论文标题
心灵差距：深度学习方法的挑战
Mind the gap: Challenges of deep learning approaches to Theory of Mind
论文作者
论文摘要
心理理论是人类推断他人心理状态的基本能力。在这里，我们提供了一个连贯的摘要，内容涉及深度学习方法理论的潜在，当前的进步和问题。我们强调，许多当前的发现可以通过快捷方式来解释。这些快捷方式之所以出现，是因为用于研究深度学习系统中思维理论的任务太狭窄了。因此，我们鼓励研究人员在复杂的开放式环境中调查心理理论。此外，为了激发未来的深度学习系统，我们简要概述了人类所做的先前工作。我们进一步认为，在深度学习研究心理理论时，研究的主要重点和贡献应该打开网络的表示。我们建议研究人员使用AI可解释性领域的工具来研究不同网络组成部分与心理理论方面之间的关系。
Theory of Mind is an essential ability of humans to infer the mental states of others. Here we provide a coherent summary of the potential, current progress, and problems of deep learning approaches to Theory of Mind. We highlight that many current findings can be explained through shortcuts. These shortcuts arise because the tasks used to investigate Theory of Mind in deep learning systems have been too narrow. Thus, we encourage researchers to investigate Theory of Mind in complex open-ended environments. Furthermore, to inspire future deep learning systems we provide a concise overview of prior work done in humans. We further argue that when studying Theory of Mind with deep learning, the research's main focus and contribution ought to be opening up the network's representations. We recommend researchers use tools from the field of interpretability of AI to study the relationship between different network components and aspects of Theory of Mind.
