{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T04:14:32Z","timestamp":1774671272270,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Contemporary society faces unprecedented challenges\u2014from rapid technological evolution to climate change and demographic tensions\u2014compelling organisations to anticipate the future for informed decision-making. This case study aimed to design a digital system for end-users called the Time Machine, which enables a generative artificial intelligence (GAI) system to produce prospective future scenarios based on the input information automatically, proposing hypotheses and prioritising trends to streamline and make the formulation of future scenarios more accessible. The system\u2019s design, development, and testing progressed through three versions of prompts for the OpenAI GPT-4 LLM, with six trials conducted involving 222 participants. This iterative approach allowed for gradual adjustment of instructions given to the machine and encouraged refinement. Results from the six trials demonstrated that the Time Machine is an effective tool for generating future scenarios that promote debate and stimulate new ideas in multidisciplinary teams. Our trials proved that GAI-generated scenarios could foster discussions on +70% of generated scenarios with appropriate prompting, and more than half included new ideas. In conclusion, large language models (LLMs) of GAI, with suitable prompt engineering and architecture, have the potential to generate useful future scenarios for organisations, transforming future intelligence into a more accessible and operational resource. However, critical use of these scenarios is essential.<\/jats:p>","DOI":"10.3390\/fi17010048","type":"journal-article","created":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T10:32:15Z","timestamp":1737369135000},"page":"48","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["The Time Machine: Future Scenario Generation Through Generative AI Tools"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1431-9349","authenticated-orcid":false,"given":"Jan","family":"Ferrer i Pic\u00f3","sequence":"first","affiliation":[{"name":"Innex Labs, Institut pel Futur, Carrer de Llu\u00eds Millet 8, 17190 Salt, Catalonia, Spain"},{"name":"Departament d\u2019Enginyeria Gr\u00e0fica i Disseny, Escola T\u00e8cnica Superior d\u2019Enginyeria Industrial de Barcelona (ETSEIB), Universitat Polit\u00e8cnica de Catalunya, Avinguda Diagonal 647, 08028 Barcelona, Catalonia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9200-1976","authenticated-orcid":false,"given":"Michelle","family":"Catta-Preta","sequence":"additional","affiliation":[{"name":"Innex Labs, Institut pel Futur, Carrer de Llu\u00eds Millet 8, 17190 Salt, Catalonia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4142-083X","authenticated-orcid":false,"given":"Alex","family":"Trejo Ome\u00f1aca","sequence":"additional","affiliation":[{"name":"Innex Labs, Institut pel Futur, Carrer de Llu\u00eds Millet 8, 17190 Salt, Catalonia, Spain"},{"name":"Departament d\u2019Enginyeria Gr\u00e0fica i Disseny, Escola Polit\u00e8cnica Superior d\u2019Enginyeria de Vilanova i la Geltr\u00fa (EPSEVG), Universitat Polit\u00e8cnica de Catalunya, Avinguda de V\u00edctor Balaguer 1, 08800 Vilanova i la Geltr\u00fa, Catalonia, Spain"}]},{"given":"Marc","family":"Vidal","sequence":"additional","affiliation":[{"name":"Innex Labs, Institut pel Futur, Carrer de Llu\u00eds Millet 8, 17190 Salt, Catalonia, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7416-8306","authenticated-orcid":false,"given":"Josep Maria","family":"Monguet i Fierro","sequence":"additional","affiliation":[{"name":"Innex Labs, Institut pel Futur, Carrer de Llu\u00eds Millet 8, 17190 Salt, Catalonia, Spain"},{"name":"Departament d\u2019Enginyeria Gr\u00e0fica i Disseny, Escola T\u00e8cnica Superior d\u2019Enginyeria Industrial de Barcelona (ETSEIB), Universitat Polit\u00e8cnica de Catalunya, Avinguda Diagonal 647, 08028 Barcelona, Catalonia, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,20]]},"reference":[{"key":"ref_1","unstructured":"Wright, A. (2004). A Social Constructionist\u2019s Deconstruction of Royal Dutch Shell\u2019s Scenario Planning Process, University of Wolverhampton."},{"key":"ref_2","unstructured":"Ringland, G. (2002). Scenario Planning: Managing for the Future, Wiley."},{"key":"ref_3","unstructured":"Bell, W. (1996). Foundations of Futures Studies: Human Science for a New Era, Transaction Publishers."},{"key":"ref_4","unstructured":"Ferrer i Pic\u00f3, J. (2022). Stories from Watertown: Subjectification in Living Labs or an Auto-Ethnographic Game for the Development of Worldviews Awareness. [Master\u2019s Thesis, Universitat Polit\u00e8cnica de Catalunya]."},{"key":"ref_5","unstructured":"Avis, W.R. (2017). Scenario Thinking and Usage Among Development Actors, Institute of Development Studies. K4D Helpdesk Report."},{"key":"ref_6","unstructured":"Naisbitt, J. (1986). Megatrends: Ten New Directions Transforming Our Lives, Warner Books."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1177\/1523422307313334","article-title":"Learning With Scenarios: Summary and Critical Issues","volume":"10","author":"Burt","year":"2008","journal-title":"Adv. Dev. Hum. Resour."},{"key":"ref_8","unstructured":"van der Heijden, K. (2010). Scenarios: The Art of Strategic Conversation, Wiley. [2nd ed.]."},{"key":"ref_9","first-page":"139","article-title":"Unlocking the Potential Barriers on SMEs\u2019 Uptake of Scenario Planning","volume":"8","author":"Nyuur","year":"2015","journal-title":"J. Strategy Manag."},{"key":"ref_10","unstructured":"Recklies, D. (2024, October 30). Strategy Making in the Past and Today\u2014Part 2: Problems with the Traditional Strategy Process. Available online: https:\/\/www.themanager.org\/2015\/08\/strategy-making-2-problems-traditional-strategy-process\/?utm_source=chatgpt.com."},{"key":"ref_11","unstructured":"Malik, A. (2024, December 27). OpenAI\u2019s ChatGPT Now Has 100 Million Weekly Active Users. Available online: https:\/\/techcrunch.com\/2023\/11\/06\/Openais-Chatgpt-Now-Has-100-Million-Weekly-Active-Users\/."},{"key":"ref_12","unstructured":"Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, The MIT Press. Adaptive computation and machine learning."},{"key":"ref_13","unstructured":"Shact, L., Kreit, B., Vert, G., Holdowsky, J., and Buckley, N. (2024). Four Futures of Generative AI in the Enterprise: Scenario Planning for Strategic Resilience and Adaptability, Deloitte Insights."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"101879","DOI":"10.1016\/j.techsoc.2022.101879","article-title":"Determining the Human to AI Workforce Ratio\u2014Exploring Future Organisational Scenarios and the Implications for Anticipatory Workforce Planning","volume":"68","author":"Farrow","year":"2022","journal-title":"Technol. Soc."},{"key":"ref_15","unstructured":"Chow, A.R. (2024, December 27). How AI Is Fueling a Boom in Data Centers and Energy Demand. Available online: https:\/\/time.com\/6987773\/ai-data-centers-energy-usage-climate-change\/?utm_source=chatgpt.com\/."},{"key":"ref_16","unstructured":"Li, P., Yang, J., Islam, M.A., and Ren, S. (2023). Making AI Less \u201cThirsty\u201d: Uncovering and Addressing the Secret Water Footprint of AI Models. arXiv."},{"key":"ref_17","unstructured":"Newport, C. (2024, November 13). What Kind of Writer Is ChatGPT?. Available online: https:\/\/www.newyorker.com\/culture\/annals-of-inquiry\/what-kind-of-writer-is-chatgpt?utm_source=chatgpt.com."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Sun, Y., Li, Z., Fang, K., Lee, C.H., and Asadipour, A. (2023, January 8\u201312). Language as Reality: A Co-Creative Storytelling Game Experience in 1001 Nights Using Generative AI. Proceedings of the Nineteenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, Salt Lake City, UT, USA.","DOI":"10.1609\/aiide.v19i1.27539"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Pellas, N. (2023). The Effects of Generative AI Platforms on Undergraduates\u2019 Narrative Intelligence and Writing Self-Efficacy. Educ. Sci., 13.","DOI":"10.3390\/educsci13111155"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1111\/jpim.12602","article-title":"Innovative Idea Generation in Problem Finding: Abductive Reasoning, Cognitive Impediments, and the Promise of Artificial Intelligence","volume":"38","author":"Garbuio","year":"2021","journal-title":"J. Prod. Innov. Manag."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Malakuczi, V., Ershova, M., Gentile, A., Gironi, C., Saviano, M., and Imbesi, L. (2024, January 23\u201328). Design in Dialogue: AI as an Aid of Imagination for Future Scenarios. Proceedings of the DRS2024, Boston, MA, USA.","DOI":"10.21606\/drs.2024.1171"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Finkenstadt, D.J., Eapen, T., Sotiriadis, J., and Guinto, P. (2024). Use GenAI to Improve Scenario Planning. SSRN Electron. J.","DOI":"10.2139\/ssrn.4760156"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Mannuru, N.R., Shahriar, S., Teel, Z.A., Wang, T., Lund, B.D., Tijani, S., Pohboon, C.O., Agbaji, D., Alhassan, J., and Galley, J. (2023). Artificial Intelligence in Developing Countries: The Impact of Generative Artificial Intelligence (AI) Technologies for Development. Inf. Dev., 02666669231200628.","DOI":"10.1177\/02666669231200628"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Poli, R. (2017). Big History and Anticipation. Handbook of Anticipation, Springer International Publishing.","DOI":"10.1007\/978-3-319-31737-3_1-1"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kieslich, K., Helberger, N., and Diakopoulos, N. (2024, January 3\u20136). My Future with My Chatbot: A Scenario-Driven, User-Centric Approach to Anticipating AI Impacts. Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro, Brazil.","DOI":"10.1145\/3630106.3659026"},{"key":"ref_26","unstructured":"Chen, X.A., Burke, J., Du, R., Hong, M.K., Jacobs, J., Laban, P., Li, D., Peng, N., Willis, K.D.D., and Wu, C.-S. (2023). Next Steps for Human-Centered Generative AI: A Technical Perspective. arXiv."},{"key":"ref_27","unstructured":"Surowiecki, J. (2004). The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations, Doubleday. [1st ed.]."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Susskind, R.E., and Susskind, D. (2015). The Future of the Professions: How Technology Will Transform the Work of Human Experts, Oxford University Press. Oxford scholarship online.","DOI":"10.1093\/oso\/9780198713395.001.0001"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Mun, J., Jiang, L., Liang, J., Cheong, I., DeCairo, N., Choi, Y., Kohno, T., and Sap, M. (2024, January 21\u201323). Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits. Proceedings of the Seventh AAAI\/ACM Conference on AI, Ethics, and Society (AIES-24), San Jose, CA, USA.","DOI":"10.1609\/aies.v7i1.31698"},{"key":"ref_30","first-page":"53","article-title":"Speculative Futures on ChatGPT and Generative Artificial Intelligence (AI): A Collective Reflection from the Educational Landscape","volume":"18","author":"Bozkurt","year":"2023","journal-title":"Asian J. Distance Educ."},{"key":"ref_31","unstructured":"Dweck, C. (2017). Mindset: Changing the Way You Think to Fulfil Your Potential, Robinson."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"9","DOI":"10.15446\/dyna.v90n230.111700","article-title":"Prompt Engineering: A Methodology for Optimizing Interactions with AI-Language Models in the Field of Engineering","volume":"90","year":"2023","journal-title":"Dyna"},{"key":"ref_33","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., and Polosukhin, I. (2017). Attention Is All You Need. arXiv."},{"key":"ref_34","unstructured":"Brown, T.B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., and Askell, A. (2020). Language Models Are Few-Shot Learners. arXiv."},{"key":"ref_35","unstructured":"Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q., and Zhou, D. (2022). Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. arXiv."},{"key":"ref_36","unstructured":"Madaan, A., and Yazdanbakhsh, A. (2022). Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango. arXiv."},{"key":"ref_37","unstructured":"Madaan, A., Tandon, N., Gupta, P., Hallinan, S., Gao, L., Wiegreffe, S., Alon, U., Dziri, N., Prabhumoye, S., and Yang, Y. (2023). Self-Refine: Iterative Refinement with Self-Feedback. arXiv."},{"key":"ref_38","unstructured":"Wang, X., Wei, J., Schuurmans, D., Le, Q., Chi, E., Narang, S., Chowdhery, A., and Zhou, D. (2022). Self-Consistency Improves Chain of Thought Reasoning in Language Models. arXiv."},{"key":"ref_39","unstructured":"Zhou, D., Sch\u00e4rli, N., Hou, L., Wei, J., Scales, N., Wang, X., Schuurmans, D., Cui, C., Bousquet, O., and Le, Q. (2022). Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. arXiv."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Liu, J., Liu, A., Lu, X., Welleck, S., West, P., Bras, R.L., Choi, Y., and Hajishirzi, H. (2021). Generated Knowledge Prompting for Commonsense Reasoning. arXiv.","DOI":"10.18653\/v1\/2022.acl-long.225"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Jung, J., Qin, L., Welleck, S., Brahman, F., Bhagavatula, C., Bras, R.L., and Choi, Y. (2022). Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations. arXiv.","DOI":"10.18653\/v1\/2022.emnlp-main.82"},{"key":"ref_42","unstructured":"Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T.L., Cao, Y., and Narasimhan, K. (2023). Tree of Thoughts: Deliberate Problem Solving with Large Language Models. arXiv."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Sahoo, P., Singh, A.K., Saha, S., Jain, V., Mondal, S., and Chadha, A. (2024). A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications. arXiv.","DOI":"10.1007\/979-8-8688-0569-1_4"},{"key":"ref_44","unstructured":"Amatriain, X. (2024). Prompt Design and Engineering: Introduction and Advanced Methods. arXiv."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.destud.2018.10.001","article-title":"Empirically Analysing Design Reasoning Patterns: Abductive-Deductive Reasoning Patterns Dominate Design Idea Generation","volume":"60","author":"Christensen","year":"2019","journal-title":"Des. Stud."},{"key":"ref_46","unstructured":"Brandt, E., and Binder, T. (2007, January 12\u201315). Experimental Design Research: Genealogy\u2013Intervention\u2013Argument. Proceedings of the International Association of Societies of Design Research 2007: Emerging Trends in Design, Hong Kong, China."},{"key":"ref_47","first-page":"643","article-title":"A Systematic Literature Review of Mining Weak Signals and Trends for Corporate Foresight","volume":"88","author":"Grottke","year":"2018","journal-title":"J. Bus. Econ."},{"key":"ref_48","unstructured":"Doran, H., and Dyer, K. (2021). Trend Deck\u2014Evidence of Future Change for UK Policy Makers, Futures, Foresight and Horizon Scanning."},{"key":"ref_49","unstructured":"Joint Research Center-EC (2023, December 12). The Megatrends Hub. Available online: https:\/\/knowledge4policy.ec.europa.eu\/foresight\/tool\/megatrends-hub_en."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Halskov, K., and Dalsg\u00e5rd, P. (2006, January 26\u201328). Inspiration Card Workshops. Proceedings of the 6th Conference on Designing Interactive Systems, University Park, PA, USA.","DOI":"10.1145\/1142405.1142409"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.jclepro.2012.05.013","article-title":"System Innovation for Sustainability: A Systemic Double-Flow Scenario Method for Companies","volume":"45","author":"Gaziulusoy","year":"2013","journal-title":"J. Clean. Prod."},{"key":"ref_52","first-page":"47","article-title":"Chasing Black Swans through Science Fiction: Surprising Future Events in the Stories of a Finnish Writing Competition","volume":"20","author":"Ahlqvist","year":"2015","journal-title":"J. Futur. Stud."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s00163-022-00386-z","article-title":"Feedback Systems in the Design and Development Process","volume":"33","author":"Wynn","year":"2022","journal-title":"Res. Eng. Des."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"102826","DOI":"10.1016\/j.compcom.2024.102826","article-title":"Machine-in-the-Loop Writing: Optimizing the Rhetorical Load","volume":"71","author":"Knowles","year":"2024","journal-title":"Comput. Compos."},{"key":"ref_55","unstructured":"Talebirad, Y., and Nadiri, A. (2023). Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents. arXiv."},{"key":"ref_56","unstructured":"Carbonell, E. (2024). De la Caverna la Cosmos, Ara Llibres."},{"key":"ref_57","unstructured":"Dunne, A., and Raby, F. (2013). Speculative Everything: Design, Fiction, and Social Dreaming, The MIT Press."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/17\/1\/48\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:32:21Z","timestamp":1759919541000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/17\/1\/48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,20]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,1]]}},"alternative-id":["fi17010048"],"URL":"https:\/\/doi.org\/10.3390\/fi17010048","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,20]]}}}