Preventive digital care for addiction and mental illness

Important results from the project

** Denna text är maskinöversatt ** The main goal was to be able to use existing online player data in games, betting and self-tests to add classification of risk levels and make it self-learning. Achieved this by training an AI model to predict different results of the self-test that is beneficial for the analysts and classifying players risk categories (eg low medium and high) using the player´s historical bet. The dimensions we worked with are the five dimensions of the self-test, over consumption of time and money, and consequences for time, money and emotions.

Expected long term effects

** Denna text är maskinöversatt ** Sustainable Interaction works hard to contribute its knowledge in addiction, psychosocial health to take its customers towards more sustainable business models and businesses and meet rules in the gaming area. Assources and skills obtained through automated AI tools and this project will help to build AI competence also with the customer´s IT and development team. We expect a higher uptake and adoption of AI technology through our project and use of the results

Approach and implementation

** Denna text är maskinöversatt ** Successful parts - Create business value proposals for the client - Data collection and approval of player data management - Design of the AI model Less successful parts - Integration with client online data streamscomplaintsMXXRR000000XBR000