Tackling Bias in Data Science: from Prediction to Intervention
A Workshop on Transdisciplinary Data Science
November 15–17, 2021
100 Coronado Drive, Clearwater, FL 33767
The second edition of DAISY focuses on bias at large in data science, from models–biased predictions that fail to generalize or reiterate disparity–to people–structural barriers to inclusion and equity.
The symposium will feature invited talks and roundtables with academic researchers, industry, and federal agency representatives.
As in the DAISY tradition, transdisciplinarity is key. Themes will encompass individuals’ health & work life, and organizational perspectives. The common thread is ‘how to surpass biased prediction models that project a haunted past into intervention models that can change our future for the better’.
Jiang Bian, PhD
Department of Health Outcomes and Biomedical Informatics
College of Medicine
Director, Cancer Informatics and eHealth Core Program
University of Florida Health Cancer Center
Mattia Prosperi, MEng, PhD
College Coordinator for AI
Department of Epidemiology
College of Public Health and Health Professions and College of Medicine
Mo Wang, PhD
Lanzillotti-McKethan Eminent Scholar Chair
Director, Human Resource Research Center
Chair, Management Department
Warrington College of Business
David R Nelson, Senior Vice President for Health Affairs, UF & President, UF Health
Link to registration (Oct 1st): DAISY2021 Registration
Please send your inquiries to Ms. Tayla Hunt email@example.com.
The workshop will be able to accommodate ~60 people.
We will process RSVPs in the order we receive them until the planned cap.
Registration is free and there is availability of partial travel reimbursement for participants (until budget allows).
The event will also be publicly live-streamed:
The streaming links will be sent to the registered participants and posted on the program page.
Footnote: The workshop acronym is DAISY, which sounds graceful and easy to remember. We reverse engineered it into DAta Intelligence SYmposium, but any other interpretation is welcome!