Skip to main content
SpringerLink
Log in

Co-creative Product Design with Interactive Evolutionary Algorithms: A Practice-Based Reflection

  • Conference paper
  • First Online:
Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13221))

Abstract

Progress in AI has brought about new approaches for designing products via co-creative human–computer interaction. In architecture, interior design, and industrial design, computational methods such as evolutionary algorithms support the designer’s creative process by revealing populations of generated design solutions in a parametric design space. However, the benefits and shortcomings of such algorithms for designers are not yet fully understood. This paper reports the in-depth, in-situ and longitudinal experiences of one industrial designer using an interactive evolutionary algorithm in a non-trivial creative product design task. Our study sheds light on the intricate interaction between algorithm, human designer and their environment. It identifies, amongst others, the algorithm’s contributions to design inspiration and to overcoming fixation. We contribute concrete proposals for the future study of co-creative AI in design exploration and creative practice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alcaide-Marzal, J., Diego-Mas, J.A., Acosta-Zazueta, G.: A 3D shape generative method for aesthetic product design. Design Stud. 66, 144–176 (2019)

    Article  Google Scholar 

  2. Ang, M.C., Chau, H.H., McKay, A., De Pennington, A.: Combining evolutionary algorithms and shape grammars to generate branded product design. In: Proceedings of the Design Computing and Cognition, pp. 521–539 (2006)

    Google Scholar 

  3. Banerjee, A., Quiroz, J.C., Louis, S.: A model of creative design using collaborative interactive genetic algorithms. In: Proceedings of the Design Computing and Cognition, pp. 397–416 (2008)

    Google Scholar 

  4. Bernal, M., Haymaker, J.R., Eastman, C.: On the role of computational support for designers in action. Design Stud. 41, 163–182 (2015)

    Article  Google Scholar 

  5. Boden, M.A.: Creative Mind: Myths and Mechanisms, 2 edn. Routledge (2004)

    Google Scholar 

  6. Bonham, C.R., Parmee, I.C.: An investigation of exploration and exploitation within cluster oriented genetic algorithms (COGAs). In: Proceedings of the Conference on Genetic and Evolutionary Computation, pp. 1491–1497 (1999)

    Google Scholar 

  7. Chang, Y.S., Chien, Y.H., Lin, H.C., Chen, M.Y., Hsieh, H.H.: Effects of 3D CAD applications on the design creativity of students with different representational abilities. Comput. Hum. Behav. 65, 107–113 (2016)

    Article  Google Scholar 

  8. Cluzel, F., Yannou, B., Dihlmann, M.: Using evolutionary design to interactively sketch car silhouettes and stimulate designer’s creativity. Eng. Appl. Artif. Intell. 25(7), 1413–1424 (2012)

    Article  Google Scholar 

  9. Crilly, N.: The evolution of “co-evolution" (Part I): problem solving, problem finding, and their interaction in design and other creative practices. She Ji: J. Design Econ. Innov. 7(3), 309–332 (2021)

    Google Scholar 

  10. Dabbeeru, M.M., Mukerjee, A.: Discovering implicit constraints in design. In: Proceedings of the Design Computing and Cognition, pp. 201–220 (2008)

    Google Scholar 

  11. Darke, J.: The primary generator and the design process. Design Stud. 1(1), 36–44 (1979)

    Article  Google Scholar 

  12. Dorst, K.: The core of ‘design thinking’ and its application. Design Stud. 32(6), 521–532 (2011)

    Article  Google Scholar 

  13. Dorst, K., Cross, N.: Creativity in the design process: co-evolution of problem-solution. Design Stud. 22(5), 425–437 (2001)

    Article  Google Scholar 

  14. Frich, J., MacDonald Vermeulen, L., Remy, C., Biskjaer, M.M., Dalsgaard, P.: Mapping the landscape of creativity support tools in HCI. In: Proceedings of the Conference on Human Factors in Computing Systems, pp. 1–18 (2019)

    Google Scholar 

  15. Gong, D.W., Hao, G.S., Zhou, Y., Sun, X.Y.: Interactive genetic algorithms with multi-population adaptive hierarchy and their application in fashion design. Appl. Math. Comput. 185(2), 1098–1108 (2007)

    Article  Google Scholar 

  16. Grasshopper. https://www.grasshopper3d.com/. Accessed 22 Mar 2021

  17. Halskov, K., Lundqvist, C.: Filtering and informing the design space: towards design-space thinking. ACM Trans. Comput. Hum. Interact. 28(1), 1–28 (2021)

    Article  Google Scholar 

  18. Harding, J., Brandt-Olsen, C.: Biomorpher: interactive evolution for parametric design. Int. J. Architect. Comput. 16(2), 144–163 (2018)

    Article  Google Scholar 

  19. Howard, T.J., Culley, S.J., Dekoninck, E.: Describing the creative design process by the integration of engineering design and cognitive psychology literature. Design Stud. 29(2), 160–180 (2008)

    Article  Google Scholar 

  20. Isley, C.G., Rider, T.: Research-through-design: exploring a design-based research paradigm through its ontology, epistemology, and methodology. In: Proceedings of the Design as a Catalyst for Change - DRS International Conference, pp. 358–368 (2018)

    Google Scholar 

  21. Kantosalo, A., Toivonen, H.: Modes for creative human-computer collaboration: alternating and task-divided co-creativity. In: Proceedings of the International Conference on Computational Creativity, pp. 77–84 (2016)

    Google Scholar 

  22. Kielarova, S.W., Sansri, S.: Shape optimization in product design using interactive genetic algorithm integrated with multi-objective optimization. In: Proceedings of the International Workshop on Multi-disciplinary Trends in Artificial Intelligence, pp. 76–86 (2016)

    Google Scholar 

  23. Koskinen, I., Krogh, P.G.: Design accountability: when design research entangles theory and practice. Int. J. Design 9(1), 121–127 (2015)

    Google Scholar 

  24. Krish, S.: A practical generative design method. Comput. Aided Design Appl. 43(1), 88–100 (2011)

    Article  Google Scholar 

  25. Lee, H.C., Tang, M.X.: Generating stylistically consistent product form designs using interactive evolutionary parametric shape grammars. In: Proceedings of the International Conference on Computer-Aided Industrial Design and Conceptual Design (2006)

    Google Scholar 

  26. Liu, H., Tang, M., Frazer, J.H.: Supporting creative design in a visual evolutionary computing environment. Adv. Eng. Softw. 35(5), 261–271 (2004)

    Article  Google Scholar 

  27. Lo, C.H., Ko, Y.C., Hsiao, S.W.: A study that applies aesthetic theory and genetic algorithms to product form optimization. Adv. Eng. Inf. 29(3), 662–679 (2015)

    Article  Google Scholar 

  28. Maréchal, G.: Autoethnography. In: Mills, A.J., Durepos, G., Wiebe, E. (eds.) Encyclopedia of Case Study Research, pp. 34–45. Sage (2010)

    Google Scholar 

  29. Mitchell, W.J.: Constructing complexity. In: Martens, B., Brown, A. (eds.) Proceedings of the International Computer Aided Architectural Design Futures Conference, pp. 41–50 (2005)

    Google Scholar 

  30. Murphy, P.: Design research: aesthetic epistemology and explanatory knowledge. She Ji: J. Design Econ. Innov. 3(2), 117–132 (2017)

    Google Scholar 

  31. Pedgley, O.: Capturing and analysing own design activity. Design Stud. 28(5), 463–483 (2007)

    Article  Google Scholar 

  32. Ralph, P., Wand, Y.: A proposal for a formal definition of the design concept. In: Lyytinen, K., Loucopoulos, P., Mylopoulos, J., Robinson, B. (eds.) Design Requirements Engineering: A Ten-Year Perspective. LNBIP, vol. 14, pp. 103–136. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-540-92966-6_6

  33. Renner, G., Ekárt, A.: Genetic algorithms in computer aided-design. Comput. Aided Design Appl. 35(8), 709–726 (2003)

    Article  Google Scholar 

  34. Rhinoceros3D. www.rhino3d.com. Accessed 22 Mar 2021

  35. Rittel, H.W., Webber, M.M.: Dilemmas in a general theory of planning. Policy Sci. 4(2), 155–169 (1973)

    Article  Google Scholar 

  36. Robertson, B.F., Radcliffe, D.F.: Impact of CAD tools on creative problem solving in engineering design. Comput. Aided Design Appl. 41(3), 136–146 (2009)

    Article  Google Scholar 

  37. Schön, D.A.: Reflective Practitioner. Basic Books, New York (1983)

    Google Scholar 

  38. Schön, D.A.: Designing as a reflective conversation with the materials of a design situation. Knowl. Based Syst. 5(1), 3–14 (1992)

    Article  Google Scholar 

  39. Sharrock, W., Anderson, B.: Organizational innovation and the articulation of the design space. In: Moran, T.P., Carroll, J.M. (eds.) Design Rationale, chap. 15, pp. 429–451. CRC Press (1996)

    Google Scholar 

  40. Simon, H.A.: The Sciences of the Artificial. MIT Press (1969)

    Google Scholar 

  41. Singh, D., Rajcic, N., Colton, S., McCormack, J.: Camera obscurer: generative art for design inspiration. In: Ekárt, A., Liapis, A., Castro Pena, M.L. (eds.) EvoMUSART 2019. LNCS, vol. 11453, pp. 51–68. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-16667-0_4

  42. Su, J., Zhang, S.: Research on product shape innovation design method with human-computer interaction through genetic algorithm. In: Proceedings of the International Conference Computer-Aided Industrial Design & Conceptual Design, pp. 301–305 (2010)

    Google Scholar 

  43. Tabatabaei Anaraki, N.A.: Fashion design aid system with application of interactive genetic algorithms. In: Correia, J., Ciesielski, V., Liapis, A. (eds.) EvoMUSART 2017. LNCS, vol. 10198, pp. 289–303. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-55750-2_20

    Chapter  Google Scholar 

  44. Wang, Y., Ma, H.S., Yang, J.H., Wang, K.S.: Industry 4.0: a way from mass customization to mass personalization production. Adv. Manuf. 5(4), 311–320 (2017)

    Article  Google Scholar 

  45. Woodbury, R.F., Burrow, A.L.: Whither design space? Artif. Intell. Eng. Design Anal. Manuf. 20(2), 63–82 (2006)

    Article  Google Scholar 

  46. Xue, H., Desmet, P.M.A.: Researcher introspection for experience-driven design research. Design Stud. 63, 37–64 (2019)

    Article  Google Scholar 

  47. Zimmerman, J., Forlizzi, J., Evenson, S.: Research through design as a method for interaction design research in HCI. In: Proceedings of the Conference on Human Factors in Computing Systems, pp. 493–502 (2007)

    Google Scholar 

Download references

Acknowledgments

Many thanks to our anonymous reviewers for their extremely valuable feedback and suggestions for future work. AK has been funded by the Academy of Finland (through grants no. 311090 “Digital Aura” and no. 328729) and TT has been funded by the Academy of Finland (grant no. 311090 “Digital Aura”). CG is funded by the Academy of Finland Flagship programme Finnish Center for Artificial Intelligence (FCAI).

Author information

Authors and Affiliations

  1. Department of Design, Aalto University, Espoo, Finland

    Severi Uusitalo & Antti Salovaara

  2. Department of Computer Science, University of Helsinki, Helsinki, Finland

    Anna Kantosalo

  3. Department of Computer Science, Aalto University, Espoo, Finland

    Anna Kantosalo, Tapio Takala & Christian Guckelsberger

  4. School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK

    Christian Guckelsberger

  5. Finnish Center for Artificial Intelligence, Helsinki, Finland

    Christian Guckelsberger

Authors
  1. Severi Uusitalo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anna Kantosalo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Antti Salovaara
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tapio Takala
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Christian Guckelsberger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Severi Uusitalo .

Editor information

Editors and Affiliations

  1. University of Coimbra, Coimbra, Portugal

    Tiago Martins

  2. University of A Coruña, A Coruña, Spain

    Nereida Rodríguez-Fernández

  3. University of Coimbra, Coimbra, Portugal

    Sérgio M. Rebelo

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Uusitalo, S., Kantosalo, A., Salovaara, A., Takala, T., Guckelsberger, C. (2022). Co-creative Product Design with Interactive Evolutionary Algorithms: A Practice-Based Reflection. In: Martins, T., Rodríguez-Fernández, N., Rebelo, S.M. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2022. Lecture Notes in Computer Science, vol 13221. Springer, Cham. https://doi.org/10.1007/978-3-031-03789-4_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-03789-4_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-03788-7

  • Online ISBN: 978-3-031-03789-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation