Bridging the Gap: Protocol Towards Fair and Consistent Affect Analysis

Understand

The increasing integration of machine learning algorithms in daily life underscores the critical need for fairness and equity in their deployment.

• As these technologies play a pivotal role in decision-making, addressing biases across diverse subpopulation groups, including age, gender, and race, becomes paramount.
• Automatic affect analysis, at the intersection of physiology, psychology, and machine learning, has seen significant development.
• However, existing databases and methodologies lack uniformity, leading to biased evaluations.