Briefing with artificial intelligence for requirement elicitation: Three cases with ChatGPT for exploration of possibilities

• Autorzy: Çalışkan, Ekrem Bahadır

Warianty tytułu

PL

Wywiad ze sztuczną inteligencją w procesie zbierania danych do projektowania. Badanie możliwości ChatGPT – trzy przypadki

• Języki publikacji: EN

Abstrakty

EN

Architectural program is important knowledge of space requirements affecting the design besides context, concept, and intentions. The requirement knowledge is elicited and validated between project stakeholders during the pre-design and design process. The complexity of defining requirements and the difficulty capturing knowledge from project parties vary. Briefing is a vital process to capture, refine, create, and manage space requirements from end-users. Lacks of communication, the inclusion of user clients, and clarity of objectives are critical for eliciting requirements. The AI tools offer many possibilities to diverse areas, and several studies have been conducted recently. The research seeks the usage of AI to capture the building requirement by putting it in the position of the end-user. For this purpose, ChatGPT was used, a language model capable of generating texts and predicting and creating knowledge. The study’s objective is to explore AI’s limits and capabilities for the briefing process to initiate the requirement elicitation. Within the semi-structured interview process, the briefing session was executed for three cases by putting the AI in the end user position. The results are promising in the requirement elicitation of pre-project stages considering the clarity of the architectural program, integrity in context, and usage of time. The argued contribution of AI in architectural projects requires further research; however, the study underlines the possible usage of AI for defining the requirements of the spaces. The avenues of further research may include validating captured knowledge processes needed, examining the AI for different building typologies and project stakeholders, and seeking the bias, ethical concerns, and combinations of humans and AI for various tasks.

PL

Program architektoniczny ma oczywisty i zasadniczy wpływ na formę projektowanych budowli. Wiedza na temat oczekiwań i wymagań programowych jest pozyskiwana i weryfikowana w czasie procesu projektowania wstępnego. Złożoność definiowania potrzeb użytkowych i trudności w pozyskiwaniu informacji od stron zaangażowanych w powstawanie projektu są zróżnicowane. Wywiad jest podstawowym narzędziem mającym na celu tworzenie, udoskonalanie i zarządzanie wymaganiami dotyczącymi dyspozycji przestrzennych z perspektywy użytkowników końcowych. Sztuczna inteligencja (AI) oferuje wiele możliwości w różnych dziedzinach, w tym w projektowaniu, co od niedawna poddawane jest szczegółowym analizom. W niniejszym artykule przedstawiono badania nad możliwościami wykorzystania AI do programowania budynków z punktu widzenia ich użytkowników. Wykorzystano model językowy ChatGPT, który ma zdolność przewidywania oraz generowania tekstów i informacji. Podstawowym celem badania było ustalenie granic i zdolności/precyzji AI w formułowaniu wymogów przestrzennych dla trzech różnych typów budowli. Wyniki okazały się obiecujące pod względem łatwości prowadzenia ustaleń ma linii projektant–użytkownik na etapach przedprojektowych. ChatGPT pozwolił stworzyć jasny program architektoniczny przy zintegrowaniu kontekstu i ekonomicznym wykorzystaniu czasu. Postulowany wkład AI w projektowanie architektoniczne wymaga dalszych badań, jednak przedstawiona analiza wskazuje możliwe zastosowanie sztucznej inteligencji do definiowania wymagań programowych i przestrzennych. Kierunki dalszych ustaleń mogą obejmować walidację zdobytej wiedzy, procesy potrzebne do jej zastosowania, badania AI dla różnych typów budynków i interesariuszy projektu, a także dyskusje na temat wątpliwości prawnych i kwestii etycznych.

Słowa kluczowe

PL

sztuczna inteligencja; wywiad; uchwycenie wymagań; ChatGPT; użytkownik

EN

artificial intelligence; briefing; requirement capturing; ChatGPT; end-user

• Czasopismo: Architectus
• Rocznik: 2023
• Tom: Nr 3 (75)
• Strony: 93--101
• Opis fizyczny: Bibliogr. 34 poz., il., tab.

Twórcy

autor

Çalışkan, Ekrem Bahadır

• Faculty of Architecture and Fine Arts, Ankara Yıldırım Beyazıt University, Ankara, Türkiye,

Bibliografia

• [1] Blyth A., Worthigton J., Managing the brief for better design, Routledge, London 2010, doi: 10.4324/9780203857373.
• [2] Shahrin F., Johansen E., Lockley S., Udeaja C., Effective Capture, Translating and Delivering Client Requirements Using Building Information Modelling (Bim) Technology, [in:] Arcom Research Workshop On Decision-Making Across Levels, Time And Space: Exploring Theories, Methods And Practices, EPSRC, Manchester 2010, 38–45.
• [3] Kamara J.M., Anumba C.J., Carrillo P.M., Bouchlaghem D., Conceptual framework for live capture and reuse of project knowledge, “International Conference on Information Technology for Construction” 2003, January, 178–185.
• [4] Tan H.C., Anumba C.J., Carrillo P.M., Bouchlaghem D., Kamara J., Udeaja C., Capture and reuse of project knowledge in construction, Wiley-Blackwell, 2010, doi: 10.1002/9781444315448.
• [5] Al-Ghassani A., Improving the structural design process: A knowledge management approach, PhD thesis, Loughborough University, Leicestershire 2003.
• [6] Pourzolfaghar Z., Ibrahim R., Abdullah R., Adam N.M., A technique to capture multi-disciplinary tacit knowledge during the conceptual design phase of a building project, “Journal of Information and Knowledge Management” 2014, Vol. 13, No. 2, doi: 10.1142/s0219649214500130.
• [7] Dwivedi Y.K., Kshetri N., Hughes L. et al., “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy’, “International Journal of Information Management” 2023, Vol. 71, doi: 10.1016/j.ijinfomgt.2023.102642.
• [8] Mondal S., Das S., Vrana V.G., How to Bell the Cat? A theoretical review of Generative Artificial Intelligence towards digital disruption in all walks of life, “Technologies” 2023, Vol. 11, No. 2, 44, doi: 10.3390/technologies11020044.
• [9] Crompton H., Burke D., Artificial intelligence in higher education: the state of the field, “International Journal of Educational Technology in Higher Education” 2023, Vol. 20, No. 22, doi: 10.1186/s41239-023-00392-8.
• [10] Jaruga-Rozdolska A., Artificial intelligence as part of future practices in the architect’s work: MidJourney generative tool as part of a process of creating an architectural form, “Architectus” 2022, nr 3(71), 95–104, doi: 10.37190/arc220310.
• [11] Bozkurt A., Xiao J., Lambert S. et al., Speculative Futures on ChatGPT and Generative Artificial Intelligence (AI): A Collective Reflection from the Educational Landscape, “Asian Journal of Distance Education” 2023, Vol. 18, Iss. 1, 53–130, doi: 10.5281/zenodo.7636568.
• [12] Barrett P., Stanley C., Better construction briefing, Wiley-Blackwell, Oxford 1999.
• [13] Ryd N., The design brief as carrier of client information during the construction process, “Design Studies” 2004, Vol. 25, Iss. 3, 231–249, doi: 10.1016/j.destud.2003.10.003.
• [14] Olatokun E., Pathirage C., Importance of knowledge capturing (KC) in the design briefing process in the construction industry, [in:] 12 th International Postgraduate Research Conference (IPGRC 2015), 2015, 1–16.
• [15] Kamara J.M., Anumba C.J., Hobbs B., From briefing to client requirements processing, [in:] W. Hughes (ed.), 15 th Annual ARCOM Conference, 15–17 September 1999, Liverpool John Moores University, Association of Researchers in Construction Management, Vol. 1, 317–326.
• [16] Barrett P.S., Hudson J., Stanley C., Good practice in briefing: the limits of rationality, “Automation in Construction” 1999, Vol. 8, Iss. 6, 633–642, doi: 10.1016/s0926-5805(98)00108-3.
• [17] Pegoraroa C., Paula I.C., Requirements processing for building design: A systematic review, “Producao” 2017, Vol. 27, 1–18, doi: 10.1590/0103-6513.212116.
• [18] Norouzi N., Shabak M., Bin Embi M.R., Khan T.H., The architect, the client and effective communication in architectural design practice, “Procedia – Social and Behavioral Sciences” 2015, Vol. 172, 635–642, doi: 10.1016/j.sbspro.2015.01.413.
• [19] Faatz S., Architectural programming: providing essential knowledge of project participants needs in the pre-design phase, “Organization, Technology & Management in Construction: An International Journal” 2009, Vol. 1, No. 2, 80–85.
• [20] Olatokun E.O., Requirement elicitation using knowledge capturing (Kc) techniques during the client briefing process for improved client satisfaction in the UK construction industry, University of Salford, Salford 2017.
• [21] McGee R.W., Annie Chan: Three short stories written with ChatGPT, 2023, February 15, https://ssrn.com/abstract=4359403.
• [22] Biswas S.S., Potential use of Chat GPT in global warming, “Annals of Biomedical Engineering” 2023, Vol. 51, Iss. 6, 1126–1127, doi: 10.1007/s10439-023-03171-8.
• [23] Biswas S., Prospective role of ChatGPT in the military: According to ChatGPT, “Qeios” 2023, 1–19, doi: 10.32388/8wyyod.
• [24] ChatGPT, 2023, https://openai.com/blog/chatgpt [accessed: 16.03.2023].
• [25] Landgrebe J., Smith B., Making AI meaningful again, “Synthese” 2021, Vol. 198, No. 3, 2061–2081, doi: 10.1007/s11229-019-02192-y.
• [26] OpenAI, 2023, https://openai.com/ [accessed: 13.03.2023].
• [27] Caucheteux C., Gramfort A., King J.R., Deep language algorithms predict semantic comprehension from brain activity, “Scientific Reports” 2022, Vol. 12, No. 1, 1–10, doi: 10.1038/s41598-022-20460-9.
• [28] Aydın Ö., Karaarslan E., Is ChatGPT leading generative AI? What is beyond expectations?, “Academic Platform Journal of Engineering and Smart Systems” 2023, 11(3), 118–134, doi: 10.21541/apjess.1293702.
• [29] Floridi L., Chiriatti M., GPT-3: Its nature, scope, limits, and consequences, “Minds and Machines” 2020, Vol. 30, Iss. 4, 681–694, doi: 10.1007/s11023-020-09548-1.
• [30] McGee R.W., Who were the 10 best and 10 worst U.S . Presidents? The Opinion of ChatGPT (Artificial Intelligence), 2023, February, doi: 10.2139/ssrn.4367762.
• [31] Yang X., Li Y., Zhang X., Chen H., Cheng W., Exploring the limits of ChatGPT for query or aspect-based text summarization, “arXiv” 2023, February, doi: 10.48550/arXiv.2302.08081.
• [32] Fellow R., Liu A., Research methods for consrtuctions, Wiley-Blackwell, Hoboken 2008.
• [33] Yalçın M., Bozdayı A.M., Hakan E.M. , Cultural determinants within the design set up of kindergarten and preschool interiors: Assessment of four typologies in terms of their spatial formation, “MEGARON” 2017, Vol. 12, No. 1, 130–144, doi: 10.5505/megaron.2017.49469.
• [34] Sarioğlu-Erdoğdu G.P., Problems in housing research and comparative housing studies, “MEGARON” 2011, Vol. 6, No. 2, 71–78.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).

Identyfikatory

DOI

10.37190/arc230309