Designing robots that do no harm: understanding the challenges of Ethics for Robots

This article describes key challenges in creating an ethics "for" robots. Robot ethics is not only a matter of the effects caused by robotic systems or the uses to which they may be put, but also the ethical rules and principles that these systems ought to follow-what we call "Ethics for Robots." We suggest that the Principle of Nonmaleficence, or "do no harm," is one of the basic elements of an ethics for robots-especially robots that will be used in a healthcare setting. We argue, however, that the implementation of even this basic principle will raise significant challenges for robot designers. In addition to technical challenges, such as ensuring that robots are able to detect salient harms and dangers in the environment, designers will need to determine an appropriate sphere of responsibility for robots and to specify which of various types of harms must be avoided or prevented. These challenges are amplified by the fact that the robots we are currently able to design possess a form of semi-autonomy that differs from other more familiar semi-autonomous agents such as animals or young children. In short, robot designers must identify and overcome the key challenges of an ethics for robots before they may ethically utilize robots in practice.

Shared Control of Bimanual Robotic Limbs With a Brain-Machine Interface for Self-Feeding

Advances in intelligent robotic systems and brain-machine interfaces (BMI) have helped restore functionality and independence to individuals living with sensorimotor deficits; however, tasks requiring bimanual coordination and fine manipulation continue to remain unsolved given the technical complexity of controlling multiple degrees of freedom (DOF) across multiple limbs in a coordinated way through a user input. To address this challenge, we implemented a collaborative shared control strategy to manipulate and coordinate two Modular Prosthetic Limbs (MPL) for performing a bimanual self-feeding task. A human participant with microelectrode arrays in sensorimotor brain regions provided commands to both MPLs to perform the self-feeding task, which included bimanual cutting. Motor commands were decoded from bilateral neural signals to control up to two DOFs on each MPL at a time. The shared control strategy enabled the participant to map his four-DOF control inputs, two per hand, to as many as 12 DOFs for specifying robot end effector position and orientation. Using neurally-driven shared control, the participant successfully and simultaneously controlled movements of both robotic limbs to cut and eat food in a complex bimanual self-feeding task. This demonstration of bimanual robotic system control via a BMI in collaboration with intelligent robot behavior has major implications for restoring complex movement behaviors for those living with sensorimotor deficits.