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As humans are being progressively pushed further downstream in the decision-making process of autonomous systems, the need arises to ensure that moral standards, however defined, are adhered to by these robotic artifacts. While meaningful inroads have been made in this area regarding the use of ethical lethal military robots, including work by our laboratory, these needs transcend the warfighting domain and are pervasive, extending to eldercare, robot nannies, and other forms of service and entertainment robotic platforms. This paper presents an overview of the spectrum and specter of ethical issues raised by the advent of these systems, and various technical results obtained to date by our research group, geared towards managing ethical behavior in autonomous robots in relation to humanity. This includes: (1) the use of an ethical governor capable of restricting robotic behavior to predefined social norms; (2) an ethical adaptor which draws upon the moral emotions to allow a system to constructively and proactively modify its behavior based on the consequences of its actions; (3) the development of models of robotic trust in humans and its dual, deception, drawing on psychological models of interdependence theory; and (4) concluding with an approach towards the maintenance of dignity in human-robot relationships.

We vary the ability of robots to mitigate a participant's risk in a navigation guidance task to determine the effect this has on the participant's trust in the robot in a second round. A significant loss of trust was found after a single robot failure.

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Deception is utilized by a variety of intelligent systems ranging from insects to human beings. It has been argued that the use of deception is an indicator of theory of mind [2] and of social intelligence [4]. We use interdependence theory and game theory to explore the phenomena of deception from the perspective of robotics, and to develop an algorithm which allows an artificially intelligent system to determine if deception is warranted in a social situation. Using techniques introduced in [1], we present an algorithm that bases a robot's deceptive action selection on its model of the individual it's attempting to deceive. Simulation and robot experiments using these algorithms which investigate the nature of deception itself are discussed.