Predicting Risk to Sustainable Play - An AI Journey
Session Title
Session 2-3-D: Policy and Regulation, Part 5
Presentation Type
Paper Presentation
Start Date
24-5-2023 1:30 PM
End Date
24-5-2023 3:00 PM
Disciplines
Data Science
Abstract
Using AI to predict potentially problematic play has often focused on self cancellation, using supervised learning. Practice typically centres on isolating the small group of players who may develop elevated signs of risk or harm. But the increases use of tools like bank blocks means we need new approaches to predicting risk. And increasingly, we want to focus on the whole player base.
This presentation aims to:
- Outline an unsupervised learning approach to predicting risk from patterns of play
- Explore the potential for AI to be used to measure sustainable as well as potentially risky play
- Place sustainable play in the wider context of personalised player journeys driven by AI
Keywords
AI, sustainable play, personalisation, safer play
Funding Sources
none
Competing Interests
none
Predicting Risk to Sustainable Play - An AI Journey
Using AI to predict potentially problematic play has often focused on self cancellation, using supervised learning. Practice typically centres on isolating the small group of players who may develop elevated signs of risk or harm. But the increases use of tools like bank blocks means we need new approaches to predicting risk. And increasingly, we want to focus on the whole player base.
This presentation aims to:
- Outline an unsupervised learning approach to predicting risk from patterns of play
- Explore the potential for AI to be used to measure sustainable as well as potentially risky play
- Place sustainable play in the wider context of personalised player journeys driven by AI