Robots are being extensively used for the purpose of discovering and testing empirical hypotheses about biological sensorimotor mechanisms. We examine here methodological problems that have to be addressed in order to design and perform “good” experiments with these machine models. These problems notably concern the mapping of biological mechanism descriptions into robotic mechanism descriptions; the distinction between theoretically unconstrained “implementation details” and robotic features that carry a modeling weight; the role of preliminary calibration experiments; the monitoring of experimental environments for (...) disturbing factors that affect both modeling features and theoretically unconstrained implementation details of robots. Various assumptions that are gradually introduced in the process of setting up and performing these robotic experiments become integral parts of the background hypotheses that are needed to bring experimental observations to bear on biological mechanism descriptions. (shrink)

Bionic systems, connecting biological tissues with computer or robotic devices through brain–machine interfaces, can be used in various ways to discover biological mechanisms. In this article I outline and discuss a “stimulation-connection” bionics-supported methodology for the study of the brain, and compare it with other epistemic uses of bionic systems described in the literature. This methododology differs from the “synthetic”, simulative method often followed in theoretically driven Artificial Intelligence and cognitive science, even though it involves machine models of biological systems. (...) I also bring the previous analysis to bear on some claims on the epistemic value of bionic technologies made in the recent philosophical literature. I believe that the methodological reflections proposed here may contribute to the piecewise understanding of the many ways bionic technologies can be deployed not only to restore lost sensory-motor functions, but also to discover brain mechanisms. (shrink)

Cybernetics promoted machine-supported investigations of adaptive sensorimotor behaviours observed in biological systems. This methodological approach receives renewed attention in contemporary robotics, cognitive ethology, and the cognitive neurosciences. Its distinctive features concern machine experiments, and their role in testing behavioural models and explanations flowing from them. Cybernetic explanations of behavioural events, regularities, and capacities rely on multiply realizable mechanism schemata, and strike a sensible balance between causal and unifying constraints. The multiple realizability of cybernetic mechanism schemata paves the way to principled (...) comparisons between biological systems and machines. Various methodological issues involved in the transition from mechanism schemata to their machine instantiations are addressed here, by reference to a simple sensorimotor coordination task. These concern the proper treatment of ceteris paribus clauses in experimental settings, the significance of running experiments with correct but incomplete machine instantiations of mechanism schemata, and the advantage of operating with real machines ??? as opposed to simulated ones ??? immersed in real environments. (shrink)

In their theoretical and experimental reflections on the capacities and behaviours of living systems, neuroscientists often formulate generalizations about the behaviour of neural circuits. These generalizations are highly idealized, as they omit reference to the myriads of conditions that could perturb the behaviour of the modelled system in real-world settings. This article analyses an experimental investigation of the behaviour of place cells in the rat hippocampus, in which highly idealized generalizations were tested by comparing predictions flowing from them with real-world (...) experimental results. The aim of the article is to identify under what conditions even single prediction failures regarding the behaviour of single cells sufficed to reject highly idealized generalizations, and under what conditions prima facie counter-examples were deemed to be irrelevant to the testing of highly idealized generalizations. The results of this analysis may contribute to understanding how idealized models are tested experimentally in neuroscience and used to make reliable predictions concerning living systems in real-world settings. (shrink)

What can interactive robots offer to the study of social behaviour? Philosophical reflections about the use of robotic models in animal research have focused so far on methods involving robots which do not interact with the target system. Yet, leading researchers have claimed that interactive robots may constitute powerful experimental tools to study collective behaviour. Can they live up to these epistemic expectations? This question is addressed here by focusing on a particular experimental methodology involving interactive robots which has been (...) often adopted in animal research. This methodology is shown to differ from other robot-supported methods for the study of animal behaviour analysed in the philosophical literature, chiefly including the synthetic method. It is also discussed whether biomimicry and acceptability are necessary for an interactive robot to be sensibly used in animal research according to this method. (shrink)

This article addresses prospective and retrospective responsibility issues connected with medical robotics. It will be suggested that extant conceptual and legal frameworks are sufficient to address and properly settle most retrospective responsibility problems arising in connection with injuries caused by robot behaviours (which will be exemplified here by reference to harms occurred in surgical interventions supported by the Da Vinci robot, reported in the scientific literature and in the press). In addition, it will be pointed out that many prospective responsibility (...) issues connected with medical robotics are nothing but well-known robotics engineering problems in disguise, which are routinely addressed by roboticists as part of their research and development activities: for this reason they do not raise particularly novel ethical issues. In contrast with this, it will be pointed out that novel and challenging prospective responsibility issues may emerge in connection with harmful events caused by normal robot behaviours. This point will be illustrated here in connection with the rehabilitation robot Lokomat. (shrink)

Bionic technologies connecting biological nervous systems to computer or robotic devices for therapeutic purposes have been recently claimed to provide novel experimental tools for the investigation of biological mechanisms. This claim is examined here by means of a methodological analysis of bionics-supported experimental inquiries on adaptive sensory-motor behaviours. Two broad classes of bionic systems (regarded here as hybrid simulations of the target biological system) are identified, which differ from each other according to whether a component of the biological target system (...) is replaced by an artificial component, or else a component of an artificial system is replaced by a biological component. The role of these hybrid systems in the modelling of adaptive sensory-motor biological behaviours is discussed with reference to bionics-supported experiments on the mechanisms of body stabilization in lampreys. Methodological problems emerging from these case studies often arise in computer-based and biorobotic simulations of biological behaviours too. Accordingly, the present analysis contributes to identifying a more general regulative methodological framework for the machine-based modelling of biological systems. (shrink)

Research on hybrid bionic systems (HBSs) is still in its infancy but promising results have already been achieved in laboratories. Experiments on humans and animals show that artificial devices can be controlled by neural signals. These results suggest that HBS technologies can be employed to restore sensorimotor functionalities in disabled and elderly people. At the same time, HBS research raises ethical concerns related to possible exogenous and endogenous limitations to human autonomy and freedom. The analysis of these concerns requires reflecting (...) on the availability of scientific models accounting for key aspects of sensorimotor coordination and plastic adaptation mechanisms in the brain. (shrink)

Abstract. The rapid developments of robotics technologies in the last twenty years of the XX century have greatly encouraged research on the use of robots for surgery, diagnosis, rehabilitation, prosthetics, and assistance to disabled and elderly people. This chapter provides an overview of robotic technologies and systems for health care, focussing on various ethical problems that these technologies give rise to. These problems notably concern the protection of human physical and mental integrity, autonomy, responsibility, ...

First of all, in this paper we provide some clarifications on the several meanings of the term ‘ethics’, above all in the light of contemporary discussions on this matter. Then we analyze an important ethical concept, i.e. the concept of moral responsibility, for the sake of clarifying some problems concerning the human-robot relationship. Finally, we try to develop a well defined pattern of “ethics of responsibility” in order to give a general background for resolving concrete dilemmas that may arise in (...) the artificial world. (shrink)

In recent years, a number of research projects have been proposed whose goal is to build large-scale simulations of brain mechanisms at unprecedented levels of biological accuracy. Here it is argued that the roles these simulations are expected to play in neuroscientific research go beyond the “synthetic method” extensively adopted in Artificial Intelligence and biorobotics. In addition we show that, over and above the common goal of simulating brain mechanisms, these projects pursue various modelling ambitions that can be sharply distinguished (...) from one another, and that correspond to conceptually different interpretations of the notion of “biological accuracy”. They include the ambition to reach extremely deep levels in the mechanistic decomposition hierarchy, to simulate networks composed of extremely large numbers of neural units, to build systems able to generate rich behavioural repertoires, to simulate “complex” neuron models, to implement the “best” theories available on brain structure and function. Some questions will be raised concerning the significance of each of these modelling ambitions with respect to the various roles played by simulations in the study of the brain. (shrink)

In so-called ethorobotics and robot-supported social cognitive neurosciences, robots are used as scientific tools to study animal behavior and cognition. Building on previous epistemological analyses of biorobotics, in this article it is argued that these two research fields, widely differing from one another in the kinds of robots involved and in the research questions addressed, share a common methodology, which significantly differs from the “synthetic method” that, until recently, dominated biorobotics. The methodological novelty of this strategy, the research opportunities that (...) it opens, and the theoretical and technological challenges that it gives rise to, will be discussed with reference to the peculiarities of the two research fields. Some broad methodological issues related to the generalization of results concerning robot-animal interaction to theoretical conclusions on animal-animal interaction will be identified and discussed. (shrink)

Robotics and Philosophy of Science What relationship holds between robotics and philosophy of science? Can robotics research contribute to research in philosophy of science? Conversely, can the results achieved by philosophers of science contribute to the progress of research in robotics? This article will deal with both questions based on the distinction between the so-called philosophy of general science and the philosophy of the particular sciences. It will draw relatively pessimistic conclusions about the possibility that robotics research shed light on (...) questions pertaining to the philosophy of general science, and more optimistic conclusions about the potential contribution of robotics research to the philosophy of particular sciences. The normative aspect of philosophy of science is consistent with the possibility that this field of research, taking robotics as its object of study, provides guidelines and regulative methodological principles for engineers and roboticists. Through these considerations, this article attempts to explore a possible field of interaction between philosophy and scientific-technological research, with reference to a discipline that is assuming an increasingly predominant role in many aspects of daily life. (shrink)

Nijhawan argues convincingly that predictive mechanisms are pervasive in the central nervous system (CNS). However, scientific understanding of visual prediction requires one to formulate empirically testable neurophysiological models. The author's suggestions in this direction are to be evaluated on the basis of more realistic experimental methodologies and more plausible assumptions on the hierarchical character of the human visual cortex.

Simulation studies have been carried out in robotics for a variety of epistemic and practical purposes. Here it is argued that two broad classes of simulation studies can be identified in robotics research. The first one is exemplified by the use of robotic systems to acquire knowledge on living systems in so-called biorobotics, while the second class of studies is more distinctively connected to cases in which artificial systems are used to acquire knowledge about the behaviour of autonomous mobile robots. (...) The two classes pertain to sub-areas of robotics which are apparently quite distant from one another in terms of goals, methodologies, technologies, and theoretical backgrounds. Still both are concerned with building, running, and experimenting on simulations of other systems. This paper aims to reveal and discuss some methodological commonalities between the two classes of studies. Philosophical literature on simulation methodologies has been traditionally focused on studies carried out in research fields other than robotics: this article may therefore contribute to shedding light on how the concept of simulation is used in robotics, and on the role simulation methodologies play in this research field. (shrink)

A number of research projects have recently taken up the challenge of formulating large-scale models of brain mechanisms at unprecedented levels of detail. These research enterprises have raised lively debates in the press and in the scientific and philosophical literature, some of them revolving around the question whether the incorporation of so many details in a theoretical model and in a computer simulations of it is really needed for the model to be explanatory. Is there a “right” level of detail? (...) In this article I analyse the claim, made by two leading neuroscientists, according to which the content of the why-question addressed and the amount of computational resources available constrains the choice of the most appropriate level of detail in brain modelling. Based on the recent philosophical literature on scientific explanation, I distinguish between two kinds of details, called here mechanistic decomposition and property details, and argue that the nature of the why-question provides only partial constraints to the choice of the most appropriate level of detail under the two interpretations of the term considered here. (shrink)

The advancement of computing technology makes it possible to build extremely accurate digital reconstructions of brain circuits. Are such unprecedented levels of biological accuracy essential for brain simulations to play the roles they are expected to play in neuroscientific research? The main goal of this paper is to clarify this question by distinguishing between various roles played by large-scale simulations in contemporary neuroscience, and by reflecting about what makes a simulation biologically accurate. It is argued that large-scale simulations may play (...) model-oriented and prediction-oriented roles in brain research, and that the concept of biological accuracy can be interpreted as related to the plausibility of the theoretical model implemented in the simulation system, to the accuracy of the computer implementation, and to the level of details of the implemented model. Building on these observations and distinctions, it is argued that biological accuracy is not essential for a computer simulation to play the epistemic roles it is expected to play in brain research. (shrink)