Human Mind
Research on the human mind currently focuses on understanding complex cognitive processes like Theory of Mind (ToM), the ability to understand others' mental states, and its implications for human-AI interaction and collaboration. This involves developing and evaluating computational models, often employing large language models (LLMs) and multimodal architectures, to predict and simulate human behavior in various social and collaborative contexts. Key areas of investigation include improving the accuracy and efficiency of these models, particularly in handling uncertainty and noisy data, and exploring the ethical implications of increasingly sophisticated AI systems capable of understanding and responding to human mental states. These advancements have significant implications for improving human-computer interaction, developing more effective assistive technologies, and furthering our understanding of the human mind itself.
Papers
Machine Theory of Mind for Autonomous Cyber-Defence
Luke Swaby, Matthew Stewart, Daniel Harrold, Chris Willis, Gregory Palmer
Augmenting Minds or Automating Skills: The Differential Role of Human Capital in Generative AI's Impact on Creative Tasks
Meiling Huang, Ming Jin, Ning Li
MIND: Effective Incorrect Assignment Detection through a Multi-Modal Structure-Enhanced Language Model
Yunhe Pang, Bo Chen, Fanjin Zhang, Yanghui Rao, Jie Tang