The Most Intelligent Robots Are Those that Exaggerate: Examining Robot Exaggeration

This paper presents a model of exaggeration suitable for implementation on a robot. Exaggeration is an interest form of dishonesty in that it serves as a tradeoff between the different costs associated with lying and the reward received by having one’s lie accepted. Moreover, exaggeration offers the deceiver additional control in the form of much the exaggerated statement differs from the truth. We use a color guessing game to examine the different tradeoffs between these costs and rewards and their impact on exaggeration. Our results indicate some amount of exaggeration is the preferred option during most early interactions. Further, because the cost of lying increases linear with the number of lies, exaggeration decreases with additional interactions. We conclude by arguing why social robots must be capable of lying.