Much research in robotic artificial intelligence (AI) and Artificial Life has focused on autonomous agents as an embodied and situated approach to AI. Such systems are commonly viewed as overcoming many of the philosophical problems associated with traditional computationalist AI and cognitive science, such as the grounding problem (Harnad) or the lack of intentionality (Searle), because they have the physical and sensorimotor grounding that traditional AI was argued to lack. Robot lawn mowers and self-driving cars, for example, more or less reliably avoid obstacles, approach charging stations, and so on—and therefore might be considered to have some form of artificial intentionality or intentional directedness. It should be noted, though, that the fact that robots share physical environments with people does not necessarily mean that they are situated in the same perceptual and social world as humans. For people encountering socially interactive systems, such as social robots or automated vehicles, this poses the nontrivial challenge to interpret them as intentional agents to understand and anticipate their behavior but also to keep in mind that the intentionality of artificial bodies is fundamentally different from their natural counterparts. This requires, on one hand, a “suspension of disbelief ” but, on the other hand, also a capacity for the “suspension of belief.” This dual nature of (attributed) artificial intentionality has been addressed only rather superficially in embodied AI and social robotics research. It is therefore argued that Bourgine and Varela’s notion of Artificial Life as the practice of autonomous systems needs to be complemented with a practice of socially interactive autonomous systems , guided by a better understanding of the differences between artificial and biological bodies and their implications in the context of social interactions between people and technology.

We present a novel example of a biomechatronic hybrid system. The living component of the system, embedded within microbial fuel cells, relies on the availability of food and water in order to produce electrical energy. The latter is essential to the operations of the mechatronic component, responsible for finding and collecting food and water, and for the execution of work. In simulation, we explore the behavioral and cognitive consequences of this symbiotic relation. In particular we highlight the importance of the integration of sensorimotor and metabolic signals within an evolutionary perspective, in order to create sound cognitive living technology .