The crying shame of robot nannies: An ethical appraisal

Childcare robots are being manufactured and developed with the long term aim of creating surrogate carers. While total child-care is not yet being promoted, there are indications that it is „on the cards‟. We examine recent research and developments in childcare robots and speculate on progress over the coming years by extrapolating from other ongoing robotics work. Our main aim is to raise ethical questions about the part or full-time replacement of primary carers. The questions are about human rights, privacy, robot use of restraint, deception of children and accountability. But the most pressing ethical issues throughout the paper concern the consequences for the psychological and emotional wellbeing of children. We set these in the context of the child development literature on the pathology and causes of attachment disorders. We then consider the adequacy of current legislation and international ethical guidelines on the protection of children from the overuse of robot care. Who’s to say that at some distant moment there might be an assembly line producing a gentle product in the form of a grandmother- whose stock in trade is love. From

Granny and the robots: ethical issues in robot care for the elderly

The growing proportion of elderly people in society, together with recent advances in robotics, makes the use of robots in elder care increasingly likely. We outline developments in the areas of robot applications for assisting the elderly and their carers, for monitoring their health and safety, and for providing them with companionship. Despite the possible benefits, we raise and discuss six main ethical concerns associated with: the potential reduction in the amount of human contact; an increase in the feelings of objectification and loss of control; a loss of privacy; a loss of personal liberty; deception and infantilisation; the circumstances in which elderly people should be allowed to control robots. We conclude by balancing the care benefits against the ethical costs. If introduced with foresight and careful guidelines, robots and robotic technology could improve the lives of the elderly, reducing their dependence, and creating more opportunities for social interactio

On the importance of sluggish state memory for learning long term dependency

The vanishing gradients problem inherent in Simple Recurrent Networks (SRN) trained with back-propagation, has led to a significant shift towards the use of Long Short-term Memory (LSTM) and Echo State Networks (ESN), which overcome this problem through either second order error-carousel schemes or different learning algorithms respectively. This paper re-opens the case for SRN-based approaches, by considering a variant, the Multi-recurrent Network (MRN). We show that memory units embedded within its architecture can ameliorate against the vanishing gradient problem, by providing variable sensitivity to recent and more historic information through layer- and self-recurrent links with varied weights, to form a so-called sluggish state-based memory. We demonstrate that an MRN, optimised with noise injection, is able to learn the long term dependency within a complex grammar induction task, significantly outperforming the SRN, NARX and ESN. Analysis of the internal representations of the networks, reveals that sluggish state-based representations of the MRN are best able to latch on to critical temporal dependencies spanning variable time delays, to maintain distinct and stable representations of all underlying grammar states. Surprisingly, the ESN was unable to fully learn the dependency problem, suggesting the major shift towards this class of models may be premature

Keeping them out and keeping us in: the robot border

Colloque international antiAtlas des Frontières
Nouveau Conservatoire Darius Milhaud, Aix-en-Provence
Du 30 septembre au 2 octobre 2013This talk will examine developments in future robotics technology that could be applied to the protection of borders. The use of unmanned aircraft is already being used to identify border incursions and track 'offenders'. And there are plans for the use of ground robots to intercept those crossing borders illegally. But this is just the beginning. The next generation of military robots will find their own targets and attack them without human supervision. Currently states are reluctant to give up such developments despite international protest. If they continue, it will only be a matter of time before autonomous robots enter service in the civilian world to help keep out 'illegal' immigrants. But in any discussion of the new technologies we must consider their potential misuse to seal us in

Why robots should not be delegated with the decision to kill

The EPSRC first principle of robotics, “robots should not be designed solely or primarily to kill or harm humans, except in the interests of national security”, is challenged in detail here. Focusing on security and armed conflict, arguments are marshalled against the principle on ethical, legal, technical and security grounds. A new principle is proposed that robots should never be delegated with the decision to apply violent force to humans

Neural Networks for Coordination and Control: The Portability of Experiential Representations

It is time to locate Connectionist representation theory in the new wave of robotics research. The utility of representations developed in Artificial Neural Networks during learning has been demonstrated in Cognitive Science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a Classifier net is trained with laser scan data; (ii) an Arm net is trained for picking up objects; (iii) an Inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalisation of decentered v..