Nothing Special   »   [go: up one dir, main page]

Skip to main content

Investigating Trust Perceptions Toward AI in Industrial Designers

  • Conference paper
  • First Online:
Digital Interaction and Machine Intelligence (MIDI 2023)

Abstract

AI is increasingly present in creative industries, including industrial design. However, there is insufficient understanding of professionals’ perceptions of such tools. This knowledge is crucial for fostering adoption and trust in technology. The article explores designers’ perceptions and trust in these tools and examines the possibilities for integration and collaboration. It employs a mixed-methods explanatory sequential approach to investigate these professionals’ trust in AI during the creative stages of New Product Development (NPD), such as sketching and rendering. The results reveal designers’ limited trust in AI tools, influenced equally by their perceptions of the artifacts’ risk, competency, and benevolence. Participants envisioned AI as a future adjunct to their toolkit, pinpointing ethics, transparency, tool control, and efficiency as areas for improvement. The study offers insights into fostering trust and presents design recommendations for future AI-enabled applications in industrial design. It sheds light on AI’s potential as a creative partner, underlining the need for ethical and transparent integration.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 179.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
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

Similar content being viewed by others

References

  1. Abdalla, S.B., Rashid, M., Ara, D.R.: Plausibility of CAAD in conceptual design: challenges in architectural engineering for early-stage digital design tools. J. Archit. Eng. 27(2) (2021). https://doi.org/10.1061/(asce)ae.1943-5568.0000457

  2. Anantrasirichai, N., Bull, D.: Artificial intelligence in the creative industries: a review. Artif. Intell. Rev. 55(1), 589–656 (2022). https://doi.org/10.1007/s10462-021-10039-7

    Article  Google Scholar 

  3. Arias-Rosales, A.: The perceived value of human-AI collaboration in early shape exploration: an exploratory assessment. PLoS One 17(9 September) (2022). https://doi.org/10.1371/journal.pone.0274496

  4. Bach, T.A., Khan, A., Hallock, H., Beltrão, G., Sousa, S.: A systematic literature review of user trust in AI-enabled systems: an HCI perspective. Int. J. Hum.-Comput. Interact. 1–16 (2022). https://doi.org/10.1080/10447318.2022.2138826

  5. Boni, M.: The ethical dimension of human-artificial intelligence collaboration. Eur. View 20(2), 182–190 (2021). https://doi.org/10.1177/17816858211059249

  6. Caldwell, C., Clapham, S.E.: Organizational trustworthiness: an international perspective. J. Bus. Ethics 47, 349–364 (2003). https://doi.org/10.1023/A:1027370104302

    Article  Google Scholar 

  7. Creswell, J.W.: Research Design, 4th edn. SAGE Publications Inc., Thousand Oaks (2014)

    Google Scholar 

  8. Das, A., Rad, P.: Opportunities and challenges in explainable artificial intelligence (XAI): a survey (2020). http://arxiv.org/abs/2006.11371

  9. Dwivedi, Y.K., et al.: Artificial intelligence (AI): multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manage. 57 (2021). https://doi.org/10.1016/j.ijinfomgt.2019.08.002

  10. Figoli, F.A.: Artificial intelligence in the design process the impact on creativity and team collaboration. FrancoAngeli (2022)

    Google Scholar 

  11. Glikson, E., Woolley, A.W.: Human trust in artificial intelligence: review of empirical research. Academy of Management Annals (in press) The Bright Side of Social Categorization: The Role of Global Identity in Reducing Relational Conflict in Multicultural Teams View project AI-human interaction View project. Technical report (2020). https://www.researchgate.net/publication/340605601

  12. Guest, G., Namey, E., Chen, M.: A simple method to assess and report thematic saturation in qualitative research. PLoS One 15(5) (2020). https://doi.org/10.1371/journal.pone.0232076

  13. Gulati, S., Sousa, S., Lamas, D.: Design, development and evaluation of a human-computer trust scale. Behav. Inf. Technol. 38(10), 1004–1015 (2019). https://doi.org/10.1080/0144929X.2019.1656779

    Article  Google Scholar 

  14. Hayat, A., Shahare, V., Sharma, A.K., Arora, N.: Introduction to industry 4.0. In: Namasudra, S., Akkaya, K. (eds.) Blockchain and its Applications in Industry 4.0. Studies in Big Data, vol 119, pp. 29–59. Springer, Cham (2023). https://doi.org/10.1007/978-981-19-8730-4_2

  15. Jacovi, A., Marasović, A., Miller, T., Goldberg, Y.: Formalizing trust in artificial intelligence: prerequisites, causes and goals of human trust in AI. In: FAccT 2021 - Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, pp. 624–635. Association for Computing Machinery, Inc. (2021). https://doi.org/10.1145/3442188.3445923

  16. Kazi, R.H., Grossman, T., Cheong, H., Hashemi, A., Fitzmaurice, G.: DreamSketch: early stage 3D design explorations with sketching and generative design. In: UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, pp. 401–414. Association for Computing Machinery, Inc. (2017). https://doi.org/10.1145/3126594.3126662

  17. Koch, C.H.W.: The future of industrial design and its role in industry 4.0 (2022). https://doi.org/10.13140/RG.2.2.15506.32969, https://www.researchgate.net/publication/362321819

  18. Krahe, C., Iberl, M., Jacob, A., Lanza, G.: AI-based computer aided engineering for automated product design - a first approach with a Multi-View based classification. In: Procedia CIRP, vol. 86, pp. 104–109. Elsevier B.V. (2020). https://doi.org/10.1016/j.procir.2020.01.038

  19. Kuys, B., Koch, C., Renda, G.: The priority given to sustainability by industrial designers within an industry 4.0 paradigm. Sustain. (Switz.) 14(1) (2022). https://doi.org/10.3390/su14010076

  20. Malamin, B.: Chapter 8. Attitudes of graphic designers and copywriters in Bulgaria towards artificial intelligence. Technical report (2022). https://www.mckinsey.com/featured-

  21. Mcnight, D.H., Carter, M., Thatcher, J.B.: Trust in a specific technology: an investigation of its components and measures. ACM Trans. Manage. Inf. Syst. (TMIS) 2(2), 1–25 (2011)

    Article  Google Scholar 

  22. Nazaretsky, T., Cukurova, M., Alexandron, G.: An instrument for measuring teachers’ trust in AI-based educational technology. In: ACM International Conference Proceeding Series, pp. 56–66. Association for Computing Machinery (2022). https://doi.org/10.1145/3506860.3506866

  23. Pallant, J.: SPSS survival manual. Technical report (2010). www.openup.co.uk/spss

  24. Paramonova, I., Sousa, S., Lamas, D.: Exploring factors affecting user perception of trustworthiness in advanced technology: preliminary results. In: Zaphiris, P., Ioannou, A. (eds.) HCII 2023. LNCS, vol. 14040, pp. 366–383. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-34411-4_25

    Chapter  Google Scholar 

  25. Tatipala, S., Larsson, T., Johansson, C., Wall, J.: The influence of industry 4.0 on product design and development: conceptual foundations and literature review. In: Chakrabarti, A., Poovaiah, R., Bokil, P., Kant, V. (eds.) Design for Tomorrow—Volume 2. Smart Innovation, Systems and Technologies, vol. 222, pp. 757–768. Springer, Cham (2021). https://doi.org/10.1007/978-981-16-0119-4_61

  26. Trakadas, P., et al.: An artificial intelligence-based collaboration approach in industrial IoT manufacturing: key concepts, architectural extensions and potential applications. Sens. (Switzer.) 20(19), 1–20 (2020). https://doi.org/10.3390/s20195480

    Article  Google Scholar 

  27. Tsang, Y.P., Lee, C.K.: Artificial intelligence in industrial design: a semi-automated literature survey (2022). https://doi.org/10.1016/j.engappai.2022.104884

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yana Klimava .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 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

Klimava, Y., Beltrão, G., Paramonova, I. (2024). Investigating Trust Perceptions Toward AI in Industrial Designers. In: Biele, C., et al. Digital Interaction and Machine Intelligence. MIDI 2023. Lecture Notes in Networks and Systems, vol 1076. Springer, Cham. https://doi.org/10.1007/978-3-031-66594-3_20

Download citation

Publish with us

Policies and ethics