Abstract
Org(SB-EAI) was a transdisciplinary theoretical project investigating a novel approach to Embodied Artificial Intelligence (EAI) by integrating cognitive models developed within EAI with conceptual and methodological resources drawn from Synthetic Biology (SB). Its central thesis is that biological organization—rather than bodily morphology or material composition alone—plays the decisive role in the emergence and functioning of cognitive processes. This stance directly addresses recognized limitations in current EAI research, which has tended to emphasize superficial bodily features (sensorimotor coupling, morphological computation) while remaining tied to conventional hardware–software paradigms of cognition. In contrast, Org(SB-EAI) proposed an organizational perspective grounded in wetware chemical models, seeking to root artificial cognition in biologically inspired principles such as metabolic self-production, self-maintenance, and autopoietic organization. The ambition was to articulate deeper and more biologically realistic models of artificial cognition, with implications extending toward minimal forms of EAI and future biotechnological applications. The project was entirely theoretical, with no experimental component foreseen or undertaken. Its methodology was grounded in the epistemology of the artificial, the history of complex and systemic thought, and the philosophy of mind and of life. Within this framework, the project critically examined how artificial cognitive systems are conceptualized, modeled, and interpreted, paying particular attention to the epistemic and conceptual boundaries—and potential points of continuity—between natural and artificial cognition. This involved a sustained engagement with foundational questions about what counts as cognition, how organizational closure and biological self-production relate to information-processing accounts of mind, and how concepts native to one explanatory tradition (e.g., autopoiesis, metabolism, chemical self-organization) might be meaningfully translated into the vocabulary of another (e.g., embodiment, computation, robotics). A defining feature of Org(SB-EAI) was its intrinsic transdisciplinarity, treated not as an incidental feature but as a methodological necessity dictated by the complexity of its object of study. The project brought together philosophy, synthetic biology, and embodied artificial intelligence. The research proceeded through in-depth conceptual analysis and theoretical exploration, with the primary objective of constructing a shared conceptual plane and a common language capable of translating ideas across disciplinary boundaries. The intended output was a set of guiding principles, a coherent theoretical framework, and a reference vocabulary designed to orient and inform future research at the intersection of synthetic biology and embodied AI. Org(SB-EAI) positions itself as a foundational, agenda-setting contribution intended to shape and guide subsequent interdisciplinary research. Results The project's results form a coherent four-part body of work, each objective yielding distinct, substantive outputs that build cumulatively toward a complete theoretical-to-applicative architecture for wetware-based cognition. The principal result of Objective 1 is a fully articulated theoretical and methodological framework for wetware-based artificial cognition, grounded in Varelian autonomy and developed through what the project calls the WNAI paradigm. Concretely, this yielded the definition of two implementable system types—target systems and evolver systems—conceived as tractable models of autonomous chemical cognition rather than purely abstract constructs. A further substantive result was the formalization of chemical cognitive systems as networks of processes possessing specific organizational properties, namely coupling, self-regulation, and closure of dependencies, which gives the abstract notion of autonomy a precise, analyzable structure. The objective also produced an explicit comparative analysis contrasting computationalist and constructivist approaches to chemical AI, clarifying their divergent assumptions, and it culminated in the design of implementable architectures compatible with current synthetic biology constraints. Collectively, these results constitute the conceptual and architectural foundation of the entire project, successfully transitioning abstract models of autopoiesis into experimentally tractable forms of autonomous wetware systems. Objective 2 produced a structured framework oriented toward the future chemical implementation of wetware systems, and its results are notably concrete and technically detailed. These include a classification of Chemical AI across three distinct organizational levels, providing a systematic taxonomy where none previously existed; a bottom-up synthetic-cell primer cataloguing relevant technologies, material constraints, and theoretical models; a combined theoretical and simulation-based account establishing noise as a constructive resource for system function rather than mere disturbance; and a preliminary situated model capturing synthetic cell-environment interaction. These outputs were further operationalized into concrete deliverables: comparative conceptual maps and tables specifying the distinctive properties of wetware as a cognitive substrate; explicit identification of implementation variables critical to synthetic cell construction and stability, including membrane functionalization, co-encapsulation, internal network design, energetic regime, and module integration; a set of simulation-supported design principles for adaptive systems covering multilevel organization, openness, redundancy and degeneracy, near-critical operation, and intrinsic incompleteness; and a tractable in silico scenario enabling system-environment coupling and internal adaptive dynamics to be analyzed through information-theoretic metrics. These results collectively provide the technical-conceptual bridge between the theoretical framework of Objective 1 and the evaluative framework of Objective 3. Objective 3 yielded a structured epistemological framework for evaluating the relevance of wetware models, with results organized across three levels. The first major result is the definition of relevance criteria themselves, distinguishing phenomenological relevance from organizational relevance as complementary evaluative dimensions. The second is the specification of autonomy as the criterion of organizational relevance for minimal wetware cognition, directly extending the theoretical apparatus of Objective 1 into evaluative territory. The third is a system-level reformulation incorporating sustainability and ethical implications, which allows concrete wetware modelling scenarios from Objective 2 to actually be assessed rather than merely described. These results were operationalized into a clear distinction between phenomenological and organizational relevance; into autonomy and organizational closure as defining criteria for cognitively relevant organization; into specific operational indicators for minimal chemical cognition, including persistence under perturbation, adaptive modulation, and identity maintenance; and into an extended evaluative scope covering system-level sustainability and viability. Taken together, this constitutes the evaluative core of the project, establishing for the first time clear, operational conditions under which wetware models can be judged to contribute meaningfully to the scientific understanding of life and cognition. Objective 4 produced the project's applicative results, structured once again across three levels. The first is the definition of a concrete applicative domain, smart drug delivery, situating autonomous wetware systems within a specific and practically significant technological context. The second is a reinterpretation of function itself in terms of autonomy, yielding the substantive theoretical distinction between heteronomous and autonomous systems, a result that reframes how functionality is understood for wetware technologies generally. The third is a system-level extension of applicability that identifies concrete conditions for integration, sustainability, and ethical evaluation. These results were operationalized into an autonomy-based specification of applicability; into identified system-level conditions including maintainability, infrastructural openness, and distributed regulation; into an analysis of system integration within extended socio-technical configurations; and into evaluative guidelines grounded in systemic viability rather than isolated performance metrics. The result is a translation of the project's theoretical models into actionable guidelines for real-world implementation, completing the project's progression from foundational theory through technical modelling and evaluation to responsible applicative guidance for autonomous wetware systems.
Dettagli del progetto
Responsabile scientifico: Andrea Roli
Strutture Unibo coinvolte:
Dipartimento di Informatica - Scienza e Ingegneria
Coordinatore:
Università del Salento(Italy)
Contributo totale Unibo: Euro (EUR) 19.077,00
Durata del progetto in mesi: 28
Data di inizio
05/10/2023
Data di fine:
28/02/2026
