This article tackles the topic of the special issue “Biology
in AI: New Frontiers in Hardware, Software and Wetware Modeling
of Cognition” in two ways. It addresses the problem of the relevance
of hardware, software, and wetware models for the scientific
understanding of biological cognition, and it clarifies the
contributions that synthetic biology, construed as the synthetic
exploration of cognition, can offer to artificial intelligence (AI). The
research work proposed in this article is based on the idea that the
relevance of hardware, software, and wetware models of biological
and cognitive processes—that is, the concrete contribution that
these models can make to the scientific understanding of life and
cognition—is still unclear, mainly because of the lack of explicit
criteria to assess in what ways synthetic models can support the
experimental exploration of biological and cognitive phenomena.
Our article draws on elements from cybernetic and autopoietic
epistemology to define a framework of reference, for the synthetic
study of life and cognition, capable of generating a set of assessment
criteria and a classification of forms of relevance, for synthetic
models, able to overcome the sterile, traditional polarization of their
evaluation between mere imitation and full reproduction of the target
processes. On the basis of these tools, we tentatively map the forms
of relevance characterizing wetware models of living and cognitive
processes that synthetic biology can produce and outline a
programmatic direction for the development of “organizationally
relevant approaches” applying synthetic biology techniques to the
investigative field of (embodied) AI
