Perceived unsustainability decreases acceptance of artificial intelligence

doi:10.3724/SP.J.1041.2025.1973

Abstract

Abstract:

Artificial intelligence (AI) has the potential to facilitate ecological governance and promote sustainable development. However, it also rapidly consumes energy and generates significant carbon emissions, posing challenges to both the natural environment and human survival. Despite these concerns, little research has examined the environmental costs of AI and how people respond to them. This study investigates how perceptions of AI sustainability influence individuals’ willingness to adopt AI in human-machine- environment decision-making contexts, as well as the underlying mechanisms and boundary conditions of this effect. Using a survey and AI-generated attitude descriptors from ChatGPT, a pilot study revealed generally high usage intentions and positive attitudes toward environmentally friendly AI systems. Study 1, consisting of two sub-studies, manipulated perceived AI sustainability (low vs. control) and found that participants exposed to low-sustainability AI reported lower acceptance and reduced support for national AI research. Study 2, using an experiment manipulating the perception of sustainability (low vs. high), replicated these findings and identified moral judgment, rather than agency attribution, as the mediating mechanism. Study 3 explored potential boundary conditions, demonstrating that individuals’ pro-environmental attitudes moderated the observed effects. These findings provide psychological insights into the social governance of AI and offer new perspectives on the relationship between AI and sustainable development.

Key words: sustainability, artificial intelligence, moral, agency, acceptance

WEI Xinni, YU Feng, PENG Kaiping. (2025). Perceived unsustainability decreases acceptance of artificial intelligence. Acta Psychologica Sinica, 57(11), 1973-1987.

Figures/Tables 5

Figure 1. Mediation path in Study 2.
Note: ^*p < 0.05, ^**p < 0.01, ^***p < 0.001; All the efficents were standardized.

Figure 2. Mediation path in Study 2.
Note:* p < 0.05, ^**p < 0.01, ^***p < 0.001; All the efficents were standardized.

Figure 3. Moderating effect of pro-environmental attitude on the relationship between sustainability and morality.

Figure 4. Moderating effect of pro-environmental attitude on the relationship between sustainability and willingness to use AI.

Figure 5. Moderating effect of pro-environmental attitude on the relationship between sustainability and support for AI research.

References 69

[1]	Ahn, M., Kang, J., & Hustvedt, G. (2016). A model of sustainable household technology acceptance. International Journal of Consumer Studies, 40, 83-91. https://doi.org/10.1111/ijcs.12217
[2]	Al-Sharafi, M. A., Al-Emran, M., Arpaci, I., Iahad, N. A., AlQudah, A. A., Iranmanesh, M., & Al-Qaysi, N. (2023). Generation Z use of artificial intelligence products and its impact on environmental sustainability: A cross-cultural comparison. Computers in Human Behavior, 143, 107708. https://doi.org/10.1016/j.chb.2023.107708
[3]	Anderson, M., & Anderson, S. L. (2007). Machine ethics: Creating an ethical intelligent agent. AI Magazine, 28(4), 15-26. https://doi.org/10.1609/aimag.v28i4.2065
[4]	Averdung, A., & Wagenfuehrer, D. (2011). Consumers’ acceptance, adoption and behavioural intentions regarding environmentally sustainable innovations. E3 Journal of Business Management and Economics, 2(3), 98-106.
[5]	Banks, J. (2019). A perceived moral agency scale: Development and validation of a metric for humans and social machines. Computers in Human Behavior, 90, 363-371. https://doi.org/10.1016/j.chb.2018.08.028
[6]	Baudier, P., Ammi, C., & Deboeuf-Rouchon, M. (2020). Smart home: Highly-educated students' acceptance. Technological Forecasting and Social Change, 153, 119355. https://doi.org/10.1016/j.techfore.2018.06.043
[7]	Bigman, Y. E., Wilson, D., Arnestad, M. N., Waytz, A., & Gray, K. (2023). Algorithmic discrimination causes less moral outrage than human discrimination. Journal of Experimental Psychology: General, 152(1), 4-27. https://doi.org/10.1037/xge0001250
[8]	Braun Kohlová, M., & Urban, J. (2020). Buy green, gain prestige and social status. Journal of Environmental Psychology, 69, 101416. https://doi.org/10.1016/j.jenvp.2020.101416
[9]	Bretter, C., Unsworth, K. L., Kaptan, G., & Russell, S. V. (2023). It is just wrong: Moral foundations and food waste. Journal of Environmental Psychology, 88, 102021. https://doi.org/10.1016/j.jenvp.2023.102021
[10]	Camilleri, A. R., Larrick, R., Hossain, S., & Patino-Echeverri, D. (2019). Consumers underestimate the emissions associated with food but are aided by labels. Nature Climate Change, 9, 53-58. https://doi.org/10.1038/s41558-018-0354-z doi: 10.1038/s41558-018-0354-z URL
[11]	Chen, S. H., Qiu, H., Xiao, H., He, W., Mou, J., & Siponen, M. T. (2020). Consumption behavior of eco-friendly products and applications of ICT innovation. Journal of Cleaner Production, 287, 125436. https://doi.org/10.1016/j.jclepro.2020.125436
[12]	Constantinescu, M. V., Vică, C., Uszkai, R., & Voinea, C. (2022). Blame it on the AI? On the moral responsibility of artificial moral advisors. Philosophy & Technology, 35(2), 35. https://doi.org/10.1007/s13347-022-00529-z
[13]	De Canio, F. (2023). Consumer willingness to pay more for pro- environmental packages: The moderating role of familiarity. Journal of Environmental Management, 339, 117828. https://doi.org/10.1016/j.jenvman.2023.117828
[14]	Deci, E. L., & Ryan, R. M. (1987). The support of autonomy and the control of behavior. Journal of Personality and Social Psychology, 53(6), 1024-1037. https://doi.org/10.1037/0022-3514.53.6.1024 doi: 10.1037//0022-3514.53.6.1024 URL pmid: 3320334
[15]	Dhar, P. (2020). The carbon impact of artificial intelligence. Nature Machine Intelligence. 2, 423-425.
[16]	Djeffal, C., Siewert, M. B., & Wurster, S. (2022). Role of the state and responsibility in governing artificial intelligence: A comparative analysis of AI strategies. Journal of European Public Policy, 29(11), 1799-1821. https://doi.org/10.1080/13501763.2022.2094987
[17]	Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data—Evolution, challenges and research agenda. International Journal of Information Management, 48, 63-71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
[18]	Dunlap, R. E., Van Liere, K. D., Mertig, A. G., & Emmet Jones, R. (2000). Measuring endorsement of the new ecological paradigm: A revised NEP scale. Journal of Social Issues, 56(3), 425-442. https://doi.org/10.1111/0022-4537.00176
[19]	Farrow, K., Grolleau, G., & Ibanez, L. (2017). Social norms and pro-environmental behavior: A review of the evidence. Ecological Economics, 140, 1-13. https://doi.org/10.1016/j.ecolecon.2017.04.017
[20]	Feinberg, M., & Willer, R. (2013). The moral roots of environmental attitudes. Psychological Science, 24(1), 56-62. https://doi.org/10.1177/0956797612449177
[21]	Floridi, L., & Sanders, J. W. (2004). On the morality of artificial agents. Minds and Machines, 14(3), 349-379. https://doi.org/10.1023/B:MIND.0000035461.63578.9d
[22]	Formosa, P., & Ryan, M. (2021). Making moral machines: Why we need artificial moral agents. AI and Society, 36(3), 839-851. https://doi.org/10.1007/s00146-020-01089-6
[23]	Gansser, O. A., & Reich, C. S. (2021). A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application. Technology in Society, 65, 101535. https://doi.org/10.1016/j.techsoc.2021.101535
[24]	Gifford, R., & Sussman, R. (2012). Environmental attitudes. In S. D. Clayton (Ed.), The Oxford handbook of environmental and conservation psychology (pp. 65-80). Oxford University Press.
[25]	Graham, J., Nosek, B. A., Haidt, J., Iyer, R., Koleva, S., & Ditto, P. H. (2011). Mapping the moral domain. Journal of Personality and Social Psychology, 101(2), 366-385. https://doi.org/10.1037/a0021847 doi: 10.1037/a0021847 URL pmid: 21244182
[26]	Grazzini, L., Acuti, D., & Aiello, G. (2021). Solving the puzzle of sustainable fashion consumption: The role of consumers’ implicit attitudes and perceived warmth. Journal of Cleaner Production, 287, 125579. https://doi.org/10.1016/j.jclepro.2020.125579
[27]	Gunkel, D. J. (2012). The machine question: Critical perspectives on AI, robots, and ethics. The MIT Press.
[28]	Haesevoets, T., De Cremer, D., Dierckx, K., & Van Hiel, A. (2021). Human-machine collaboration in managerial decision making. Computers in Human Behavior, 119, 106730. https://doi.org/10.1016/j.chb.2021.106730
[29]	Haidt, J. (2001). The emotional dog and its rational tail: A social intuitionist approach to moral judgment. Psychological Review, 108(4), 814-834. https://doi.org/10.1037/0033-295x.108.4.814 doi: 10.1037/0033-295x.108.4.814 URL pmid: 11699120
[30]	Haidt, J., & Joseph, C. (2004). Intuitive ethics: How innately prepared intuitions generate culturally variable virtues. Daedalus, 133(4), 55-66. https://doi.org/10.1162/0011526042365555
[31]	Haikonen, P. O. (2007). Robot brains: Circuits and systems for conscious machines. John Wiley & Sons.
[32]	Hernandez, J. M., Wright, S.A., & Ferminiano Rodrigues, F. (2015). Attributes versus benefits: The role of construal levels and appeal type on the persuasiveness of marketing messages. Journal of Advertising, 44, 243-253. https://doi.org/10.1080/00913367.2014.967425
[33]	Himma, K. E. (2009). Artiﬁcial agency, consciousness, and the criteria for moral agency: What properties must an artiﬁcial agent have to be a moral agent? Ethics and Information Technology, 11(1), 19-29. https://doi.org/10.1007/s10676-008-9167-5
[34]	Jay, C., Yu, Y., Crawford, I., James, P., Gledson, A., Shaddick, G.,... Topping, D. (2024). Prioritize environmental sustainability in use of AI and data science methods. Nature Geoscience, 17(2), 106-108. https://doi.org/10.1038/s41561-023-01369-y
[35]	Jia, F., Soucie, K., Alisat, S., Curtin, D., & Pratt, M. (2017). Are environmental issues moral issues? Moral identity in relation to protecting the natural world. Journal of Environmental Psychology, 52, 104-113. https://doi.org/10.1016/j.jenvp.2017.06.004
[36]	Johnson, S. G., & Ahn, J. (2020). Principles of moral accounting: How our intuitive moral sense balances rights and wrongs. Cognition, 206, 104467. https://doi.org/10.1016/j.cognition.2020.104467
[37]	Kelly, S., Kaye, S., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925. https://doi.org/10.1016/j.tele.2022.101925
[38]	Kneer, M., & Stuart, M. T. (2021). Playing the blame game with robots. In Bethel C., Paiva A., Broadbent E., Feil-Seifer D., Szafi D.r (Chairs), Companion of the 2021 ACM/IEEE international conference on human-robot interaction (pp. 407-411). Association for Computing Machinery. https://doi.org/10.1145/3434074.3447202
[39]	Krettenauer, T. (2017). Pro-environmental behavior and adolescent moral development. Journal of Research on Adolescence, 27(3), 581-593. https://doi.org/10.1111/jora.12300 doi: 10.1111/jora.12300 URL pmid: 28776840
[40]	Lakoff, G. (1995). Metaphor, morality, and politics or, why conservatives have left liberals in the dust. Social Research, 62, 177-213.
[41]	MacKinnon, D. P., Krull, J. L., & Lockwood, C. M. (2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science, 1(4), 173-181. https://doi.org/10.1023/a:1026595011371 doi: 10.1023/a:1026595011371 URL pmid: 11523746
[42]	Maninger, T., & Shank, D. B. (2022). Perceptions of violations by artificial and human actors across moral foundations. Computers in Human Behavior Reports, 5, 100154. https://doi.org/10.1016/j.chbr.2021.100154
[43]	McCright, A. M., & Dunlap, R. E. (2011). The politicization of climate change and polarization in the American public's views of global warming, 2001-2010. The Sociological Quarterly, 52(2), 155-194. https://doi.org/10.1111/j.1533-8525.2011.01198.x
[44]	Mert, W., Suschek-Berger, J., & Tritthart, W. (2008). Consumer acceptance of smart appliances (D 5. Graz: Inter-University Research Centre on Technology, Work and Culture.
[45]	Monroe, A. E., Dillon, K. D., & Malle, B. F. (2014). Bringing free will down to earth: People’s psychological concept of free will and its role in moral judgment. Consciousness and Cognition, 27, 100-108. https://doi.org/10.1016/j.concog.2014.04.011
[46]	Moor, J. H. (2006). The nature, importance, and difficulty of machine ethics. IEEE Intelligent Systems, 21(4), 18-21. https://doi.org/10.1109/MIS.2006.80
[47]	Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104. https://doi.org/10.1016/j.ijinfomgt.2020.102104
[48]	Pal., N. R. (2020). In search of trustworthy and transparent intelligent systems with human-like cognitive and reasoning capabilities. Frontiers in Robotics and AI, 7, 76. https://doi.org/10.3389/frobt.2020.00076
[49]	Park, E., Hwang, B., Ko, K., & Kim, D. (2017). Consumer acceptance analysis of the home energy management system. Sustainability, 9(12), 2351. https://doi.org/10.3390/su9122351
[50]	Ray, J. L., Mende-Siedlecki, P., Gantman, A., & Van Bavel, J. J. (2021). The role of morality in social cognition. In The Neural Basis of Mentalizing (pp. 555-566). Springer. https://doi.org/10.1007/978-3-030-51890-5.ch28
[51]	Schwartz, D., & Loewenstein, G. (2020). Encouraging pro-environmental behaviour through green identity labelling. Nature Sustainability, 3(9), 746-752. https://doi.org/10.1038/s41893-020-0543-4
[52]	Schwartz, R., Dodge, J., Smith, N. A., & Etzioni, O. (2020). Green AI. Communications of the ACM, 63(12), 54-63. https://doi.org/10.1145/3381831
[53]	Siala, H., & Wang, Y. (2022). SHIFTing artificial intelligence to be responsible in healthcare: A systematic review. Social Science & Medicine, 296, 114782. https://doi.org/10.1016/j.socscimed.2022.114782
[54]	Strubell, E., Ganesh, A., & McCallum, A. (2020). Energy and Policy Considerations for Modern Deep Learning Research. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13693-13696. https://doi.org/10.1609/aaai.v34i09.7123
[55]	Sullins, J. P. (2006). When is a robot a moral agent? International Review of Information Ethics, 6, 23-30.
[56]	Swanepoel, D. (2021). Does Artificial Intelligence Have Agency? In: Clowes, R.W., Gärtner, K., Hipólito, I. (Eds.) The mind-technology problem. Studies in brain and mind (vol. 18, pp.88-104). Springer, Cham
[57]	Tetlock, P. E. (2002). Social functionalist frameworks for judgment and choice: Intuitive politicians, theologians, and prosecutors. Psychological Review, 109(3), 451-471. https://doi.org/10.1037/0033-295X.109.3.451 URL pmid: 12088240
[58]	Tetlock, P. E. (2003). Thinking the unthinkable: Sacred values and taboo cognitions. Trends in Cognitive Sciences, 7(7), 320-324. https://doi.org/10.1016/S1364-6613(03)00135-9 URL pmid: 12860191
[59]	Urban, J., Bahník, Š., & Kohlová, M. B. (2023). Pro-environmental behavior triggers moral inference, not licensing by observers. Environment and Behavior, 55(1-2), 74-98. https://doi.org/10.1177/00139165231163547
[60]	van Wynsberghe, A. (2021). Sustainable AI: AI for sustainability and the sustainability of AI. AI Ethics, 1, 213-218. https://doi.org/10.1007/s43681-021-00043-6
[61]	van Wynsberghe, A., & Robbins, S. (2019). Critiquing the reasons for making artificial moral agents. Science and Engineering Ethics, 25(3), 719-735. https://doi.org/10.1007/s11948-018-0030-8 doi: 10.1007/s11948-018-0030-8 URL pmid: 29460081
[62]	Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
[63]	Verdecchia, R., Sallou, J., & Cruz, L. (2023). A systematic review of Green AI. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(4), e1507. https://doi.org/10.1002/widm.1507
[64]	Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S.,... Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 1-10. https://doi.org/10.1038/s41467-019-14108-y
[65]	Wilson, A., Stefanik, C., & Shank, D. B. (2022). How do people judge the immorality of artificial intelligence versus humans committing moral wrongs in real-world situations? Computers in Human Behavior Reports, 8, 100229. https://doi.org/10.1016/j.chbr.2022.100229
[66]	Wyss, A. M., Knoch, D., & Berger, S. (2022). When and how pro-environmental attitudes turn into behavior: The role of costs, benefits, and self-control. Journal of Environmental Psychology, 79, 101748. https://doi.org/10.1016/j.jenvp.2021.101748
[67]	Yu, F. (2020). On AI and Human Beings. Frontiers, (1), 30-36.
[68]	Yu, F., & Xu, L. (2018). How to make an ethical intelligence? Answer from a psychological perspective. Global Journal of Media Studies, 5(4), 24-42.
[69]	Złotowski, J., Yogeeswaran, K., & Bartneck, C. (2017). Can we control it? Autonomous robots threaten human identity, uniqueness, safety, and resources. International Journal of Human-Computer Studies, 100, 48-54. https://doi.org/10.1016/j.ijhcs.2016.12.008