Entangled Life and Code: A Computational Design Taxonomy for Synergistic Bio-Digital Systems

Paper Title

Entangled Life and Code: A Computational Design Taxonomy for Synergistic Bio-Digital Systems ✱

Publication Info

• Topic area: Computational design for bio-digital systems integrating living organisms and digital components.
• Keywords: Bio-digital systems, computational taxonomy, regenerative design, microorganisms, human-computer interaction, biodesign, biological computation, digital interfaces, ecological restoration, hybrid systems.

Background and Problem

• Problem / challenge: Bio-digital systems often constrain living organisms to uni-directional roles (e.g., sensors or actuators) rather than enabling reciprocal computational partnerships. Existing frameworks fail to provide a shared vocabulary bridging biological and computational perspectives.
• Significance: Synergistic bio-digital systems could foster ecological restoration, reduce electronic waste, and enable sustainable computation by leveraging biological adaptability and digital precision.
• Motivation and related work: Prior frameworks in HCI and theoretical biology have explored bio-digital integration but lack actionable guidance for implementing mutualistic computational roles. Current systems often reduce organisms to single-function components, missing their broader computational potential.

Solution

• Proposed approach: A computational design taxonomy for bio-digital systems, comprising eight functional layers: Input, Transduction, Evaluation/Comparison, Routing/Selection, Memory/State, Adaptation, Output, and Power.
• Novelty:
  1. A biologically faithful and computationally actionable taxonomy bridging biology and computing.
  2. Analysis of 70 bio-digital systems using the taxonomy to identify computational roles and gaps.
  3. Creation of an open-source database and interactive visualization platform for exploring bio-digital systems.
  4. Identification of design opportunities for richer, reciprocal bio-digital partnerships.
• Procedure and key techniques:
  • Formulation of taxonomy based on principles from information processing theory, cybernetics, and computer architecture.
  • Coding and analysis of bio-digital systems using the taxonomy to identify computational roles, spatial and temporal characteristics, and organism-digital interactions.
  • Development of an interactive visualization platform to reveal patterns and gaps in bio-digital system design.

Results

• Concrete findings:
  • 49% of systems use organisms for transduction, while advanced roles like memory (2 systems) and adaptation (1 system) are rare.
  • Digital components predominantly serve as input providers (50%) or output translators (39%), with limited support for biological computation.
  • Biological outputs cluster around electrical signals (36%), movement (27%), and growth (27%), with chemical outputs underutilized (3 systems).
• Advantage over baselines: The taxonomy decomposes broad computational concepts into actionable layers, revealing underexplored roles and enabling systematic design of synergistic bio-digital systems.
• Experiments / evaluation:
  • Dataset: 70 microorganism-based bio-digital systems collected from academic databases, review papers, books, and portfolios.
  • Metrics: Computational roles, spatial and temporal characteristics, organism-digital interactions.
  • Visualization: Sankey diagrams highlighting dense and sparse areas in bio-digital system design.
• Limitations and future work:
  • Current taxonomy may constrain exploration of uniquely biological mechanisms without digital analogues.
  • Applicability to plant-based systems and larger ecological scales remains unexplored.
  • Future iterations should incorporate ethical dimensions like organismal agency and consent.

Summary

This paper introduces a computational design taxonomy for bio-digital systems, enabling systematic exploration of computational roles for biological and digital components. Analysis of 70 systems reveals asymmetries in organism-digital partnerships and underutilized biological capabilities, such as memory and adaptation. The taxonomy and accompanying visualization platform highlight design opportunities for richer, reciprocal bio-digital systems that align with regenerative design principles. Future work aims to refine the taxonomy, expand its applicability, and address ethical considerations in bio-digital system design.