AAAI FSS-19: Human-Centered AI: Trustworthiness of AI Models and Data Proceedings

Autor:	Buettner, Florian, Piorkowski, John, McCulloh, Ian, Waltinger, Ulli
Rok vydání:	2020
Předmět:	Computer Science - Artificial Intelligence Computer Science - Computers and Society Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	To facilitate the widespread acceptance of AI systems guiding decision-making in real-world applications, it is key that solutions comprise trustworthy, integrated human-AI systems. Not only in safety-critical applications such as autonomous driving or medicine, but also in dynamic open world systems in industry and government it is crucial for predictive models to be uncertainty-aware and yield trustworthy predictions. Another key requirement for deployment of AI at enterprise scale is to realize the importance of integrating human-centered design into AI systems such that humans are able to use systems effectively, understand results and output, and explain findings to oversight committees. While the focus of this symposium was on AI systems to improve data quality and technical robustness and safety, we welcomed submissions from broadly defined areas also discussing approaches addressing requirements such as explainable models, human trust and ethical aspects of AI. Comment: Proceedings for AAAI 2019 Fall Symposium Series - Human-centered AI: Trustworthiness of AI Models & Data
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2001.05375 Zobrazit plný text záznamu View this record from Arxiv