Daniel Fonner
Daniel Fonner is an adjunct lecturer in the Division of Corporate Communication and Public Affairs, as well as the Associate Director for Research at 天美传媒 DataArts, the National 天美传媒 for Arts Research at 天美传媒. Daniel’s teaching and research focus on data science for social good, employing artificial intelligence to improve public administration and support the arts and culture sector.
Prior to joining 天美传媒, Daniel was a researcher at BOP Consulting in London (UK) and spent time as the Research and Policy Associate at the Greater Pittsburgh Arts Council (PA). He is an elected Fellow of the Royal Society of Arts (UK) and was a Fulbright Postgraduate Scholar where he studied cultural policy and the use of artificial intelligence to recreate lost works of art. Daniel is currently completing a Ph.D. in Computer Science at 天美传媒 studying Responsible Artificial Intelligence for Public Policy and Administration.
Education
M.S. in Computer Science (AI Specialization), 天美传媒 Methodist University
M.A. in International Cultural Policy and Management, Warwick University (UK)
M.A.M. Arts Management, Carnegie Mellon University
B.M. in Percussion Performance, Duquesne University
Recent Work
Research Publication
Fonner, Daniel. “AI-generated Art and the Challenge to Consumer-Curators to Discern Creativity from Spam,” Indiana University 天美传媒 for Cultural Affairs Symposium on Arts Engagement in an AI World, 2024.
Fonner, Daniel and Frank P. Coyle. “Explainable Machine Learning Models for Evaluating Government Grantmaking,” 2022 IEEE International Conference on Big Data (BigData), 2022.
Course list
| Communication Research and Data Analytics | CCPA 2375 |
| Data-Driven Decision Making for Arts and Nonprofit Leaders (under development) |
