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CO-DESIGNING TECHNOLOGICAL EXPLORATIONS IN DEVELOPING FUTURES LITERACY THROUGH SPECULATIVE DESIGN AND AN ARTISTIC INTERVENTION

Published online by Cambridge University Press:  19 June 2023

Álvaro Aranda Muñoz ,
Nina Bozic Yams  and
Lisa Carlgren
Álvaro Aranda Muñoz*
Affiliation:
Mälardalen University; RISE - Research Institutes of Sweden
Nina Bozic Yams
Affiliation:
RISE - Research Institutes of Sweden
Lisa Carlgren
Affiliation:
RISE - Research Institutes of Sweden
*
Aranda Muñoz, Álvaro, Mälardalen University, Sweden, alvaro.aranda.munoz@ri.se

Abstract

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Futures Literacy is the capability to imagine and understand potential futures to prepare ourselves to act and innovate in the present. This pilot study aims to understand how artistic methodologies and speculative design can support the collaborative exploration of futures in the context of work and contribute to developing peoples’ capability of futures literacy. Our premise is that technologies such as Artificial Intelligence and the Internet of things can augment people and support their needs at work. To illustrate this process, we have presented a collaborative method that integrates an artistic intervention with speculative design activities. We tested the method in a full-day workshop with seventeen (17) participants from a Swedish academy responsible for enabling learning and competence development at work in the healthcare sector. The results indicate that the artistic intervention, combined with the speculative design activities, can challenge current participants’ perspectives and offer them new ways of seeing futures with technologies. These new ways of seeing reveal underlying premises crucial in developing the capability of futures literacy.

Keywords

Collaborative designCase studyDesign methodsFutures Literacy
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 957 - 966
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Boer, A. de, Wiekens, C., Damhof, L., 2018. How futures literate are you?: exploratory research on how to operationalize and measure futures literacy. 6th International Conference on Future-Oriented Technology Analysis (FTA), Brussels, Belgium.Google Scholar
Bozic-Yams, N., Aranda-Muñoz, Á., 2021. Poetics of Future Work: Blending Speculative Design with Artistic Methodology, in: CHI’ 21 Extended Abstracts, CHI EA ’21. ACM, New York, NY, USA, pp. 1–8. https://dx.doi.org/10.1145/3411763.3443451Google Scholar
Brandt, E., Binder, T., Sanders, E., 2012. Tools and techniques: Ways to engage telling, making and enacting, in: Simonsen, J., Robertson, T. (Eds.), Routledge International Handbook of Participatory Design. Routledge, pp. 145–181.Google Scholar
Carbonell, J., Sánchez-Esguevillas, A., Carro, B., 2016. The role of metaphors in the development of technologies. The case of the artificial intelligence. Futures 84, 145–153. https://dx.doi.org/10.1016/j.futures.2016.03.019CrossRefGoogle Scholar
Carney, M., Webster, B., Alvarado, I., Phillips, K., Howell, N., Griffith, J., Jongejan, J., Pitaru, A., Chen, A., 2020. Teachable Machine: Approachable Web-Based Tool for Exploring Machine Learning Classification, in: Extended Abstracts of the 2020 CHI EA ’20. Association for Computing Machinery, New York, NY, USA, pp. 1–8. https://dx.doi.org/10.1145/3334480.3382839Google Scholar
Cila, N., Smit, I., Giaccardi, E., Kröse, B., 2017. Products as Agents: Metaphors for Designing the Products of the IoT Age, in: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI ’17. ACM, New York, NY, USA, pp. 448–459. https://dx.doi.org/10.1145/3025453.3025797Google Scholar
Dalsgaard, P., 2017. Instruments of Inquiry: Understanding the Nature and Role of Tools in Design. International Journal of Design 1, 21–33.Google Scholar
Dove, G., Fayard, A.-L., 2020. Monsters, Metaphors, and Machine Learning, in: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI ’20. ACM, New York, NY, USA, pp. 1–17. https://dx.doi.org/10.1145/3313831.3376275Google Scholar
Dove, G., Lundqvist, C.E., Halskov, K., 2018. The Life Cycle of a Generative Design Metaphor, in: Proceedings of the 10th Nordic Conference on Human-Computer Interaction, NordiCHI ’18. Association for Computing Machinery, New York, NY, USA, pp. 414–425. https://doi.org/10.1145/3240167.3240190Google Scholar
Dunne, A., Raby, F., 2013. Speculative Everything: Design, Fiction, and Social Dreaming. The MIT Press.Google Scholar
Elsden, C., Chatting, D., Durrant, A.C., Garbett, A., Nissen, B., Vines, J., Kirk, D.S., 2017. On Speculative Enactments, in: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI ’17. ACM, New York, NY, USA, pp. 5386–5399. https://dx.doi.org/10.1145/3025453.3025503Google Scholar
Ericsson, 2020. Adopting AI in organizations. The journey towards constant change. URL (accessed: 29/11/22): https://www.ericsson.com/en/reports-and-papers/industrylab/reports/adopting-ai-in-organizationsGoogle Scholar
Gartner Glossary., 2022. Future of Work. URL (accessed: 04/03/23): https://www.gartner.com/en/human-resources/glossary/future-of-workGoogle Scholar
Garneij, F. and Hookway, S., 2021. The Heartists Are Present. URL (accessed: 05/03/23): http://studioalight.com/TheHeartistArePresent_en.htmlGoogle Scholar
Grzelec, A., Prata, T., 2013. Artists in organisations - mapping of European producers of artistic interventions in organisations. Creative Clash, Gothemburg.Google Scholar
Hamm, P., Klesel, M., 2021. Success Factors for the Adoption of Artificial Intelligence in Organizations: A Literature Review, in: AMCIS 2021 Proceedings. 10.Google Scholar
Harper, R.H.R., 2019. The Role of HCI in the Age of AI. International Journal of Human–Computer Interaction 35, 1331–1344. https://doi.org/10.1080/10447318.2019.1631527CrossRefGoogle Scholar
Jöhnk, J., Weißert, M., Wyrtki, K., 2020. Ready or Not, AI Comes— An Interview Study of Organizational AI Readiness Factors. Business & Information Systems Engineering 63, 5–20. https://dx.doi.org/10.1007/s12599-020-00676-7Google Scholar
Koski, O., Husso, K., 2018. Work in the age of artificial intelligence: Four perspectives on the economy, employment, skills and ethics. Ministry of Economic Affairs and Employment.Google Scholar
Mattelmäki, T., Brandt, E., Vaajakallio, K., 2011. On designing open-ended interpretations for collaborative design exploration, CoDesign, 7:2, 79–93, https://dx.doi.org/10.1080/15710882.2011.609891CrossRefGoogle Scholar
Miller, R., 2010. Futures Literacy. Embracing Complexity and Using the Future. Ethos, 10, 23–28.Google Scholar
Miller, R., 2018. Transforming the future: Anticipation in the 21st century. Taylor & Francis.Google Scholar
Miller, R., and Tuomi, I., 2022. Making the futures of AI in education: Why and how imagining the future matters. European Journal of Education, 57, 537– 541. https://doi.org/10.1111/ejed.12529CrossRefGoogle Scholar
Nortje, M.A., Grobbelaar, S.S., 2020. A Framework for the Implementation of Artificial Intelligence in Business Enterprises: A Readiness Model 1–10. https://dx.doi.org/10.1109/ice/itmc49519.2020.9198436CrossRefGoogle Scholar
OpenAI, 2022. URL: https://openai.com/ (accessed 29/11/22).Google Scholar
Ossewaarde, M., 2019. Digital transformation and the renewal of social theory: Unpacking the new fraudulent myths and misplaced metaphors. Technol Forecast Soc 146, 24–30. https://dx.doi.org/10.1016/j.techfore.2019.05.007CrossRefGoogle Scholar
Sanders, E.B.-N., Brandt, E., Binder, T., 2010. A Framework for Organizing the Tools and Techniques of Participatory Design, in: Proceedings of the 11th Biennial Participatory Design Conference, PDC ’10. ACM, New York, NY, USA, pp. 195–198. https://dx.doi.org/10.1145/1900441.1900476Google Scholar
Schön, D.A., 1992. Designing as reflective conversation with the materials of a design situation. Research in Engineering Design 3, 131–147 https://dx.doi.org/10.1007/BF01580516CrossRefGoogle Scholar
Schön, D.A., 1993. Generative metaphor: A perspective on problem-setting in social policy, in: Cambridge Core. Cambridge University Press, Cambridge, pp. 137–163. https://dx.doi.org/10.1017/cbo9781139173865.011Google Scholar
Simonsen, J., Robertson, T., 2012. Routledge International Handbook of Participatory Design. Routledge.CrossRefGoogle Scholar
Sköldberg, U.J., Woodilla, J., 2013. Arguing for design thinking interventions as a form of artistic interventions. Swedish Design Research Journal 10, 40–47. https://dx.doi.org/10.3384/svid.2000-964X.13240CrossRefGoogle Scholar
UNESCO, 2014. Networking to improve global/local anticipatory capacities, a scoping exercise: narrative report.Google Scholar
Wang, W., and Siau, K., 2019. Artificial Intelligence, Machine Learning, Automation, Robotics, Future of Work and Future of Humanity: A Review and Research Agenda. JDM vol.30, no.1 2019: pp. 61–79. http://doi.org/10.4018/JDM.2019010104Google Scholar
World Economic Forum, 2020. The Future of Jobs Report 2020.Google Scholar