IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i16p9165-d615174.html
   My bibliography  Save this article

Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals

Author

Listed:
  • Shin-Cheng Yeh

    (Graduate Institute of Environmental Education, National Taiwan Normal University, Taipei 11677, Taiwan)

  • Ai-Wei Wu

    (Graduate Institute of Environmental Education, National Taiwan Normal University, Taipei 11677, Taiwan)

  • Hui-Ching Yu

    (Department of Food & Beverage Management, Cheng-Shiu University, Kaohsiung City 83347, Taiwan)

  • Homer C. Wu

    (Graduate Program of Sustainable Tourism & Recreation Management, National Taichung University of Education, Taichung 40359, Taiwan)

  • Yi-Ping Kuo

    (Graduate Institute of Environmental Education, National Taiwan Normal University, Taipei 11677, Taiwan)

  • Pei-Xuan Chen

    (Graduate Institute of Environmental Education, National Taiwan Normal University, Taipei 11677, Taiwan)

Abstract

Artificial Intelligence (AI) will not just change our lives but bring about revolutionary transformation. AI can augment efficiencies of good and bad things and thus has been considered both an opportunity and risk for the sustainable development of humans. This study designed a survey to collect 1018 samples of educated people with access to the internet in Taiwan regarding their perceptions of AI and its connections to the Sustainable Development Goals (SDGs). The respondents showed high confidence in their AI knowledge. They had a very positive attitude toward AI but at the same time thought AI was risky. In general, people in Taiwan could be “rational optimists” regarding AI. We also examined how people think of the linkages between AI and the SDGs and found that SDG 4, SDG 9, and SDG 3 had the highest “synergy” and lowest rates of “trade-off”. Significant differences for some key questions were also identified concerning the demographic variables such as gender, age, education, and college major. According to the data analysis, education played as the base to construct a sustainable AI-aided town with an embedded innovative circular economy and high-quality water and energy services, making the residents live healthier lives. The findings of this study can be referred to when the perceptions of AI and sustainability issues are of interest for an emerging high-tech economy such as Taiwan and other Asian countries.

Suggested Citation

  • Shin-Cheng Yeh & Ai-Wei Wu & Hui-Ching Yu & Homer C. Wu & Yi-Ping Kuo & Pei-Xuan Chen, 2021. "Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals," Sustainability, MDPI, vol. 13(16), pages 1-34, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9165-:d:615174
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/16/9165/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/16/9165/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haili Zhang & Michael Song & Huanhuan He, 2020. "Achieving the Success of Sustainability Development Projects through Big Data Analytics and Artificial Intelligence Capability," Sustainability, MDPI, vol. 12(3), pages 1-23, January.
    2. Matthias Jarke & Boris Otto & Sudha Ram, 2019. "Data Sovereignty and Data Space Ecosystems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(5), pages 549-550, October.
    3. Seyed Meysam Khoshnava & Raheleh Rostami & Rosli Mohamad Zin & Dalia Štreimikienė & Alireza Yousefpour & Wadim Strielkowski & Abbas Mardani, 2019. "Aligning the Criteria of Green Economy (GE) and Sustainable Development Goals (SDGs) to Implement Sustainable Development," Sustainability, MDPI, vol. 11(17), pages 1-23, August.
    4. Måns Nilsson & Dave Griggs & Martin Visbeck, 2016. "Policy: Map the interactions between Sustainable Development Goals," Nature, Nature, vol. 534(7607), pages 320-322, June.
    5. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    6. Miltiadis D. Lytras & Kwok Tai Chui, 2019. "The Recent Development of Artificial Intelligence for Smart and Sustainable Energy Systems and Applications," Energies, MDPI, vol. 12(16), pages 1-7, August.
    7. V. Sathiya & M. Chinnadurai & S. Ramabalan & Andrea Appolloni, 2021. "Mobile robots and evolutionary optimization algorithms for green supply chain management in a used-car resale company," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(6), pages 9110-9138, June.
    8. Raymond Saner & Lichia Yiu & Melanie Nguyen, 2020. "Monitoring the SDGs: Digital and social technologies to ensure citizen participation, inclusiveness and transparency," Development Policy Review, Overseas Development Institute, vol. 38(4), pages 483-500, July.
    9. Vangelis Marinakis & Themistoklis Koutsellis & Alexandros Nikas & Haris Doukas, 2021. "AI and Data Democratisation for Intelligent Energy Management," Energies, MDPI, vol. 14(14), pages 1-14, July.
    10. Brougham, David & Haar, Jarrod, 2018. "Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace," Journal of Management & Organization, Cambridge University Press, vol. 24(2), pages 239-257, March.
    11. Vasile Gherheș & Ciprian Obrad, 2018. "Technical and Humanities Students’ Perspectives on the Development and Sustainability of Artificial Intelligence (AI)," Sustainability, MDPI, vol. 10(9), pages 1-16, August.
    12. Kwok Tai Chui & Miltiadis D. Lytras & Anna Visvizi, 2018. "Energy Sustainability in Smart Cities: Artificial Intelligence, Smart Monitoring, and Optimization of Energy Consumption," Energies, MDPI, vol. 11(11), pages 1-20, October.
    13. Barbier, Edward B. & Burgess, Joanne C., 2017. "The sustainable development goals and the systems approach to sustainability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-23.
    14. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    15. Amr ElAlfy & Nicholas Palaschuk & Dina El-Bassiouny & Jeffrey Wilson & Olaf Weber, 2020. "Scoping the Evolution of Corporate Social Responsibility (CSR) Research in the Sustainable Development Goals (SDGs) Era," Sustainability, MDPI, vol. 12(14), pages 1-21, July.
    16. Morgan R. Frank & David Autor & James E. Bessen & Erik Brynjolfsson & Manuel Cebrian & David J. Deming & Maryann Feldman & Matthew Groh & José Lobo & Esteban Moro & Dashun Wang & Hyejin Youn & Iyad Ra, 2019. "Toward understanding the impact of artificial intelligence on labor," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(14), pages 6531-6539, April.
    17. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    18. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    19. JinHyo Joseph Yun & Dooseok Lee & Heungju Ahn & Kyungbae Park & Tan Yigitcanlar, 2016. "Not Deep Learning but Autonomous Learning of Open Innovation for Sustainable Artificial Intelligence," Sustainability, MDPI, vol. 8(8), pages 1-20, August.
    20. Mathiyazhagan, Kaliyan & Agarwal, Vernika & Appolloni, Andrea & Saikouk, Tarik & Gnanavelbabu, A, 2021. "Integrating lean and agile practices for achieving global sustainability goals in Indian manufacturing industries," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anne David & Tan Yigitcanlar & Rita Yi Man Li & Juan M. Corchado & Pauline Hope Cheong & Karen Mossberger & Rashid Mehmood, 2023. "Understanding Local Government Digital Technology Adoption Strategies: A PRISMA Review," Sustainability, MDPI, vol. 15(12), pages 1-43, June.
    2. Abdelaziz Darwiesh & A. H. El-Baz & Abedallah Zaid Abualkishik & Mohamed Elhoseny, 2022. "Artificial Intelligence Model for Risk Management in Healthcare Institutions: Towards Sustainable Development," Sustainability, MDPI, vol. 15(1), pages 1-13, December.
    3. Wilson, Christopher & van der Velden, Maja, 2022. "Sustainable AI: An integrated model to guide public sector decision-making," Technology in Society, Elsevier, vol. 68(C).
    4. Simon Ofori Ametepey & Clinton Aigbavboa & Wellington Didibhuku Thwala & Hutton Addy, 2024. "The Impact of AI in Sustainable Development Goal Implementation: A Delphi Study," Sustainability, MDPI, vol. 16(9), pages 1-76, May.
    5. Tan Yigitcanlar, 2021. "Greening the Artificial Intelligence for a Sustainable Planet: An Editorial Commentary," Sustainability, MDPI, vol. 13(24), pages 1-9, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tan Yigitcanlar & Kevin C. Desouza & Luke Butler & Farnoosh Roozkhosh, 2020. "Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature," Energies, MDPI, vol. 13(6), pages 1-38, March.
    2. Tan Yigitcanlar & Federico Cugurullo, 2020. "The Sustainability of Artificial Intelligence: An Urbanistic Viewpoint from the Lens of Smart and Sustainable Cities," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    3. Makarius, Erin E. & Mukherjee, Debmalya & Fox, Joseph D. & Fox, Alexa K., 2020. "Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization," Journal of Business Research, Elsevier, vol. 120(C), pages 262-273.
    4. Uzir, Md Uzir Hossain & Al Halbusi, Hussam & Lim, Rodney & Jerin, Ishraq & Abdul Hamid, Abu Bakar & Ramayah, Thurasamy & Haque, Ahasanul, 2021. "Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19," Technology in Society, Elsevier, vol. 67(C).
    5. Chowdhury, Soumyadeb & Budhwar, Pawan & Dey, Prasanta Kumar & Joel-Edgar, Sian & Abadie, Amelie, 2022. "AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework," Journal of Business Research, Elsevier, vol. 144(C), pages 31-49.
    6. Cao, Guangming & Duan, Yanqing & Edwards, John S. & Dwivedi, Yogesh K., 2021. "Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making," Technovation, Elsevier, vol. 106(C).
    7. Tan Yigitcanlar, 2021. "Greening the Artificial Intelligence for a Sustainable Planet: An Editorial Commentary," Sustainability, MDPI, vol. 13(24), pages 1-9, December.
    8. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    9. Wilson, Christopher & van der Velden, Maja, 2022. "Sustainable AI: An integrated model to guide public sector decision-making," Technology in Society, Elsevier, vol. 68(C).
    10. Anya Johnson & Shanta Dey & Helena Nguyen & Markus Groth & Sadhbh Joyce & Leona Tan & Nicholas Glozier & Samuel B Harvey, 2020. "A review and agenda for examining how technology-driven changes at work will impact workplace mental health and employee well-being," Australian Journal of Management, Australian School of Business, vol. 45(3), pages 402-424, August.
    11. David Tremblay & François Fortier & Jean‐François Boucher & Olivier Riffon & Claude Villeneuve, 2020. "Sustainable development goal interactions: An analysis based on the five pillars of the 2030 agenda," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(6), pages 1584-1596, November.
    12. Tan Yigitcanlar & Rashid Mehmood & Juan M. Corchado, 2021. "Green Artificial Intelligence: Towards an Efficient, Sustainable and Equitable Technology for Smart Cities and Futures," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    13. Kim, Myung Ja & Hall, C. Michael & Kwon, Ohbyung & Sohn, Kwonsang, 2024. "Space tourism: Value-attitude-behavior theory, artificial intelligence, and sustainability," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    14. Shin-Cheng Yeh & Haw-Jeng Chiou & Ai-Wei Wu & Ho-Ching Lee & Homer C. Wu, 2019. "Diverged Preferences towards Sustainable Development Goals? A Comparison between Academia and the Communication Industry," IJERPH, MDPI, vol. 16(22), pages 1-21, November.
    15. Wang, Bo & Wang, Jianda & Dong, Kangyin & Nepal, Rabindra, 2024. "How does artificial intelligence affect high-quality energy development? Achieving a clean energy transition society," Energy Policy, Elsevier, vol. 186(C).
    16. Nariê Rinke Dias de Souza & Alexandre Souza & Mateus Ferreira Chagas & Thayse Aparecida Dourado Hernandes & Otávio Cavalett, 2022. "Addressing the contributions of electricity from biomass in Brazil in the context of the Sustainable Development Goals using life cycle assessment methods," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 980-995, June.
    17. Volkmar, Gioia & Fischer, Peter M. & Reinecke, Sven, 2022. "Artificial Intelligence and Machine Learning: Exploring drivers, barriers, and future developments in marketing management," Journal of Business Research, Elsevier, vol. 149(C), pages 599-614.
    18. Anita Breuer & Hannah Janetschek & Daniele Malerba, 2019. "Translating Sustainable Development Goal (SDG) Interdependencies into Policy Advice," Sustainability, MDPI, vol. 11(7), pages 1-20, April.
    19. David Mortimore, 2024. "Moving beyond human-centric organizational designs," Journal of Organization Design, Springer;Organizational Design Community, vol. 13(2), pages 65-75, June.
    20. Steve J. Bickley & Alison Macintyre & Benno Torgler, 2021. "Artificial Intelligence and Big Data in Sustainable Entrepreneurship," CREMA Working Paper Series 2021-11, Center for Research in Economics, Management and the Arts (CREMA).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9165-:d:615174. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.