User experience design and sustainability of AI-infused objects
DOI:
https://doi.org/10.19229/2464-9309/13222023Keywords:
user experience, design, sustainability, artificial intelligence, internet of thingsAbstract
AI-infused objects have become an integral part of the daily lives of an increasing number of users. While these objects offer undeniable benefits, they also raise concerns due to their environmental impact. This paper explores the characteristics of these objects and the ecosystem they create, presenting an interpretive model that examines three primary components: physical, digital, and usage. When it comes to ‘sustainability’, Design generally focuses on environmental impacts related to the physical component, while Engineering evaluates the impacts of the digital component. However, these assessments are often disconnected and fail to encompass the impacts associated with usage. The proposed approach seeks to integrate diverse methodologies to elicit the impacts related to the user experience and generate greater awareness already in the design phase.
Article info
Received: 04/04/2023; Revised: 02/05/2023; Accepted: 09/05/2023
Downloads
Article Metrics Graph
References
Abramovici, M. (2019), “Smart products”, in Chatti, S., Laperrière, L., Reinhart, G. and Tolio, T. (eds), CIRP Encyclopedia of Production Engineering, Springer Berlin, Heidelberg. [Online] Available at: doi.org/10.1007/978-3-662-53120-4_16785 [Accessed 25 March 2023].
Adaji, I. and Adisa, M. (2022), “A Review of the Use of Persuasive Technologies to Influence Sustainable Behaviour”, in Bellogin, A., Boratto, L., Santos, O. (eds), UMAP ’22 Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery, New York, pp. 317-325. [Online] Available at: doi.org/10.1145/3511047.3537653 [Accessed 25 March 2023].
Anthony, L. F. W., Kanding, B. and Selvan, R. (2020), “Carbontracker – Tracking and Predicting the Carbon Footprint of Training Deep Learning Models”, presented at the ICML Workshop on Challenges in Deploying and Monitoring Machine Learning Systems, pp. 1-11. [Online] Available at: doi.org/10.48550/arXiv.2007.03051 [Accessed 25 March 2023].
Ashri, R. (2020), The AI-Powered Workplace – How Artificial Intelligence, Data, and Messaging Platforms Are Defining the Future of Work, Apress, Berkeley (CA). [Online] Available at: doi.org/10.1007/978-1-4842-5476-9 [Accessed 25 March 2023].
Bannour, N., Ghannay, S., Névéol, A. and Ligozat, A. L. (2021), “Evaluating the carbon footprint of NLP methods – A survey and analysis of existing tools”, in Nafise, S., Moosavi, I. and Gurevych, A. (eds), Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing, Association for Computational Linguistics, pp. 11-21. [Online] Available at: doi.org/10.18653/v1/2021.sustainlp-1.2 [Accessed 25 March 2023].
Bertoni, M. (2017), “Introducing sustainability in value models to support design decision making – A systematic review”, in Sustainability, vol. 9, issue 6, article 994, pp. 1-31. [Online] Available at: doi.org/10.3390/su9060994 [Accessed 25 March 2023].
Bracquené, E., De Bock, Y. and Duflou, J. (2020), “Sustainability impact assessment of an intelligent control system for residential heating”, in Procedia CIRP, vol. 90, pp. 232-237. [Online] Available at: doi.org/10.1016/j.procir.2020.02.007 [Accessed 25 March 2023].
Braungart, M., McDonough, W. and Bollinger, A. (2007), “Cradle-to-cradle design – Creating healthy emissions – A strategy for eco-effective product and system design”, in Journal of Cleaner Production, vol. 15, issues 13-14, pp. 1337-1348. [Online] Available at: doi.org/10.1016/j.jclepro.2006.08.003 [Accessed 25 March 2023].
Budennyy, S., Lazarev, V., Zakharenko, N., Korovin, A., Plosskaya, O., Dimitrov, D., Akhripkin, V. S., Pavlov, I. V., Oseledets, I. V., Barsola, I. S., Egorov, I. V., Kosterina, A. A. and Zhukov, L. E. (2022), “eco2AI – Carbon emissions tracking of machine learning models as the first step towards sustainable AI”, in Doklady Mathematics, vol. 106, pp. 118-128. [Online] Available at: doi.org/10.1134/S1064562422060230 [Accessed 25 March 2023].
Carella, G., Arquilla, V., Zurlo, F. and Tamburello, M. C. (2019), “Phygital experiences design”, in DIID | Disegno Industriale Industrial Design, vol. 67, pp. 128-135. [Online] Available at: re.public.polimi.it/handle/11311/1138184 [Accessed 25 March 2023].
Chapman, J. (2009), “Design for (emotional) durability”, in Design Issues, vol. 25, issue 4, pp. 29-35. [Online] Available at: doi.org/10.1162/desi.2009.25.4.29 [Accessed 25 March 2023].
Charter, M. and Tischner, U. (2001), Sustainable Solutions – Developing Products and Services for the Future, Routledge London. [Online] Available at: doi.org/10.4324/9781351282482 [Accessed 25 March 2023].
Cialdini, R. B. (2009), Influence – Science and practice, Pearson Education, Boston.
Cooper, T. (2004), “Inadequate life? Evidence of consumer attitudes to product obsolescence”, in Journal of Consumer Policy, vol. 27, issue 4, pp. 421-449. [Online] Available at: doi.org/10.1007/s10603-004-2284-6 [Accessed 25 March 2023].
Coroamă, V. C., Bergmark, P., Höjer, M. and Malmodin, J. (2020), “A methodology for assessing the environmental effects induced by ICT services – Part 1 – Single services”, in Chitchyan, R. and Schien, D. (eds), Proceedings of the 7th International Conference on ICT for Sustainability, Association for Computing Machinery, New York, pp. 36-45. [Online] Available at: doi.org/10.1145/3401335.3401716 [Accessed 25 March 2023].
Crawford, K. and Joler, V. (2018), Anatomy of an AI System – The Amazon Echo as an anatomical map of human labor, data and planetary resource, Share Lab and AI Now Institute. [Online] Available at: anatomyof.ai/img/ai-anatomy-publication.pdf [Accessed 25 March 2023].
Epifani, S. (2020), Sostenibilità digitale – Perché la sostenibilità non può fare a meno della transizione digitale, Digital Transformation Institute, Roma. [Online] Available at: attiviamoenergiepositive.it/wp-content/uploads/2020/07/EstrattoPerIlSitoRidotto.pdf [Accessed 25 March 2023].
Fogg, B. J. (2002), “Persuasive technology – Using computers to change what we think and do”, in Ubiquity, vol. 2002, issue December, article 5, pp. 89-120. [Online] Available at: doi.org/10.1145/764008.763957 [Accessed 25 March 2023].
Greengard, S. (2015), The Internet of Things, MIT Press, Cambridge (MA).
Gupta, U., Kim, Y. G., Lee, S., Tse, J., Lee, H.-H. S., Wei, G. Y., Brooks, D. and Wu, C.-J. (2022), “Chasing carbon – The elusive environmental footprint of computing”, in IEEE Micro, vol. 42, issue 4, pp. 37-47. [Online] Available at: doi.org/10.1109/MM.2022.3163226 [Accessed 25 March 2023].
Gutiérrez, C., Garbajosa, J., Diaz, J. and Yagüe, A. (2013), “Providing a Consensus Definition for the Term Smart Product”, in 2013 20th IEEE International Conference and Workshops on Engineering of Computer Based Systems (ECBS), IEEE, pp. 203-211. [Online] Available at: doi.org/10.1109/ECBS.2013.26 [Accessed 25 March 2023].
Hassenzahl, M., Burmester, M. and Koller, F. (2021), “User Experience Is All There Is – Twenty Years of Designing Positive Experiences and Meaningful Technology”, in i-com, vol. 20, issue 3, pp. 197-213. [Online] Available at: doi.org/10.1515/icom-2021-0034 [Accessed 25 March 2023].
Henderson, P., Hu, J., Romoff, J., Brunskill, E., Jurafsky, D. and Pineau, J. (2020), “Towards the systematic reporting of the energy and carbon footprints of machine learning”, in The Journal of Machine Learning Research, vol. 21, issue 1, article 248, pp.10039-10081. [Online] Available at: dl.acm.org/doi/abs/10.5555/3455716.3455964 [Accessed 25 March 2023].
Hermann, M., Pentek, T. and Otto, B. (2016), “Design Principles for Industrie 4.0 Scenarios”, in 2016 49th Hawaii International Conference on System Sciences (HICSS), Koloa (US), pp. 3928-3937. [Online] Available at: doi.org/10.1109/HICSS.2016.488 [Accessed 25 March 2023].
Horner, N. C., Shehabi, A. and Azevedo, I. L. (2016), “Known unknowns – Indirect energy effects of information and communication technology”, in Environmental Research Letters, vol. 11, issue 10, article 103001, pp. 1-20. [Online] Available at: doi.org/10.1088/1748-9326/11/10/103001 [Accessed 25 March 2023].
Kaack, L. H., Donti, P. L., Strubell, E., Kamiya, G., Creutzig, F. and Rolnick, D. (2022), “Aligning artificial intelligence with climate change mitigation”, in Nature Climate Change, vol. 12, issue 6, pp. 518-527. [Online] Available at: doi.org/10.1038/s41558-022-01377-7 [Accessed 25 March 2023].
Kärkkäinen, M., Holmström, J., Främling, K., and Artto, K. (2003), “Intelligent products – A step towards a more effective project delivery chain”, in Computers in industry, vol. 50, issue 2, pp. 141-151. [Online] Available at: doi.org/10.1016/S0166-3615(02)00116-1 [Accessed 25 March 2023].
Lacoste, A., Luccioni, A., Schmidt, V. and Dandres, T. (2019), “Quantifying the Carbon Emissions of Machine Learning”, in arXiv.org. [Online] Available at: doi.org/10.48550/arXiv.1910.09700 [Accessed 25 March 2023].
Ligozat, A. L. and Luccioni, S. (2021), A Practical Guide to Quantifying Carbon Emissions for Machine Learning Researchers and Practitioners, Research Report. [Online] Available at: hal.science/hal-03376391/ [Accessed 25 March 2023].
Ligozat, A. L., Lefèvre, J., Bugeau, A. and Combaz, J. (2022), “Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Life Cycle Assessment of AI Solutions”, in Sustainability, vol. 14, issue 9, article 5172, pp. 1-14. [Online] Available at: doi.org/10.3390/su14095172 [Accessed 25 March 2023].
Maass, W. and Janzen, S. (2007), “Dynamic Product Interfaces – A Key Element for Ambient Shopping Environments”, in Markus, M. L. (ed.), 20th Bled eConference in eMergence – Merging and Emerging Technologies, Processes, and Institutions – Bled, Slovenia, Faculty of Organizational Sciences, pp. 457-470. [Online] Available at: alexandria.unisg.ch/36765 [Accessed 25 March 2023].
Maeda, J. (2019), How to Speak Machine – Computational Thinking for the Rest of Us, Pinguin Random House, New York.
McGovern, G. (2020), World Wide Waste – How Digital Is Killing Our Planet – And What We Can Do About It, Silver Beach.
Meyer, G. G., Främling, K. and Holmström, J. (2009), “Intelligent products – A survey”, in Computers in Industry, vol. 60, issue 3, pp. 137-148. [Online] Available at: doi.org/10.1016/j.compind.2008.12.005 [Accessed 25 March 2023].
Midden, C. and Ham, J. (2018), “Persuasive Technology to Promote Pro-Environmental Behaviour”, in Steg, L. and de Groot, J. (eds), Environmental psychology – An introduction, Wiley Online Library, pp. 283-294. [Online] Available at: doi.org/10.1002/9781119241072.ch28 [Accessed 25 March 2023].
Midden, C. J. H., Kaiser, F. G. and McCalley, L. T. (2007), “Technology’s Four Roles in Understanding Individuals’ Conservation of Natural Resources”, in Journal of Social Issues, vol. 63, issue 1, pp. 155-174. [Online] Available at: doi.org/10.1111/j.1540-4560.2007.00501.x [Accessed 25 March 2023].
Mugge, R. (2007), Product Attachment, PhD Thesis, Technische Universiteit of Delft, the Netherlands. [Online] Available at: resolver.tudelft.nl/uuid:0a7cef79-cb04-4344-abb1-cff24e3c3a78 [Accessed 25 March 2023].
Nishikawa-Pacher, A. (2022), “Research Questions with PICO – A Universal Mnemoni”, in Publications, vol. 10, issue 3, article 21, pp. 1-10. [Online] Available at: doi.org/10.3390/publications10030021 [Accessed 25 March 2023].
Oinas-Kukkonen, H. and Harjumaa, M. (2009), “Persuasive systems design – Key issues, process model, and system features”, in Communications of the Association for Information Systems, vol. 24, article 28, pp. 485-500. [Online] Available at: doi.org/10.17705/1CAIS.02428 [Accessed 25 March 2023].
Pirson, T. and Bol, D. (2021), “Assessing the embodied carbon footprint of IoT edge devices with a bottom-up life-cycle approach”, in Journal of Cleaner Production, vol. 322, article 128966, pp. 1-13. [Online] Available at: doi.org/10.1016/j.jclepro.2021.128966 [Accessed 25 March 2023].
Pohl, J., Frick, V., Finkbeiner, M. and Santarius, T. (2022), “Assessing the environmental performance of ICT-based services – Does user behaviour make all the difference?”, in Sustainable Production and Consumption, vol. 31, pp. 828-838. [Online] Available at: doi.org/10.1016/j.spc.2022.04.003 [Accessed 25 March 2023].
Pohl, J., Hilty, L. M. and Finkbeiner, M. (2019), “How LCA contributes to the environmental assessment of higher order effects of ICT application – A review of different approaches”, in Journal of cleaner production, vol. 219, pp. 698-712. [Online] Available at: doi.org/10.1016/j.jclepro.2019.02.018 [Accessed 25 March 2023].
Ranganathan, P. and Aggarwal, R. (2020), “Study designs – Part 7 – Systematic reviews”, in Perspectives in Clinical Research, vol. 11, issue 2, pp. 97-100. [Online] Available at: pubmed.ncbi.nlm.nih.gov/32670836/ [Accessed 25 March 2023].
Rizwan, A., Rasheed, R., Javed, H., Farid, Q. and Ahmad, S. R. (2022), “Environmental sustainability and life cycle cost analysis of smart versus conventional energy meters in developing countries”, in Sustainable Materials and Technologies, vol. 33, pp. 2-12. [Online] Available at: doi.org/10.1016/j.susmat.2022.e00464 [Accessed 25 March 2023].
Rowland, C., Goodman, E., Charlier, M., Light, A. and Lui, A. (2015), Designing connected products – UX for the consumer Internet of Things, O’Reilly Media. [Online] Available at: dl.acm.org/doi/abs/10.5555/2891121 [Accessed 25 March 2023].
Shehabi, A. (2017), “Data Clouds and the Environment”, in Egenhoefer, R. B. (ed.), Routledge Handbook of Sustainable Design, Routledge, London, pp. 170-178. [Online] Available at: doi.org/10.4324/9781315625508 [Accessed 25 March 2023].
Stermieri, L., Kober, T., Schmidt, T. J., McKenna, R. and Panos, E. (2023), “Quantifying the implications of behavioral changes induced by digitalization on energy transition – A systematic review of methodological approaches”, in Energy Research & Social Science, vol. 97, article 102961, pp. 1-19. [Online] Available at: doi.org/10.1016/j.erss.2023.102961 [Accessed 25 March 2023].
Tukker, A. and Tischner, U. (2006), “Product-services as a research field – Past, present and future – Reflections from a decade of research”, in Journal of Cleaner Production, vol. 14, issue 17, pp. 1552-1556. [Online] Available at: doi.org/10.1016/j.jclepro.2006.01.022 [Accessed 25 March 2023].
Turovsky, B. (2016), “Ten years of Google Translate”, in The Keyword, 28/04/2016. [Online] Available at: blog.google/products/translate/ten-years-of-google-translate [Accessed 25 March 2023].
Vailshery, L. S. (2022), “Number of IoT connected devices worldwide 2019-2021, with forecasts to 2030”, in Statista, 22/11/2022. [Online] Available at: statista.com/statistics/1183457/iot-connected-devices-worldwide [Accessed 25 March 2023].
van Wynsberghe, A. (2021), “Sustainable AI – AI for sustainability and the sustainability of AI”, in AI and Ethics, vol. 1, issue 3, pp. 213-218. [Online] Available at: doi.org/10.1007/s43681-021-00043-6 [Accessed 25 March 2023].
Vezzoli, C. (2007), System design for sustainability – Theory, methods and tools for a sustainable ‘satisfaction-system’ design, Maggioli Editore, Santarcangelo di Romagna (RM).
Vezzoli, C., Delfino, E. and Ambole, L. A. (2014), “System Design for Sustainable Energy for all – A new challenging role for design to foster sustainable development”, in FormAkademisk, vol. 7, issue 3, pp. 1-27. [Online] Available at: doi.org/10.7577/formakademisk.791 [Accessed 25 March 2023].
Vezzoli, C., Garcia Parra, B. and Kohtala, C. (eds) (2021), Designing Sustainability for All – The Design of Sustainable Product-Service Systems Applied to Distributed Economies, Springer Nature, Milano. [Online] Available at: doi.org/10.1007/978-3-030-66300-1 [Accessed 25 March 2023].
Vezzoli, C., Macrì, L. and Takacs, B. (2022), System Design for Sustainability in Practice, Maggioli Editore, Santarcangelo di Romagna (RM).
Vezzoli, C. and Manzini, E. (2008), “Review – Design for sustainable consumption and production systems”, in Tukker, A., Charter, M., Vezzoli, C., Stø, E. and Andersen, M. M. (eds), System Innovation for Sustainability 1 – Perspectives on Radical Changes to Sustainable Consumption and Production, Routledge, London, Chapter 28, pp. 1-21. [Online] Available at: doi.org/10.4324/9781351280204 [Accessed 25 March 2023].
Vitali, I., Paracolli, A. and Arquilla, V. (2022), “The role of design in the era of conversational interfaces”, in Spallazzo, D. and Sciannamé, M. (eds), Embedding Intelligence – Desiglerly reflections on AI-infused Products, FrancoAngeli, Milano, pp. 77-86. [Online] Available at: researchgate.net/publication/363335630_EMBEDDING_INTELLIGENCE_ Designerly_ reflections_on_AI-infused_products [Accessed 25 March 2023].
Wohlschlager, D., Neitz-Regett, A. and Lanzinger, B. (2021), “Environmental Assessment of Digital Infrastructure in Decentralized Smart Grids”, in 2021 IEEE 9th International Conference on Smart Energy Grid Engineering (SEGE), IEEE, pp. 13-18. [Online] Available at: doi.org/10.1109/SEGE52446.2021.9535061 [Accessed 25 March 2023].
Wu, C.-J., Raghavendra, R., Gupta, U., Acun, B., Ardalani, N., Maeng, K. et alii (2022), “Sustainable AI – Environmental implications, challenges and opportunities”, in Marculescu, D., Chi, Y., and Wu, C. (eds), Proceedings of Machine Learning and Systems, vol. 4, pp. 795-813. [Online] Available at: doi.org/10.48550/arXiv.2111.00364 [Accessed 25 March 2023].
Zaffagnini, T. and Morganti, L. (2022), “Data-driven LCA per l’innovazione industriale green delle facciate continue customizzate | Data-driven LCA for green industrial innovation of custom curtain walls”, in Agathón | International Journal of Architecture, Art and Design, vol. 12, pp. 94-105. [Online] Available at: doi.org/10.19229/2464-9309/1292022 [Accessed 25 March 2023].
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2023 Venanzio Arquilla, Alice Paracolli
This work is licensed under a Creative Commons Attribution 4.0 International License.
This Journal is published under Creative Commons Attribution Licence 4.0 (CC-BY).
License scheme | Legal code
This License allows anyone to:
Share: copy and redistribute the material in any medium or format.
Adapt: remix, transform, and build upon the material for any purpose, even commercially.
Under the following terms
Attribution: Users must give appropriate credit, provide a link to the license, and indicate if changes were made; users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No additional restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices
Users do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give users all of the permissions necessary for their intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
