Abstract Number:
1238
Submission Type:
Invited Panel Session
Participants:
Stephan Sain (1), David Clifford (2), Maria Terres (3), Marian Farah (4), Victoria Gamerman (5), Haoda Fu (6), Stephan Sain (1)
Institutions:
(1) Jupiter Intelligence, N/A, (2) Mineral.ai, N/A, (3) Waymo, N/A, (4) Cana Technology, Inc., N/A, (5) Boehringer Ingelheim, N/A, (6) Eli Lilly and Company, N/A
Chair:
Panelist(s):
Session Organizer:
Session Description:
The recent attention surrounding large-scale large language models (LLMs), such as the GPT series, has spawned much conversation about the role of machine learning (ML) and, more generally, artificial intelligence (AI), in many different settings. While LLMs and AI/ML have tremendous potential, there are also many issues and open questions. Given industry's leading position and influence in AI research (e.g., Ahmed et al., Science, March, 2023), the Caucus of Industry Representatives (CIR) aims to bring together several experts from different business and industry sectors. This panel will discuss how AI/ML can drive innovation while also addressing challenges, benefits and risks, biases, ethics, data privacy, as well as opportunities for public-private collaborations.
The panel includes representation from different industries and sectors, including digital agriculture, self-driving cars, sustainability, biotech and pharmaceuticals. Further, the chair has a background weather and climate.
After brief introductions, the panel will answer questions prepared by the Caucus of Industry Representatives as well as questions from the audience.
Sponsors:
Committee on Applied Statisticians 3
Section on Statistical Learning and Data Science 2
Section on Text Analysis 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
Yes
Applied
Yes
Estimated Audience Size
Medium (80-150)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
I understand