Research Publications
Cotter, K., & Reisdorf, B. (2020). Algorithmic Knowledge Gaps: A New Dimension of (Digital) Inequality. International Journal of Communication, 14, 745–765.
Cotter, K., DeCook, J. R., & Kanthawala, S. (2022). Fact-Checking the Crisis: COVID-19, Infodemics, and the Platformization of Truth. Social Media+ Society, 8(1), 20563051211069050.
Gupta, A., Badr, Y., Negahban, A., & Qiu, R. G. (2021). Energy-efficient heating control for smart buildings with deep reinforcement learning. Journal of Building Engineering, 34, 101739.
Hsu, Y. C., Huang, T. H. K., Hu, T. Y., Dille, P., Prendi, S., Hoffman, R., ... & Nourbakhsh, I. (2021, May). Project RISE: recognizing industrial smoke emissions. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 17, pp. 14813-14821).
Li, Z. S., Li, Y.-F., Qiu, R. G., & Zio, E. (2022). Guest Editorial: Special Section on AI Enhanced Reliability Assessment and Predictive Health Management. IEEE Transactions on Industrial Informatics, 18(10), 7196–7197.
Masrur, A., Yu, M., Mitra, P., Peuquet, D., & Taylor, A. (2022). Interpretable machine learning for analysing heterogeneous drivers of geographic events in space-time. International Journal of Geographical Information Science, 36(4), 692-719.
Passonneau, R. J., McNamara, D., Muresan, S., & Perin, D. (2017). Preface: Special Issue on Multidisciplinary Approaches to AI and Education for Reading and Writing. International Journal of Artificial Intelligence in Education, 27(4), 665–670.
Shu, K., Sliva, A., Wang, S., Tang, J., & Liu, H. (2017). Fake News Detection on Social Media: A Data Mining Perspective. ACM SIGKDD Explorations Newsletter, 19(1), 22–36.
Singh, P., Gnesdilow, D., Cang, X., Baker, S., Goss, W., Kim, C., Passonneau, R. J., & Puntambekar, S. (2022). Design of Real-time Scaffolding of Middle School Science Writing Using Automated Techniques. International Society for the Learning Sciences Conference.
Peddinti, V., & Qiu, R. (2022). A Machine Learning Approach to Understanding the Progression of Alzheimer’s Disease. In H. Yang, R. Qiu, & W. Chen (Eds.), AI and Analytics for Public Health (pp. 381–392). Springer International Publishing.
Wang, J., Yang, H., Shao, R., Abdullah, S., & Sundar, S. S. (2020). Alexa as coach: Leveraging smart speakers to build social agents that reduce public speaking anxiety. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ‘20), Paper 434.
Wilder, B., Onasch-Vera, L., Diguiseppi, G., Petering, R., Hill, C., Yadav, A., Rice, E., & Tambe, M. (2021). Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 14948–14956.
Xie, J., & Wang, Q. (2020). Benchmarking Machine Learning Algorithms on Blood Glucose Prediction for Type I Diabetes in Comparison With Classical Time-Series Models. IEEE Transactions on Biomedical Engineering, 67(11), 3101–3124.
Xie, J., & Wang, Q. (2019). A personalized diet and exercise recommender system for type 1 diabetes self-management: An in silico study. Smart Health, 13, 100069.
Yang, H., Qiu, R. G., & Chen, W. (2022). AI and Analytics for Public Health: Proceedings of the 2020 INFORMS International Conference on Service Science. Springer Nature.
You, Y., Kou, Y., Ding, X., & Gui, X. (2021). The Medical Authority of AI: A Study of AI-enabled Consumer-Facing Health Technology. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-16).
Graham, S. S., & Hopkins, H. R. (2022). AI for Social Justice: New Methodological Horizons in Technical Communication. Technical Communication Quarterly, 31(1), 89–102.
Vecchione, B., Levy, K., & Barocas, S. (2021). Algorithmic Auditing and Social Justice: Lessons from the History of Audit Studies. Equity and Access in Algorithms, Mechanisms, and Optimization, 1–9.
Margetts, H. (2022). Rethinking AI for Good Governance. Daedalus, 151(2), 360–371.
Züger, T., & Asghari, H. (2022). AI for the public. How public interest theory shifts the discourse on AI. AI & SOCIETY.
Baum, S. D. (2020). Social choice ethics in artificial intelligence. AI & SOCIETY, 35(1), 165–176.
Bondi, E., Xu, L., Acosta-Navas, D., & Killian, J. A. (2021). Envisioning Communities: A Participatory Approach Towards AI for Social Good. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 425–436.
Cowls, J., King, T., Taddeo, M., & Floridi, L. (2019). Designing AI for Social Good: Seven Essential Factors (SSRN Scholarly Paper No. 3388669). Social Science Research Network.
Cowls, J., Tsamados, A., Taddeo, M., & Floridi, L. (2021). A definition, benchmark and database of AI for social good initiatives. Nature Machine Intelligence, 3(2), 111–115.
Eliot, D. L. B. (n.d.). The Neglected Dualism Of Artificial Moral Agency And Artificial Legal Reasoning In AI For Social Good. 4.
Floridi, L. (2019). Establishing the rules for building trustworthy AI. Nature Machine Intelligence, 1(6), 261–262.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2021). An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. In L. Floridi (Ed.), Ethics, Governance, and Policies in Artificial Intelligence (pp. 19–39). Springer International Publishing.
Floridi, L., Cowls, J., King, T. C., & Taddeo, M. (2020). How to Design AI for Social Good: Seven Essential Factors. Science and Engineering Ethics, 26(3), 1771–1796.
Hager, G. D., Drobnis, A., Fang, F., Ghani, R., Greenwald, A., Lyons, T., Parkes, D. C., Schultz, J., Saria, S., Smith, S. F., & Tambe, M. (2019). Artificial Intelligence for Social Good (arXiv:1901.05406). arXiv.
Kshirsagar, M., Robinson, C., Yang, S., Gholami, S., Klyuzhin, I., Mukherjee, S., Nasir, M., Ortiz, A., Oviedo, F., Tanner, D., Trivedi, A., Xu, Y., Zhong, M., Dilkina, B., Dodhia, R., & Lavista Ferres, J. M. (2021). Becoming Good at AI for Good. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 664–673.
Li, V. O. K., Lam, J. C. K., & Cui, J. (2021). AI for Social Good: AI and Big Data Approaches for Environmental Decision-Making. Environmental Science & Policy, 125, 241–246.
Madianou, M. (2021). Nonhuman humanitarianism: When “AI for good” can be harmful. Information, Communication & Society, 24(6), 850–868.
Mccarthy, S. (2018, November 1). Google pledges $25 million to AI for social good. University Wire.
Moore, J. (2019). AI for Not Bad. Frontiers in Big Data, 2.
Selwyn, N., Cordoba, B. G., Andrejevic, M., & Campbell, L. (2020). AI For Social Good: Australian Public Attitudes Toward AI and Society.
Shi, Z. R., Wang, C., & Fang, F. (2020). Artificial Intelligence for Social Good: A Survey (arXiv:2001.01818). arXiv.
Slota, S. C., Fleischmann, K. R., Greenberg, S., Verma, N., Cummings, B., Li, L., & Shenefiel, C. (2020). Good systems, bad data?: Interpretations of AI hype and failures. Proceedings of the Association for Information Science and Technology, 57(1), e275.
Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751–752.
Theodorou, A., & Virginia, D. (2020). Towards ethical and socio-legal governance in AI. Nature Machine Intelligence, 2(1), 10–12.
Tomašev, N., Cornebise, J., Hutter, F., Mohamed, S., Picciariello, A., Connelly, B., Belgrave, D. C. M., Ezer, D., Haert, F. C. van der, Mugisha, F., Abila, G., Arai, H., Almiraat, H., Proskurnia, J., Snyder, K., Otake-Matsuura, M., Othman, M., Glasmachers, T., Wever, W. de, … Clopath, C. (2020). AI for social good: Unlocking the opportunity for positive impact. Nature Communications, 11(1), 2468.
Wearn, O. R., Freeman, R., & Jacoby, D. M. P. (2019). Responsible AI for conservation. Nature Machine Intelligence, 1(2), 72–73.
Wilder, B., Onasch-Vera, L., Diguiseppi, G., Petering, R., Hill, C., Yadav, A., Rice, E., & Tambe, M. (2021). Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 14948–14956.
Polson, N., & Scott, J. (2018). AIQ: How Artificial Intelligence Works and How We Can Harness Its Power for a Better World. London: Bantam Press.