Living systems are smarter bots: Slime mold semiosis versus AI symbol manipulation

The creativity of cells: aneural irrational cognition

Evidence of cognition in aneural cells is well-establish in the literature. This paper extends the exploration of the mechanisms of cognition by considering whether or not aneural cells may be capable of irrational cognition, making associations based on coincidental similarities and circumstantial factors. If aneural cells do harness such semiosic qualities, as with higher-level creativity, this might be how they are able to overcome old algorithms and invent tools for new situations. I will look at three examples of irrational learning in aneural systems in terms of semiotics: (1) generalisation in the immune system, based on viral molecular mimicry, whereby immune cells attack the self, which seems to be an overgeneralisation of an icon sign based on mere similarity, not identity, (2) the classical conditioning of pea plants to trope toward wind as a sign of light, which seems to be an association of an index sign based on mere temporal proximity, and (3) a pharmaceutical intervention to prevent pregnancy, using a conjugate to encrypt self with non-self, which seems to be an example of symbol use. We identify irrational cognition easily when it leads to 'wrong' outcomes, but, if it occurs, it may also lead to favourable outcomes and 'creative' solutions.

The hiatus between organism and machine evolution: Contrasting mixed microbial communities with robots

Mixed microbial communities, usually composed of various bacterial and fungal species, are fundamental in a plethora of environments, from soil to human gut and skin. Their evolution is a paradigmatic example of intertwined dynamics, where not just the relations among species plays a role, but also the opportunities - and possible harms - that each species presents to the others. These opportunities are in fact affordances, which can be seized by heritable variations and selection. In this paper, starting from a systemic viewpoint of mixed microbial communities, we focus on the pivotal role of affordances in evolution and we contrast it to the artificial evolution of programs and robots. We maintain that the two realms are neatly separated, in that natural evolution proceeds by extending the space of its possibilities in a completely open way, while the latter is inherently limited by the algorithmic framework in which it is defined. This discrepancy characterizes also an envisioned setting in which robots evolve in the physical world. We present arguments supporting our claim and we propose an experimental setting for assessing our statements. Rather than just discussing the limitations of the artificial evolution of machines, the aim of this contribution is to emphasize the tremendous potential of the evolution of the biosphere, beautifully represented by the evolution of communities of microbes.