# Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning

**Authors:** Procheta Sen, Debasis Ganguly  
**arXiv:** [2005.06618](https://arxiv.org/abs/2005.06618)  
**Date:** 2020-05-14  
**Summary page:** https://www.summarizepaper.com/en/paper/2005.06618v2/

## Key points

- Authors Procheta Sen and Debasis Ganguly address cognitive biases in human society and their impact on AI systems
- They propose a bias-aware multi-objective learning framework to combat biases based on identity attributes
- Experiments show the approach successfully reduces biases related to gender in emotion prediction tasks
- The research emphasizes the importance of developing socially responsible AI that actively mitigates cognitive biases from historical data

## Summary

In their paper titled "Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning," authors Procheta Sen and Debasis Ganguly address the issue of cognitive biases in human society and their potential impact on AI systems. They propose a bias-aware multi-objective learning framework to combat this problem by reducing the frequency of predicting stereotypes based on identity attributes. Through experiments, they demonstrate how their approach successfully mitigates biases related to gender in emotion prediction tasks. This research highlights the importance of developing socially responsible AI that actively addresses and mitigates cognitive biases present in historical data.