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
I work at the intersection of human-computer interaction, AI/ML, and public interest technology, where I use human-centered methods to understand how we might co-design more equitable data-driven technologies with stakeholders.
My current work focuses on understanding the organizational dynamics of how AI/ML teams work towards fairness and equity in their products and services, and what types of methods, tools, and organizational processes might best support them in doing so.
Relatedly, another strand of my work focuses on how methods from participatory and speculative design might enable AI/ML (and, more broadly, algorithmic) systems in the public sector to be co-designed with community members to support more equitable outcomes in civic decision-making and public education.
|May 2020||I'm excited to announce that I'll be starting a postdoctoral research position at Microsoft Research with the amazing people at the FATE (Fairness, Accountability, Transparency, and Ethics in AI) research group!|
|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 Hanna Wallach, Jenn Wortman Vaughan, and Luke Stark at Microsoft Research!|
|December 2019||Very proud to have had two papers accepted to the CHI 2020 conference! Grateful for amazing co-authors at Microsoft Research (paper here) and our Allô Alphabet literacy project (paper here)!|
|July 2019||We won the best paper award at the ACM Compass conference for our paper looking at how rural families use a voice-based literacy technology!|
|June 2019||Our paper outlining a research agenda for ethics and equity in NLP systems in education was presented at the ACL Workshop on Innovative Use of NLP for Building Educational Applications.|
|December 2018||Our team presented our short paper on a longitudinal evaluation of our deployed fire risk model at the AI for Social Good workshop at the NeurIPS conference in Montreal!|
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 (pp. 1-14). [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 (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
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]
Madaio, M., Martin, S.E. (2018). 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]
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]
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]