ICTS

Prediction-based decision-making systems are becoming increasingly prevalent in various domains. Previous studies have demonstrated that such systems are vulnerable to runaway feedback loops which exacerbate existing biases. The automated decisions have dynamic feedback effects on the system itself. In this talk we will show how the existence of feedback loops in the machine learning-based decision-making pipeline can perpetuate and reinforce machine learning biases and propose control strategies to counteract their undesired effects.

Zoom link: https://us02web.zoom.us/j/81379290349
Meeting ID: 813 7929 0349

For more details of past and upcoming ICTS -OT/ML/PDE seminars please click the link