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.

Key words: autopoiesis, (embodied) ai, minimal cells, synthetic biology, synthetic cells.

When we attempt to define life, we tend to refer to individuals, those that are alive. But these individuals might be cells, organisms, colonies… ecosystems? We can describe living systems at different scales. Which ones might be the best ones to describe different selves? I explore this question using concepts from information theory, ALife, and Buddhist philosophy. After brief introductions, I review the implications of changing the scale of observation, and how this affects our understanding of selves at different structural, temporal, and informational scales. The conclusion is that there is no single “best” scale for a self, as this will depend on the scale at which decisions must be made. Different decisions, different scales.