Abstract
Innovation is a team sport that requires interdisciplinary collaboration. This study discusses how design thinking methods can be adapted to support such collaborative AI innovation and Human centred AI (HCAI). We propose an enhancement to the traditional double diamond framework, by adding a notion of “data discovery” alongside problem discovery. Further we propose the use of “data user stories” to not only communicate user tasks and user goals, but also document input and output data of a given process.
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Axure RP, http://axure.com.
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Figma, http://figma.com.
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Jupyter, http://jupyter.org.
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Streamlit, http://streamlit.io.
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Shiny, http://shiny.rstudio.com.
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OptimalWorkshop, https://www.optimalworkshop.com.
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UserZoom, https://www.userzoom.com.
References
Tschimmel, K.: Design thinking as an effective toolkit for innovation. In: ISPIM Conference Proceedings, page 1. The International Society for Professional Innovation Management (ISPIM) (2012)
Ergonomics of human-system interaction - Part 110. Standard, International Organization for Standardization, Geneva, CH, March 2020
Stackowiak, K.: Design thinking in software and AI projects: proving ideas through rapid prototyping. In: Design Thinking in Software and AI Projects: Proving Ideas Through Rapid Prototyping (2020)
Shneiderman, B.: Human-Centered AI. Oxford University Press, Oxford (2022)
Gillies, M., et al.: Human-centred machine learning. In: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, CHI EA 2016, pp. 3558–3565. Association for Computing Machinery, New York, NY, USA (2016)
Amershi, S., et al.: Guidelines for human-AI interaction. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019, pp.. 1–13. Association for Computing Machinery, New York, NY, USA (2019)
Vera Liao, Q., Gruen, D., Miller, S.: Questioning the AI: informing design practices for explainable AI user experiences. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–15. ACM, Honolulu HI USA, April 2020
Sanchez, T., Caramiaux, B., Françoise, J., Bevilacqua, F., Mackay, W.: How do people train a machine? Strategies and (Mis)understandings. In: CSCW 2021 - The 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing, Virtual, United States, October 2021
Shneiderman, B.: Human-centered artificial intelligence: three fresh ideas. AIS Trans. Human Comput. Interact. 12, 109–124 (2020)
Maimon, O., Rokach, L.: Data Mining and Knowledge Discovery Handbook, 2nd edn. Springer, New York (2010). https://doi.org/10.1007/b107408
Shearer, C.: The CRISP-DM model: the new blueprint for data mining. J. Data Warehous. 5(4), 13–22 (2000)
Norman, D.A.: User Centered System Design: New Perspectives on Human-computer Interaction. CRC Press, Cambridge (1986)
British Design Council: What is the framework for innovation? Design council’s evolved double diamond. (2004). Accessed 30 May 2022
Ishikawa, F., Yoshioka, N.: How do engineers perceive difficulties in engineering of machine-learning systems? - questionnaire survey. In: 2019 IEEE/ACM Joint 7th International Workshop on Conducting Empirical Studies in Industry (CESI) and 6th International Workshop on Software Engineering Research and Industrial Practice (SER IP), pp. 2–9 (2019)
Vogelsang, A., Borg, M.: Requirements engineering for machine learning: perspectives from data scientists. CoRR, abs/1908.04674 (2019)
Lucassen, G., Keuken, M., Dalpiaz, F., Brinkkemper, S., Sloof, G., Schlingmann, J.: Jobs-to-be-Done Oriented Requirements Engineering: A Method for Defining Job Stories, pp. 227–243, March 2018
Schleith, J., Norkute, M., Mikhail, M., Tsar, D.: Cognitive strategies prompts: creativity triggers for human centered AI opportunity detection. In: Creativity and Cognition (C &C 2022), Venice, Italy (2022)
The Britannica Dictionary. Data
Villamizar, H., Escovedo, T., Kalinowski, M.: Requirements engineering for machine learning: a systematic mapping study. In: 2021 47th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), pp. 29–36 (2021)
Kostova, B., Gurses, S., Wegmann, A.: On the interplay between requirements, engineering, and artificial intelligence. In: Sabetzadeh, M., (eds.) et al. Joint Proceedings of REFSQ-2020 Workshops, Doctoral Symposium, Live Studies Track, and Poster Track co-located with the 26th International Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2020), Pisa, Italy, March 24, 2020, vol. 2584, CEUR Workshop Proceedings. CEUR-WS.org (2020)
Maiden, N., Jones, S., Karlsen, I.K., Neill, .R, Zachos, K., Milne, A.: Requirements engineering as creative problem solving: a research agenda for idea finding. In: 2010 18th IEEE International on Requirements Engineering Conference (RE), pp. 57–66. IEEE Computer Society (2010)
Patton, J., Economy, P.: User Story Mapping: Discover the Whole Story, Build the Right Product. O’Reilly Media, Sebastopol (2014)
Vivekananthamoorthy, N., Sankar, S.: Lean six sigma. In: Coskun, A. (ed.) Six Sigma. IntechOpen, Rijeka (2011)
The Prototypers Dilemma [EUROIA 2018]. https://www.slideshare.net/jbaeck/the-prototypers-dilemma-euroia-2018-117320114. Accessed 30 May 2022
Hanington, B., Martin, B.: Universal Methods of Design Expanded and Revised. Rockport Publishers, Beverly (2019)
Jupyter. http://jupyter.org. Accessed 30 May 2022
Schleith, J.: Human-centered evaluation of dynamic content (2021)
Arora, M., Kanjilal, U., Varshney, D.: Evaluation of information retrieval: precision and recall. Int. J. Indian Cult. Bus. Manage. 12(2), 224–236 (2016)
Johannes Schleith, Nina Hristozova, Brian Chechmanek, Carolyn Bussey, and Leszek Michalak. Noise over fear of missing out. In Carolin Wienrich, Philipp Wintersberger, and Benjamin Weyers, editors, Mensch und Computer 2021 - Workshopband, Bonn, 2021. Gesellschaft für Informatik e.V
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Schleith, J., Tsar, D. (2022). Triple Diamond Design Process. In: Kurosu, M., et al. HCI International 2022 - Late Breaking Papers. Design, User Experience and Interaction. HCII 2022. Lecture Notes in Computer Science, vol 13516. Springer, Cham. https://doi.org/10.1007/978-3-031-17615-9_9
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