Research, NYC, working with the FATE (Fairness, Accountability, Transparency, and Ethics in AI) research group. I recently completed my PhD at the Human-Computer Interaction Institute at Carnegie Mellon University, where I was a Siebel Scholar and a fellow in the PIER Program in Interdisciplinary Education Research. Before coming to CMU, I completed an M.S. in the Digital Media program at Georgia Tech and was a teacher at a public high school in Maryland.
What I Do
My research focuses on human-centered approaches to fairness and equity issues in AI, including how AI practitioners and other stakeholders operationalize principles for responsible AI; the tools and practices that support this fairness work in practice; and the social and organizational dynamics that impact those efforts, including approaches for designing AI/ML and NLP systems with participation from affected stakeholders.
I am particularly interested in how these approaches take shape in applications in educational AI systems and in public sector AI/ML systems more generally, including the implications for equity (beyond the more limited frame of "fairness") and uncovering and balancing the values tensions and power dynamics among multiple stakeholders involved in such systems.
|February 2021||Our proposed workshop on the intersection of Human-Computer Interaction and Natural Language Processing was accepted, co-located at the EACL conference in April 2021 (co-organizing with Su Lin Blodgett, Brendan O'Connor, Hanna Wallach, and Qian Yang.|
|October 2020||Presented a paper at the CSCW 2020 Ethics in Design Workshop on using checklist items to prompt conversations about fairness in AI within cross-functional industry teams.|
|August 2020||Started a postdoctoral research position at Microsoft Research in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) research group!|
|April 2020||Published 2 papers at the CHI 2020 Workshop on Fair and Responsible AI: a paper on processes for engaging impacted communities in participating in AI research, and a paper on the need for organizational priorities to support AI fairness efforts in industry practice.|
|July 2020||I defended my dissertation! Huge thanks to my wonderful committee!|
|March 2020||We won a Best Paper Award at CHI 2020 for our paper on co-designing AI fairness checklists with AI practitioners, in collaboration with Luke Stark, Jenn Wortman Vaughan, and Hanna Wallach at Microsoft Research!|
Madaio, M., Stark, L., Wortman Vaughan, J., Wallach, H. (2020). Prompting Conversations about Fairness in AI Design with Checklists. Presented at the Ethics in Design Workshop at the 2020 CSCW Conference on Computer Supported Cooperative Work and Social Computing. [pdf]
Madaio, M., Stark, L., Wortman Vaughan, J., Wallach, H. (2020). Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI. In the Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-14). [pdf]
Best Paper Award
Madaio, M., Stark, L., Wortman Vaughan, J., Wallach, H. (2020). The Need for Top-Level Performance Indicators to Support Fairness in AI. Presented at the Workshop on Fair and Responsible AI at the 2020 CHI Conference on Human Factors in Computing Systems. [pdf]
Black, E., Williams, J., Madaio, M., Donti, P.L. (2020). A Call for Universities to Develop Requirements for Community Engagement in AI Research. Presented at the Workshop on Fair and Responsible AI at the 2020 CHI Conference on Human Factors in Computing Systems. [pdf]
Madaio, M., Yarzebinski, E., Kamath, V., Akpe, H., Blahoua Seri, A., Tanoh, F., Jasinska, K. & Ogan, A. (2020). Collective Support and Independent Learning with a Voice-Based Literacy Technology in Rural Communities. In the Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-14). [pdf]
Chatterjee, R., Madaio, M., Ogan, A. (2020). Predicting Gaps in Usage in a Phone-Based Literacy Intervention System. In the Proceedings of the In International Conference on Artificial Intelligence in Education (pp. 92-105). Springer, Cham. [pdf]
Best Student Paper Award
Mayfield, E., Madaio, M., Prabhumoye, S., Gerritsen, D., McLaughlin, B., Dixon-Roman, E., Black, E. (2019). Equity Beyond Bias in Language Technologies for Education. In 14th Workshop on Innovative Use of NLP for Building Educational Applications, at ACL 2019. [pdf]
Madaio, M., Martin, S.E. (2019). Who owns the Smart City? Towards an Ethical Framework for Civic AI. In Scherling, Laura, and Andrew DeRosa, eds. Ethics in Design and Communication: Critical Perspectives. Bloomsbury Publishing, 2020. [book] [pre-print of the chapter available on request].
Madaio, M., Kamath, V., Yarzebinski, E., Zasacky, S., Tanoh, F., Hannon-Cropp, J., Cassell, J., Jasinska, K. & Ogan, A. (2019). "You Give a Little of Yourself": Family Support for Children’s Use of an IVR Literacy System. In the Proceedings of the 2019 ACM SIGCAS Conference on Computing and Sustainable Societies (ACM COMPASS). [pdf]
Best Paper Award
Madaio, M., Tanoh, F., Blahoua Seri, A., Jasinska, K. & Ogan, A. (2019). "Everyone Brings Their Grain of Salt": Designing for Low-Literate Parental Engagement with a Mobile Literacy Technology in Côte d'Ivoire. Accepted to the 2019 ACM CHI Conference on Human Factors in Computing Systems (CHI). [pdf]
Lee, J., Lin, Y., and Madaio, M. (2018). A Longitudinal Evaluation of a Deployed Fire Risk Model. In the AI for Social Good Workshop at the Neural Information Processing System Conference. (NeurIPS 2018). [pdf]
Singh Walia, B., Hu, Q., Chen, J., Chen, F., Lee, J., Kuo, N., Narang, P., Batts, J., Arnold, G., and Madaio, M. (2018). A dynamic pipeline for spatio-temporal fire risk prediction. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. (KDD). [pdf]
Uchidiuno, J., Yarzebinski, E., Madaio, M., Maheshwari., N., Koedinger, K., & Ogan, A. (2018). Designing Appropriate Learning Technologies for School vs Home Settings in Tanzanian Rural Villages. In the Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable Societies (ACM COMPASS). [pdf]
Madaio, M., Peng, K., Ogan, A., & Cassell, J. (2018). A climate of support: a process-oriented analysis of the impact of rapport on peer tutoring. In Proceedings of the 12th International Conference of the Learning Sciences (ICLS) , 2017. [pdf] Best Paper Award; Best Student Paper Nominee
Madaio, M., Chen, S.T, Haimson, O.L., Zhang, W., Cheng, X., Hinds-Aldrich, M., Chau, D.H., and Dilkina, B. (2016). Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM. 2016, pp. 185–194. [pdf] Best Student Paper, Runner-Up
Madaio, M., Grinter, R. E., & Zegura, E. W. (2016, June). Experiences with MOOCs in a West-African Technology Hub. In Proceedings of the Eighth International Conference on Information and Communication Technologies and Development (p. 49). ACM. [pdf]