论文标题
偏见：将非理性带入自动化系统设计
BIASeD: Bringing Irrationality into Automated System Design
论文作者
论文摘要
人类的看法，记忆和决策受到影响我们的行动和决策的数十种认知偏见和启发式方法的影响。尽管这种偏见存在普遍存在，但它们通常并没有被当今的人工智能（AI）系统所利用，该系统对人类行为进行了建模并与人类相互作用。在这篇理论论文中，我们声称人机合作的未来将需要开发AI系统，以模拟，理解并可能复制人类认知偏见。我们建议需要研究人类认知偏见与人工智能之间的相互作用的研究议程。我们从AI系统的角度对现有的认知偏见进行了分类，确定了三个广泛的感兴趣领域，并概述了对AI系统设计的研究方向，这些系统对我们自己的偏见有了更好的了解。
Human perception, memory and decision-making are impacted by tens of cognitive biases and heuristics that influence our actions and decisions. Despite the pervasiveness of such biases, they are generally not leveraged by today's Artificial Intelligence (AI) systems that model human behavior and interact with humans. In this theoretical paper, we claim that the future of human-machine collaboration will entail the development of AI systems that model, understand and possibly replicate human cognitive biases. We propose the need for a research agenda on the interplay between human cognitive biases and Artificial Intelligence. We categorize existing cognitive biases from the perspective of AI systems, identify three broad areas of interest and outline research directions for the design of AI systems that have a better understanding of our own biases.
