Improving robot transparency: Real-time visualisation of robot AI substantially improves understanding in naive observers

Robert H. Wortham, Andreas Theodorou, J. Bryson
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引用次数: 37

Abstract

Deciphering the behaviour of intelligent others is a fundamental characteristic of our own intelligence. As we interact with complex intelligent artefacts, humans inevitably construct mental models to understand and predict their behaviour. If these models are incorrect or inadequate, we run the risk of self deception or even harm. Here we demonstrate that providing even a simple, abstracted real-time visualisation of a robot's AI can radically improve the transparency of machine cognition. Findings from both an online experiment using a video recording of a robot, and from direct observation of a robot show substantial improvements in observers' understanding of the robot's behaviour. Unexpectedly, this improved understanding was correlated in one condition with an increased perception that the robot was ‘thinking’, but in no conditions was the robot's assessed intelligence impacted. In addition to our results, we describe our approach, tools used, implications, and potential future research directions.
提高机器人的透明度:机器人人工智能的实时可视化大大提高了朴素观察者的理解能力
解读聪明的人的行为是我们自身智力的一个基本特征。当我们与复杂的智能人工制品互动时,人类不可避免地会构建心智模型来理解和预测它们的行为。如果这些模式不正确或不充分,我们就会冒着自我欺骗甚至伤害的风险。在这里,我们证明,即使提供一个简单的、抽象的机器人人工智能的实时可视化,也可以从根本上提高机器认知的透明度。使用机器人视频记录的在线实验和直接观察机器人的结果都表明,观察者对机器人行为的理解有了实质性的提高。出乎意料的是,在一种情况下,这种理解的提高与机器人“思考”的感知增强有关,但在任何情况下,机器人的评估智力都没有受到影响。除了我们的结果之外,我们还描述了我们的方法,使用的工具,含义和潜在的未来研究方向。
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