Sarah E. Nelson, PhD, Cambridge Health Alliance and Harvard Medical School
WEDNESDAY, MAY 15, 2024 2 – 3:30 p.m. Eastern
Approved for 1.5 CE Hours
Responsible gambling (RG) algorithms appear to have become more complex and nuanced over time, with “AI” and “machine learning” serving as buzz words to signal their legitimacy. However, no matter how complex our models, they are only as valid as the data and outcomes upon which they are built and validated. This talk entreats the audience to return to basics and consider both the building blocks and pitfalls of RG algorithms. The talk will touch on the outcomes used to validate and evaluate these algorithms, how we distinguish involvement from risk for problems, potential algorithmic biases, and the proper use of algorithms within a larger RG system.
Dr. Sarah Nelson is the director for research at the Division on Addiction, Cambridge Health Alliance, a Harvard Medical School teaching hospital, as well as an associate professor of psychology in the department of psychiatry at Harvard Medical School.
The webinar is free but advance registration is required: https://reedexpo.zoom.us/webinar/register/WN_CuLlomirTGmUsEb07mUhKQ#/registration
Learning objectives:
As a result of this program, learners will be able to:
- Identify both the promise and pitfalls of gambling algorithms in programs designed to prevent gambling problems.
- Apply these findings to the development of machine learning in responsible gambling programs.
