Artificial Intelligence (AI) and it’s sub-discipline of machine learning (ML) are changing how we make decisions, operate businesses, facilitate discovery in science, arts and humanities, and minimize error and risk in safety-critical applications. However, proliferation of AI and ML-based systems also poses serious challenges in regards to robustness, trust, and the ability to ensure that human bias is not learned by machines.   To this end, the federal government is making large investments in AI including: 

Faculty and staff are encouraged to attend this brown bag to discuss how Chapman might pursue outside opportunities that require interdisciplinary teams. All parties that work in AI, machine learning, data science, and adjacent fields are encouraged to attend to help brainstorm ideas. This also includes how Chapman can collaborate with outside partners (e.g., academic, health, nonprofit, industry) to advance AI initiatives. Topics to be discussed in the meeting include (but are not limited to):

  • Current and future funding opportunities for AI/ML research
  • Institutional strengths in AI/ML research and education
  • Existing and future partnerships to support interdisciplinary research in AI/ML
  • Growth areas for Chapman that align with AI/ML research, creative works and education
  • Infrastructure (existing and needed)
  • Outreach to K-12 as a recruitment opportunity

RSVP (in person, remote or interest) by July 14, 2020. Please note that the in person option will be limited to 15 people and require conformance with Chapman Return to Campus guidelines. If you are not able to attend this brown bag, the meeting will be recorded and available for viewing. Please record your interest in the RSVP form.