Social Commonsense

Social commonsense research focuses on imbuing artificial intelligence systems with an understanding of human social interactions and implicit knowledge, enabling them to generate more realistic and nuanced responses in various applications. Current research emphasizes integrating social commonsense knowledge into models through graph-based representations and leveraging techniques like Multiple Instance Learning and masked language models to detect misinformation and biases. This work is crucial for improving the reliability and ethical implications of AI systems, particularly in areas like conversational AI, fake news detection, and mitigating algorithmic bias.