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.

中文翻译：

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AAAI FSS-19：以人为本的人工智能：人工智能模型和数据处理的可信度

为了促进 AI 系统在实际应用中指导决策的广泛接受，解决方案必须包含可信赖的集成人类 AI 系统，这一点至关重要。不仅在自动驾驶或医学等安全关键应用中，而且在工业和政府的动态开放世界系统中，预测模型具有不确定性并产生可信赖的预测至关重要。在企业规模部署人工智能的另一个关键要求是意识到将以人为本的设计集成到人工智能系统中的重要性，以便人类能够有效地使用系统，理解结果和输出，并向监督委员会解释调查结果。虽然本次研讨会的重点是人工智能系统，以提高数据质量和技术稳健性和安全性，