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.

翻译：人类感知、记忆与决策受到数十种影响我们行动和判断的认知偏差与启发式的影响。尽管这些偏差普遍存在，但当今建模人类行为并与人类交互的人工智能系统通常并未利用它们。在这篇理论性论文中，我们认为人机协作的未来将涉及开发能够建模、理解并可能复现人类认知偏差的人工智能系统。我们提出有必要开展关于人类认知偏差与人工智能相互作用的研究议程。我们从人工智能系统的角度对现有认知偏差进行分类，识别出三个主要研究领域，并概述了设计更深入理解我们自身偏差的人工智能系统的研究方向。