Główne obszary badań związanych ze sztuczną inteligencją w piśmiennictwie z zakresu architektury informacji i projektowania UX
DOI:
https://doi.org/10.24917/20811861.23.22Słowa kluczowe:
analiza treści, architektura informacji, obszary badań, projektowanie UX, przegląd piśmiennictwa, sztuczna inteligencjaAbstrakt
Cel/Teza: Obserwowany w ostatnich latach szybki rozwój nowych technologii sztucznej inteligencji (AI) wywołał dyskusje o przyszłości architektury informacji (IA) i pokrewnych dyscyplin projektowych. W artykule podjęto próbę weryfikacji tezy, że rozwój AI w istotny sposób kształtuje pole badań współczesnej architektury informacji i projektowania UX, co prowadzi do tworzenia się nowych obszarów badań oraz identyfikacji najważniejszych z nich.
Metody badań: Jako podstawę identyfikacji i charakterystyki tych obszarów wykorzystano ilościową analizę asocjacji słów kluczowych oraz podejście jakościowe, w którym zastosowano metodę krytycznej analizy treści oraz systematycznego przeglądu piśmiennictwa. Analizom poddano piśmiennictwo przedmiotu zarejestrowane w bazie Scopus, obejmujące publikacje wydane w latach 2019–2024 reprezentujące tematy zaindeksowane słowami kluczowymi najczęściej używanymi i najsilniej powiązanymi oraz publikacje najczęściej cytowane.
Wnioski: Analiza pozwoliła wyodrębnić sześć obszarów problemowych, które można uznać za główne obszary oddziaływania rozwijającej się technologii AI na badania w zakresie szeroko rozumianej architektury informacji: (1) aplikacje AI wspierające projektowanie IA i UX; (2) projektowanie aplikacji i serwisów sieciowych z funkcjonalnościami opartymi na AI; (3) wykorzystanie IA do organizacji danych dla AI/ML/DL; (4) edukacja projektantów IA i UX w zakresie AI; (5) interakcja człowieka z AI, wytłumaczalna AI i human-centered AI; (6) podstawy teoretyczne i metodologia projektowania IA, UX i inteligentnych produktów cyfrowych.
Bibliografia
Agrawal S.S., Panchal S.B., The food app – fair and equal access to free food for anyone in need, [w:] Proceedings of IDC 2023 – 22nd Annual ACM Interaction Design and Children Conference: Rediscovering Childhood, ACM, New York 2023, s. 435-438, https://doi.org/10.1145/3585088.3595282.
Bhale S., Enhancing value proposition through AI strategy: A case-study on a targeted application of AR in field support, [w:] ACM International Conference Series. Proceedings of the 10th International Conference on E-Education, E-Business, E-Management and E-Learning, IC4E 2019, s. 453–457, https://doi.org/10.1145/3306500.3306576.
Bharat K., Cardelli L., Migratory applications, [w:] Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, Berlin–Heidelberg 1997, vol. 1222, s. 131–148.
Binder Ch., Neureiter Ch., Lüder A., Towards a domain-specific information architecture enabling the investigation and optimization of flexible production systems by utilizing artificial intelligence, „International Journal of Advanced Manufacturing Technology” 2022, vol. 123, no. 1–2, s. 49–81, https://doi.org/10.1007/s00170-022-10141-2.
Borsci S., Malizia A., Schmettow M., van der Velde F., Tariverdiyeva G., Balaji D., Chamberlain A., The chatbot usability scale: the design and pilot of a usability scale for interaction with AI-based conversational agents, „Personal and Ubiquitous Computing” 2022, vol. 26, no. 1, s. 95–119, https://doi.org/10.1007/s00779-021-01582-9.
Brennen A., What do people really want when they say they want “explainable AI?” we asked 60 stakeholders, [w:] Conference on Human Factors in Computing Systems – Proceedings 2020, ACM, New York 2020, art. 3383047, https://doi.org/10.1145/3334480.3383047.
Colombo S., Costa C., Can designers take the driver’s seat? A new human-centered process to design with data and machine learning,„Design Journal” 2024, vol. 27, no. 1, s. 7–29, https://doi.org/10.1080/14606925.2023.2279835.
Coronado E., Mastrogiovanni F., Indurkhya B., Venture G., Visual programming environments for end-user development of intelligent and social robots, a systematic review, „Journal of Computer Languages” 2020, vol. 58, art. 100970, https://doi.org/10.1016/j.cola.2020.100970.
Deka B., Huang Z., Kumar R., ERICA: Interaction mining mobile apps, [w:] UIST 2016 – Proceedings of the 29th Annual Symposium on User Interface Software and Technology, ACM, New York 2016, s. 767–776, https://doi.org/10.1145/2984511.29845.
Dillon A., Information architecture in JASIST: Just where did we come from?, „Journal of the American Society for Information Science and Technology” 2002, vol. 53, no. 10, s. 821–823, https://doi.org/10.1002/asi.10090.
Dove G., Halskov K., Forlizzi J., Zimmerman J., UX design innovation: Challenges for working with machine learning as a design material, [w:] Conference on Human Factors in Computing Systems – Proceedings, ACM, New York 2017, s. 278–288, https://doi.org/10.1145/3025453.3025739.
Earley S., There is no AI without IA, „IT Professional” 2016, vol. 18 no. 3, s. 58–64, https://doi.org/10.1109/MITP.2016.43.
Fairstein R., Banade G., Gal K., Participatory budgeting designs for the real world, [w:] Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington 2023, vol. 37, s. 5633–5640, https://doi.org/10.1609/aaai.v37i5.25699.
Fan X., Chao D., Zhang Z., Wang D., Li X., Tian F., Utilization of self-diagnosis health chatbots in real-world settings: Case study, „Journal of Medical Internet Research” 2021, vol. 23 no. 1, art. e19928, https://doi.org/10.2196/19928.
Ferreira J.J., Monteiro M.S., What Are People Doing About XAI User Experience? A Survey on AI Explainability Research and Practice, [w:] Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, Cham 2020, s. 56–73, https://doi.org/10.1007/978-3-030-49760-6_4.
Flasiński M., Wstęp do sztucznej inteligencji, Warszawa 2011.
Flechtner R., Stankowski A., AI is not a wildcard: Challenges for integrating AI into the design curriculum, [w:] ACM International Conference Proceedings Series, ACM, New York 2023, s. 72–77, https://doi.org/10.1145/3587399.3587410.
Fouad H.Y, Raz A.K., Llinas J., Lawless W.F., Mittu R., Finding the path toward design of synergistic human-centered complex systems, [w:] Engineering Artificially Intelligent Systems, Lecture Notes in Computer Science, vol. 13000, eds. W.F. Lawless, J. Llinas, D.A. Sofge, R. Mittu, Springer, Cham 2021, s. 73–89, https://doi.org/10.1007/978-3-030-89385-9_5.
Gheţa I., Heizmann M., Belkin A., Beyerer J., World modeling for autonomous systems, [w:] Advances in Artificial Intelligence. KI 2010, Lecture Notes in Computer Science, vol. 6359, Springer, Berlin–Heidelberg 2010, s. 176–183, https://doi.org/10.1007/978-3-642-16111-7_20.
Grigera J., Espada J.P., Rossi G., AI in user interface design and evaluation, „IT Professional” 2023, vol. 25, no. 2, s. 20–22, https://doi.org/10.1109/MITP.2023.3267139.
Kaplan J., Generatywna AI. Wszystko co warto wiedzieć, tłum. A. Adamczyk-Karwowska, Warszawa 2025.
Kehal I., There is no AI without IA, AI Automation, 10.07.2019, [on-line:] https://medium.com/aiautomation/theres-no-ai-without-ia-9a4b6b2ce4c8 – 5.06.2024.
Kim D., Song Y., Kim S., Lee S., Wu Y., Shin J., Lee D., How should the result of artificial intelligence be explained to users? – Research on consumer preferences in user-centered explainable artificial intelligence, „Technical Forecasting and Social Change” 2023, no. 188, art. 122343, https://doi.org/10.1016/j.techfore.2023.122343.
Knearem T., Khwaja M., Gao Y., Bentley F., Kilman-Silver C.E., Exploring the future of design tooling: The role of artificial intelligence in tools for user experience professionals, [w:] Conference on Human Factors in Computing Systems – Proceedings. CHI 2023, ACM, New York 2023, https://doi.org/10.1145/3544549.3573874.
Krämer S., Mind, Symbolism, Formalism: Is Leibniz a Precursor of Artificial Intelligence?, „Knowledge Organization” 1996, vol. 23, no. 2, s. 83–87.
Kuroki Júnior G.H.J., Gottschlag-Duque C., Information architecture applied on natural language processing: a proposal Information Science contributions on data preprocessing for training and learning of artificial neural networks, „Revista Digital de Biblioteconomia e Ciencia da Informacao” 2023, no. 21, art. e023002, https://doi.org/10.20396/rdci.v21i00.8671396/30919.
Kuroki Júnior G.H., Gottschlag-Duque C., Multimodal Information Architecture: contribution on Artificial Intelligence developments | Arquitetura da Informação Multimodal: contribuições no desenvolvimento de Inteligência Artificial, „Transinformação” 2023, no. 35, art. e226729, https://doi.org/10.1590/23180889202335e226729.
Kuroki Júnior G.H., Gottschlag-Duque C., Data and Knowledge Organization for Natural Language Processing: Searching and Identifying Better Arrangements of Texts Based on Multimodal Information Architecture, „Sage Open” 2024, vol. 14, no. 1, https://doi.org/10.1177/21582440231177042.
Kuroki Júnior G.H., Gottschlag-Duque C., Towards Multimodal Information Architecture: A social-technical approach of artificial intelligence development in Inova HFA’s Electronic Health Record (EHR), [w:] Lecture Notes in Networks and Systems, Springer, Cham 2024, no. 825, s. 792–806, https://doi.org/10.1007/978-3031-47718-8_51.
Li D., Information reconstruction of accounting robot based on blockchain, [w:] Advances in Intelligent Systems and Computing, vol. 1147, Springer, Cham 2020, s. 102-108, https://doi.org/10.1007/978-3-030-43309-3_14.
Lowe D., Henderson-Sellers B., Gu A., Web extensions to UML: Using the MVC triad, [w:] Conceptual Modeling — ER 2002. ER 2002, Lecture Notes in Computer Science, vol. 2503, eds. S. Spaccapietra, S.T. March, Y. Kambayashi, Springer, Berlin–Heidelberg, 2002, s. 105–119, https://doi.org/10.1007/3-540-45816-6_18.
Lumpas R.V., Mitrovic A., Galster M., Malinen S., Peiris P., Holland J., Question-driven design process for XAI in Active Video Watching, [w:] 31st International Conference on Computers in Education, ICCE 2023 – Proceedings, Taoyuan: Asia-Pacific Society for Computers in Education, 2023, vol. 2, s. 878–880.
Madera C., Laurent A., The next information architecture evolution: The data lake wave, [w:] 8th International Conference on Management of Digital EcoSystems, MEDES 2016, ACM, New York 2016, s. 174–180, https://doi.org/10.1145/3012071.3012077.
Mahler M.L., Weisz J.D., Chilton L.B., Geyer W., Strobelt H., HAI-GEN 2023: 4th Workshop on Human-AI Co-Creation with Generative Models, [w:] International Conference on Intelligent User Interfaces, Proceedings IUI, CEUR, Sydney 2023, s. 190–192, https://doi.org/10.1145/3581754.3584166.
Marciszewski W., Leibniz Two Legacies. Their Implications for Knowledge Engineering, „Knowledge Organization” 1996, vol. 23, no. 2, s. 77–82.
McCarthy J., Minsky M.L., Rochester R., Shannon C.E, A proposal for the Dartmouth Summer Research Project on Artificial Intelligence, 31.08.1955, [on-line:] https://raysolomonoff.com/dartmouth/boxa/dart564props.pdf – 27.04.2025.
Mühlhoff R., Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning, „New Media and Society” 2020, vol. 22, no. 10, s. 1868–1884, https://doi.org/10.1177/1461444819885334.
Nadimi-Shahraki M.H., Taghian S., Mirjalili S., Faris H., MTDE: An effective multi-trial vector-based differential evolution algorithm and its applications for engineering design problems, „Applied Soft Computing Journal” 2020, vol. 97, art. 106761, https://doi.org/10.1016/j.asoc.2020.106761.
Padmasiri P., Kalutharage P., Jayawardhane N., Wickramarathne J., AI-driven user experience design: Exploring innovations and challenges in delivering tailored user experiences, [w:] Proceedings of ICITR 2023 – 8th International Conference on Information Technology Research: The Next Evolution in Digital Transformation, Colombo 2023, https://doi.org/10.1109/ICITR61062.2023.10382802.
Ramon Llull: From the Ars Magna to Artificial Intelligence, eds. A. Fidora, C. Sierra, Artificial Intelligence Research Institute, Barcelona 2011.
Rasing N., Janus S., Smalbrugge M., Koopmans R., Zuidema S., Usability of appbased clinical decision support system to monitor psychotropic drug prescribing appropriateness in dementia, „International Journal of Medical Informatics” 2023, no. 177, art. 105132, https://doi.org/10.1016/j.ijmedinf.2023.105132.
Resisting data colonialism. A practical intervention, Institute of Network Cultures, Amsterdam 2023.
Rice S.A., Resmini A., There is no AI without IA: In conversation with Carol Smith, [w:] Advances in Information Architecture. The Academics / Practitioners Round Table 2014–2019, eds. A. Resmini, S.A. Rice, B. Irizarry, Springer, Cham 2021, s. 223–229, https://doi.org/10.1007/978-3-030-63205-2.
Robbins D.E., Gurupur V., Tanik J., Information architecture of a clinical decision support system, [w:] Conference Proceedings – IEEE SouthastCon, Nashville, TN, IEEE 2011, s. 374–378, https://doi.org/10.1109/SECON.2011.5752969.
Russo C.J., Nicklaus D.J., Tong S.S., Initial user experience with an artificial intelligence program for the preliminary design of centrifugal compressors, [w:] Proceedings of the ASME Turbo Expo, vol. 1, art. V001T01A075. Anaheim 1987, https://doi.org/10.1115/87-GT-217.
Saboury B., Morris M., Siegel E., Future directions in artificial intelligence, „Radiology Clinics of North America” 2021, no. 59, s. 1085–1095, https://doi.org/10.1016/j.rcl.2021.07.008.
Shen S., Li B., Li S., Construction and application of a big data analysis platform for enterprise, [w:] ACM International Conference Proceedings Series. Proceedings of the 2019 3rd International Conference on Computer Science and Artificial Intelligence. ACM, New York 2019, s. 54–58, https://doi.org/10.1145/3374587.3374650.
Shneidrerman B., Tutorial: Human-centered AI: Reliable, Safe and Trustworthy, [w:] International Conference on Intelligent User Interfaces, Proceedings IUI, 26th International Conference on Intelligent User Interfaces, IUI 2021. ACM, New York 2021, s. 87–89, https://doi.org/10.1145/3397482.3453994.
Shneiderman B., Human-Centered AI, Oxford University Press, New York 2022, https://doi.org/10.1093/oso/9780192845290.001.0001.
Siddiqui M.-F., Kumar R., Interpreting the nature of rainfall with AI and big data models, [w:] Proceedings of International Conference on Intelligent Engineering and Management, IEEE 2020, s. 306–310, https://doi.org/10.1109/ICIEM48762.2020.9160322.
Sosińska-Kalata B., Relacje i wzajemne oddziaływanie między architekturą informacji i projektowaniem UX a sztuczną inteligencją. Analiza bibliometryczna, „Annales Universitatis Paedagogicae Cracoviensis Studia ad Bibliothecarum Scientiam Pertinentia” 2024, t. 22, s. 478–501, https://doi.org/10.24917/20811861.22.28.
Steiner M., Meiller D., Human in focus: evaluation with electro graphic methods and artificial intelligence, [w:] International Conference on Applied Computing 2023, AC 2023 and WWW/Internet 2023, IADIS Press, Funchal 2023, s. 227–232.
Subbu R., Hocaoglu C., Sanderson A.C., A virtual design environment using evolutionary agents, [w:] Proceedings – IEEE International Conference on Robotics and Automation, IEEE, Leuven 1998, vol. 1, s. 247–253, https://doi.org/10.1109/ROBOT.1998.676384.
Suphakul T., Senivongse T., Development of privacy design patterns based on privacy principles and UML, [w:] Proceedings – 18th IEEE/ACIS International Conference on Software Engineering, Artificial, Intelligence, Networking and Parallel/Distributed Computing, SNPD, IEEE, Kanazawa 2017, s. 369–375, art. 8022748, https://doi.org/10.1109/SNPD.2017.8022748.
Tandon S., Wang J., Surfacing AI explainability in enterprise product visual design to address user tech proficiency differences, [w:] CHI 2023: Conference on Human Factors in Computing Systems – Proceedings, ACM, New York 2023, art. 398, https://doi.org/10.1145/3544549.3573867.
Varshney K.R., Engineering safety in machine learning, [w:] 2016 Information Theory and Applications Workshop, ITA 2016, IEEE, La Jolla, CA, 2017, art. 7888195, https://doi.org/10.1109/ITA.2016.7888195.
Yadav N., Shankar R., Singh S.P., Impact of Industry 4.0/ICTs, Lean Six Sigma and quality management systems on organisational performance, „TQM Journal” 2020, vol. 32, no. 4, s. 815–835, https://doi.org/10.1108/TQM-10-2019-0251.
Yang Q., Scuito A., Zimmerman J., Forlizzi J., Steinfeld A., Investigating how experienced UX designers effectively work with machine learning, [w:] DIS 2018 – Proceedings of the 2018 Designing Interactive Systems Conference, ACM, New York 2018, s. 585–596, https://doi.org/10.1145/3196709.3196730.
Yang Q., Steinfeld A., Rosé C., Zimmerman J., Re-examining whether, why, and how human-AI interaction is uniquely difficult to design, [w:] Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, ACM, New York 2020, s. 1–13, art. 3376301, https://doi.org/10.1145/3313831.3376301.
Yang X.-S., Deb S., Fong S., He X., Zhao Y.-X., From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms, „Computer” 2016, vol. 49, no. 9, s. 52–59, https://doi.org/10.1109/MC.2016.292.
York E., Evaluating ChatGPT: Generative AI in UX design and Web development pedagogy, [w:] Proceedings of the 41st International Conference on Design of Communication, SIGDOC2023, ACM, New York 2023, s. 197–201, https://doi.org/10.1145/3615335.3623035.
Zuboff S., Wiek kapitalizmu inwigilacji. Walka o przyszłość ludzkości na nowej granicy władzy, Poznań 2020.
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