Can We Agree on What Robots Should be Allowed to Do? An Exercise in Rule Selection for Ethical Care Robots

Future Care Robots (CRs) should be able to balance a patient’s, often conflicting, rights without ongoing supervision. Many of the trade-offs faced by such a robot will require a degree of moral judgment. Some progress has been made on methods to guarantee robots comply with a predefined set of ethical rules. In contrast, methods for selecting these rules are lacking. Approaches departing from existing philosophical frameworks, often do not result in implementable robotic control rules. Machine learning approaches are sensitive to biases in the training data and suffer from opacity. Here, we propose an alternative, empirical, survey-based approach to rule selection. We suggest this approach has several advantages, including transparency and legitimacy. The major challenge for this approach, however, is that a workable solution, or social compromise, has to be found: it must be possible to obtain a consistent and agreed-upon set of rules to govern robotic behavior. In this article, we present an exercise in rule selection for a hypothetical CR to assess the feasibility of our approach. We assume the role of robot developers using a survey to evaluate which robot behavior potential users deem appropriate in a practically relevant setting, i.e., patient non-compliance. We evaluate whether it is possible to find such behaviors through a consensus. Assessing a set of potential robot behaviors, we surveyed the acceptability of robot actions that potentially violate a patient’s autonomy or privacy. Our data support the empirical approach as a promising and cost-effective way to query ethical intuitions, allowing us to select behavior for the hypothetical CR

Is there room for the BBC in the mental lexicon? On the recognition of acronyms

It has been suggested that acronyms like BBC are processed like real words. This claim has been based on improved performance with acronyms in the Reicher-Wheeler task, the letter string matching task, the visual feature integration task, and the N400 component in event-related potential (ERP) studies. Unfortunately, in all these tasks performance on acronyms resembled performance on pseudowords more than performance on words. To further assess the similarity of acronyms and words, we focused on the meaning of the acronyms and used masked priming to examine whether target words can be primed to the same extent with associatively related acronyms as with associatively related words. Such priming was possible at a stimulus onset asynchrony (SOA) of 84ms. In addition, the priming of the acronyms did not depend on the letter case in which they were presented: The target word books was primed as much by isbn and iSbN as by ISBN

An architecture for ethical robots inspired by the simulation theory of cognition

The expanding ability of robots to take unsupervised decisions renders it imperative that mechanisms are in place to guarantee the safety of their behaviour. Moreover, intelligent autonomous robots should be more than safe; arguably they should also be explicitly ethical. In this paper, we put forward a method for implementing ethical behaviour in robots inspired by the simulation theory of cognition. In contrast to existing frameworks for robot ethics, our approach does not rely on the verification of logic statements. Rather, it utilises internal simulations which allow the robot to simulate actions and predict their consequences. Therefore, our method is a form of robotic imagery. To demonstrate the proposed architecture, we implement a version of this architecture on a humanoid NAO robot so that it behaves according to Asimov's laws of robotics. In a series of four experiments, using a second NAO robot as a proxy for the human, we demonstrate that the Ethical Layer enables the robot to prevent the human from coming to harm in simple test scenarios

Sensorimotor Model of Obstacle Avoidance in Echolocating Bats

Bat echolocation is an ability consisting of many subtasks such as navigation, prey detection and object recognition. Understanding the echolocation capabilities of bats comes down to isolating the minimal set of acoustic cues needed to complete each task. For some tasks, the minimal cues have already been identified. However, while a number of possible cues have been suggested, little is known about the minimal cues supporting obstacle avoidance in echolocating bats. In this paper, we propose that the Interaural Intensity Difference (IID) and travel time of the first millisecond of the echo train are sufficient cues for obstacle avoidance. We describe a simple control algorithm based on the use of these cues in combination with alternating ear positions modeled after the constant frequency bat Rhinolophus rouxii. Using spatial simulations (2D and 3D), we show that simple phonotaxis can steer a bat clear from obstacles without performing a reconstruction of the 3D layout of the scene. As such, this paper presents the first computationally explicit explanation for obstacle avoidance validated in complex simulated environments. Based on additional simulations modelling the FM bat Phyllostomus discolor, we conjecture that the proposed cues can be exploited by constant frequency (CF) bats and frequency modulated (FM) bats alike. We hypothesize that using a low level yet robust cue for obstacle avoidance allows bats to comply with the hard real-time constraints of this basic behaviour

Rational imitation for robots: the cost difference model

© 2017, © The Author(s) 2017. Infants imitate behaviour flexibly. Depending on the circumstances, they copy both actions and their effects or only reproduce the demonstrator’s intended goals. In view of this selective imitation, infants have been called rational imitators. The ability to selectively and adaptively imitate behaviour would be a beneficial capacity for robots. Indeed, selecting what to imitate is an outstanding unsolved problem in the field of robotic imitation. In this paper, we first present a formalized model of rational imitation suited for robotic applications. Next, we test and demonstrate it using two humanoid robots

Dominant Glint Based Prey Localization in Horseshoe Bats: A Possible Strategy for Noise Rejection

Rhinolophidae or Horseshoe bats emit long and narrowband calls. Fluttering insect prey generates echoes in which amplitude and frequency shifts are present, i.e. glints. These glints are reliable cues about the presence of prey and also encode certain properties of the prey. In this paper, we propose that these glints, i.e. the dominant glints, are also reliable signals upon which to base prey localization. In contrast to the spectral cues used by many other bats, the localization cues in Rhinolophidae are most likely provided by self-induced amplitude modulations generated by pinnae movement. Amplitude variations in the echo not introduced by the moving pinnae can be considered as noise interfering with the localization process. The amplitude of the dominant glints is very stable. Therefore, these parts of the echoes contain very little noise. However, using only the dominant glints potentially comes at a cost. Depending on the flutter rate of the insect, a limited number of dominant glints will be present in each echo giving the bat a limited number of sample points on which to base localization. We evaluate the feasibility of a strategy under which Rhinolophidae use only dominant glints. We use a computational model of the echolocation task faced by Rhinolophidae. Our model includes the spatial filtering of the echoes by the morphology of the sonar apparatus of Rhinolophus rouxii as well as the amplitude modulations introduced by pinnae movements. Using this model, we evaluate whether the dominant glints provide Rhinolophidae with enough information to perform localization. Our simulations show that Rhinolophidae can use dominant glints in the echoes as carriers for self-induced amplitude modulations serving as localization cues. In particular, it is shown that the reduction in noise achieved by using only the dominant glints outweighs the information loss that occurs by sampling the echo