This paper describes the results of an experiment in which human participants were required to detect degraded robot swarm behaviour and classify it as arising from either faulty or malicious robot activity in an idealised simulation of a multi-agent search and rescue task. The accuracy of participant judgements was influenced by the nature of the degradation, and between-participant differences in the extent to which they interacted with the swarm did not significantly influence their accuracy. It was found that detecting and classifying swarm degradation are challenging tasks that are likely to be strongly sensitive to task setting and will tend to require careful swarm system design and specific operator training.

This article argues that the application of an embodied cognitive science perspective does not require us to distinguish between systems that have a physically tangible body and systems that do not. I consider the specific case of ChatGPT, a large language model specialised for interactive dialogue, and argue that ChatGPT can potentially be seen as embodied, albeit with a very unfamiliar type of embodiment. I propose that we should explicitly distinguish between two notions of physicality: on the one hand, whether a system’s body is tangible or not (roughly, whether we imagine it as providing us tactile-kinesthetic affordances); on the other hand, whether a system is physically situated or not (i.e. whether or not it interacts physically with the rest of the Universe). I discuss whether or not tangibility should be accorded any major theoretical weight, within cognitive science, by considering several theoretical issues relating to embodiment: six from the previous literature, and four that I raise myself.. My conclusion is that (at least in regard to these aspects of embodied cognition) there is no good theoretical reason to treat tangible bodies as a prerequisite for embodied cognition. Hence, I argue that an interactive language model like Chat-GPT can, in principle, perceive the world and interact with it just as physically as a squid or robot does (albeit less tangibly) through text channels, which serve as its physical sensors and actuators. Whether or not we should understand it as doing so depends on its behaviour, not on its substrate.

We develop a naturalised account of planning, which identifies a class of functions (and their associated behaviours) in intelligent systems. The account identifies three principal components of a planning process: a system (defined by a set of possible system-environment decompositions); a subsystem (which presents a model, copy, or analog of some aspect of the system); and a selection mechanism (via which a subsystem is functionally related to expected future states). We give a generalised, system-independent account of planning, and then ground our analysis with a set of eight concrete reference systems, spanning biological, human, social, and artificial systems. Finally, we apply this naturalized account of planning to evaluate under what conditions planning behaviour is likely to emerge, and what failure modes arise in systems exhibiting such planning behaviour.

There are two types of trust: basic trust (BT) and secondary trust (ST). While ST refers to a rational mental state that is the result of individual-evidential decision making and calculation, BT is a relational state that the subjects experience. In this paper, drawing primarily on resources from the phenomenological-enactive approach to social cognition, I argue that there can be BT in the human-robot relation (HRR). This BT is the result of basic empathy for robots, that has been enriched by a long enough and complicated history of interaction with them. I propose a procedure according to which first basic empathy leads people to experience robots as pseudo-others, resulting in the formation of a thin and simple social relation. Then, through the history of interaction between people and robots, this simple, primary empathic-based social relation evolves into a more complicated and rich form of social relation that fosters the BT.

This contribution moves in the specific area of the philosophy of mind and, in particular, in that of the philosophy of free will. The question of free will, in fact, has always been at the center of philosophical debates and is still an open question today. The aim of this paper is to use the discipline of artificial intelligence as a magnifying glass for the free will problem in order to identify, through it, how this cognitive capacity is an androrithm : an element specific to the human being and irreproducible. Through an analysis of the similarities and dissimilarities that the question of artificial intelligence and that of free will share, and a brief review of the various types of freedom that - in the face of contemporary debate - could be present in both human beings and machines, we will come to the conclusion that the so-called ambitious free will, if it exists at all, can never be reproduced and is therefore characterized as a constitutive element of the human being.