A Conversation on Evaluating Machine Learning and Giving in the Arts 

Machine Learning is one of the latest trending topics setting the arts sector ablaze with concern and optimism. Innovative technologies under the umbrella of machine learning have the potential to impact many aspects of arts and culture. From arts creation to the administration of funding and access to arts and culture, the application of these new technologies is raising important ethical questions around equity and bias potentially present in these automated systems.
In preparation for upcoming research in partnership with Greater Pittsburgh Arts Council, we explore computational tools that have been created to assist grantmakers in their efforts to cultivate equitable funding practices to support their communities, and in doing so, explore the broader ethical context of applying machine learning in this domain. Will these tools help the sector increase equity and access to support? Should funders and arts and culture organizations trust these systems? Join us in conversation with Greater Pittsburgh Arts Council to discuss machine learning in grantmaking and the methods SMU DataArts is developing to evaluate their effectiveness.
Presenters & Panelists:
Mia Hooper, Director of Development and Grantmaking, Greater Pittsburgh Arts Council
Morgan Kasprowicz, Director of Research and Special Projects, Greater Pittsburgh Arts Council
Daniel Fonner, Associate Director of Research, SMU DataArts 
SMU DataArts Facilitators & Support:
Katie Ingersoll, Director of Communications, Engagement and Strategy, Host & Facilitator
Monica Lewis, Engagement Manager, Q&A & Tech Support
Rachelle Brisson, Events and Engagement Coordinator, Support
About SMU DataArts: www.culturaldata.org/about/
About Greater Pittsburgh Arts Council: www.pittsburghartscouncil.org/
Recommended Reads:
Researchers Turn to Machine Learning to Evaluate Equitable Practices in Grantmaking: culturaldata.org/learn/data-a...
Data Harm Record: datajusticelab.org/data-harm-...
Distributed AI Research Institute: www.dair-institute.org/about
Algorithmic Justice League: www.ajl.org/about
All Tech is Human: alltechishuman.org/responsibb...