Cost-Aware Counterfactuals for Black Box Explanations
Natalia Martinez Gil, Kanthi Sarpatwar, et al.
NeurIPS 2023
Artificial Intelligent (AI) and Machine Learning (ML) algorithms are coming out of research labs into the real-world applications, and recent research has focused a lot on Human-AI Interaction (HAI) and Explainable AI (XAI). However, Interaction is not the same as Collaboration. Collaboration involves mutual goal understanding, preemptive task co-management and shared progress tracking. Most of human activities today are done collaboratively, thus, to integrate AI into the already-complicated human workflow, it is critical to bring the Computer-Supported Cooperative Work (CSCW) perspective into the root of the algorithmic research and plan for a Human-AI Collaboration future of work. In this panel we ask: Can this future for trusted human-AI collaboration be realized? If so, what will it take? This panel will bring together HCI experts who work on human collaboration and AI applications in various application contexts, from industry and academia and from both the U.S. and China. Panelists will engage the audience through discussion of their shared and diverging visions, and through suggestions for opportunities and challenges for the future of human-AI collaboration.
Natalia Martinez Gil, Kanthi Sarpatwar, et al.
NeurIPS 2023
Aaron Tabor, Ian C.J. Smith, et al.
CHI EA 2020
Heloisa Candello, Cosmin Munteanu, et al.
CHI EA 2020
Xiangmin Fan, Junfeng Yao, et al.
CHI EA 2020