Embodied AI, the main direction of AI engaged in the synthetic modeling of natural cognition, is generally based on hardware-software approaches. Here we present the general lines of a proposal referred as the “wetware route” to Embodied AI , construed as the ideation and implementation of chemical models of cognitive processes inspired by the theory of autopoiesis. Our approach proposes to focus on the organizational traits that characterize autopoietic systems as cognitive systems, and accordingly attempts to define a viable organizational Embodied AI research program in the nascent wetware sci-tech arena of Synthetic Biology.

This paper describes a potentially rewarding research program aimed at designing, modeling, analyzing and experimentally realizing artificial cells in the wetware domain endowed with a ‘neural network’-like module for achieving minimal perception. In particular, we present a possible implementation based on bacterial phosphorylation signaling networks (dubbed as “phospho-neural network” by Hellingwerf and collaborators in 1995 ). At this initial stage only preliminary discussions are possible. The scenario we devise minimizes unrealistic assumptions and it is based on the state-of-the-art of contemporary artificial cell technology. This contribution is intended as a plan to forster the construction and the theoretical analysis of next-generation artificial cells.

This programmatic paper continues a series of works that we are dedicating to introduce a novel research program in AI, which we call Autopoietic SB-AI to indicate two basic elements of its procedural architecture. (1) The first element is the innovative methodological option of synthetically studying the cognitive domain based on the construction and experimental exploration of wetware –i.e., chemical – models of cognitive processes, using techniques defined in the field of Synthetic Biology (SB). (2) The second element is the theoretical option of developing SB models of cognitive processes based on the theory of autopoiesis. In our previous works we focused on the epistemological and theoretical groundings of Autopoietic SB-AI. In this contribution, after a general presentation of this research program, we introduce the SB technical framework that we are developing to orient Autopoietic SB-AI towards a twofold goal: building organizationally relevant wetware models of minimal biological-like systems (i.e., synthetic cells), and, on this basis, contributing to the scientific exploration of minimal cognition.

Recent progress in “artificial” (or “synthetic”) cell research has allowed the construction of sophisticated systems capable of sending/receiving chemical signals to/from biological cells. This new scenario paves the way to conceptually new technologies and scientific investigations based on interfacing organisms (natural cells) and robots (artificial cells) and exploiting their built-in molecular communication capacity. The state-of-the-art is presented and commented from the perspective of Artificial Life and synthetic biology.

The “synthetic method” is the methodological approach that guides current scientific attempts of understanding natural processes by the construction of hardware, software, and/or wetware models from scracth. It focuses the scientific inquiry on the generative mechanisms of the target processes, with the goal of testing and improving scientific hypotheses about them. This article presents an application of the synthetic method based on cutting-edge technology: the construction of “synthetic cells” (also known as “artificial cells”) capable of exchanging chemical signals (and, in this sense, of ‘communicating’) with biological cells.