Human Ai Collaboration
Human-AI collaboration (HAIC) research focuses on optimizing the interaction between humans and artificial intelligence systems to achieve superior outcomes compared to either alone. Current research emphasizes improving AI explainability and transparency, particularly through methods like Shapley values and explainable AI (XAI), to foster trust and appropriate reliance, while also addressing issues like AI bias and the potential for misinformation from incorrect explanations. This field is significant because effective HAIC can enhance decision-making across diverse domains, from healthcare and cybersecurity to software engineering and scientific discovery, ultimately leading to more efficient and reliable processes.
Papers
GOLF: Goal-Oriented Long-term liFe tasks supported by human-AI collaboration
Ben Wang
"It is there, and you need it, so why do you not use it?" Achieving better adoption of AI systems by domain experts, in the case study of natural science research
Auste Simkute, Ewa Luger, Michael Evans, Rhianne Jones
An Empirical Study on Usage and Perceptions of LLMs in a Software Engineering Project
Sanka Rasnayaka, Guanlin Wang, Ridwan Shariffdeen, Ganesh Neelakanta Iyer
3DPFIX: Improving Remote Novices' 3D Printing Troubleshooting through Human-AI Collaboration
Nahyun Kwon, Tong Sun, Yuyang Gao, Liang Zhao, Xu Wang, Jeeeun Kim, Sungsoo Ray Hong