Design of speculative artifacts: Integrating generative artificial intelligence, biomaterials, and digital fabrication in co-creative and participatory design

Abstract

This study explores artificial intelligence (AI)-mediated participatory design integrating biomaterials and digital fabrication to co-create speculative artifacts grounded in lived experiences. The present study involves experimentation with biomaterials, exploring the intersection of image-based generative AI, participatory, and co-creative methodologies within a design framework that reimagines lived experiences shaped by identity-based exclusionary processes. Rather than pursuing AI-driven discovery of new materials, this study positions design as a mediating process among human experience, critical reflection, biomaterial exploration, and digital fabrication. The research introduces a three-stage workflow (co-creation, fabrication, and materialization) that employs AI as a mediating tool between subjective narratives and tangible speculative artifacts. During the co-creation stage, participants shared their personal experiences through open-ended surveys, text-to-image generative AI visualization, and algorithmic three-dimensional (3D) modeling. This process enabled participants to speculatively reimagine lived experiences of social exclusion, demonstrating how AI can support new modes of participatory and social engagement. During the fabrication stage, digital models were translated into physical counter-molds through 3D printing and subsequently cast in silicon, reaffirming the reciprocal relationship between digital and craft-based production. The materialization stage explored biomaterial compositions informed by participants’ narratives and materialities, incorporating hair, wood ash, and plastic waste into biomaterial compositions grounded in circular economy principles. The resulting artifacts function as speculative objects that incite interpretation beyond fixed symbolic representation. This study contributes to ongoing discussions in digital fabrication, material design, and critical craft by demonstrating how AI-mediated participatory co-creation can foster ethically conscious, socially engaged, and materially grounded design practices. Future work may extend this approach to larger collective settings and further explore the integration of biomaterials and AI within ecological and inclusive design frameworks.

Keywords

Artificial intelligence / Biomaterials / Co-creative design / Participatory design / Three-dimensional printing / Artifact-based design research

Acknowledgments

The authors express their gratitude to the Associate Laboratory of Energy, Transport, and Aerospace (LAETA) and the Institute of Science and Innovation in Mechanical and Industrial Engineering (INEGI), whose resources were essential for the development of this work.

Funding

None.

Conflict of interest

The authors declare that they have no competing interests.

Author contributions

Conceptualization: Guilherme Giantini

Data curation: Guilherme Giantini

Investigation: All authors

Methodology: All authors

Project administration: All authors

Resources: Lígia Lopes, Jorge Lino Alves

Supervision: Lígia Lopes, Jorge Lino Alves

Validation: Lígia Lopes

Visualization: Guilherme Giantini

Writing-original draft: All authors

Writing-review & editing: All authors

Ethics approval and consent to participate

No specific ethical approval was required for this study, as the master’s committee responsible for reviewing the original research determined that the survey’s statement would sufficiently cover participants’ consent. Permission was obtained from participants in written format. By participating in the anonymized survey, participants agreed to provide and grant permission for the use of their shared data. These data are limited to subjective information (i.e., subjective perceptions, opinions, and claims).

Consent for publication

By participating in the anonymized survey, the participants granted their permission for the use of their shared subjective data, which includes publication for scientific and artistic purposes.

Availability of data

The original data presented in this study are openly accessible in Repositório Aberto da Universidade do Porto at https://hdl.handle.net/10216/164287.

Further disclosure

This is the first English-language version of this work. The research underpinning this paper was originally presented in a Portuguese-language master’s level thesis (December 2024), which is available at https://hdl.handle.net/10216/164287.

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