Human Machine

Human-machine interaction research focuses on improving collaboration and understanding between humans and artificial intelligence systems, aiming to leverage the strengths of both. Current efforts concentrate on developing more efficient and interpretable models, often employing deep learning architectures like transformers and generative models (e.g., StyleGAN, diffusion models), and incorporating human feedback through techniques such as active learning and human-in-the-loop approaches. This field is crucial for advancing AI safety, improving the usability of AI systems across diverse applications (e.g., healthcare, manufacturing, online safety), and gaining a deeper understanding of human cognition through comparative analysis with AI.