Abstract
Due to advances in technology, the topic “AI in HCI” is a growing research area with contributions from several research communities. To better understand the current and potentially future research activities, a workshop “AI in HCI” took place as part of the first AI in HCI conference. The intent of the workshop was twofold: to explore the research landscape of AI in HCI with current and potentially future research topics, as well as building the foundation for a community of international researchers in this area. The workshop was facilitated as a four and a half hour, remote, interactive workshop. 20 researchers attended the workshop. During the workshop, the participants brainstormed individual research topics which were grouped into 10 research categories. The participants assigned votes to the ten categories. The categories “Trust”, “Ethical AI” and “Human-Centered AI” received most votes. Afterwards the participants underwent a deep dive into the three top scored categories, elaborating per category on research questions, research approaches, research challenges, and beneficiaries. During the workshop on July 24 2020, only the topic “Trust” was elaborated. Two follow-up sessions elaborated the other two categories. This paper presents structure and results of the workshops, including the follow-up sessions and relates the results to other publications in this area. Moreover, further elaborating on the workshop results, this paper proposes a framework for Human-Centered AI for building trustworthy AI-enabled systems.
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AAAI Conference on Artificial Intelligence (AAAI), International Conference on Knowledge Discovery and Data Mining (ACM CDD), International Conference on Human Factors in Computing Systems (ACM CHI), Conference on Computer Vision and Pattern Recognition (IEEE CVPR), International Conference on Designing Interactive Systems (ACM DIS), European Conference on Computer Vision (ECCV), ACM/IEEE International Conference on Human Robot Interaction (HRI), International Conference on Multimodal Interaction (ACM ICMI), Conference on Computer Vision (IEEE ICCV), Neural information processing systems (NeurIPS), International Conference on Machine Learning (ICML), International Conference on Artificial Intelligence (IJCAI), International Conference on Intelligent Robots and Systems (IEEE IROS), International Conference on Intelligent User Interfaces (ACM IUI), ACM Symposium on User Interface Software and Technology (ACM UIST), International Conference on User Modeling, Adaptation and Personalization (ACM UMAP).
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References
McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AIMag. 27, 12–12 (2006). https://doi.org/10.1609/aimag.v27i4.1904
Crevier, D.: AI: The Tumultuous History of the Search for Artificial Intelligence. Basic Books, New York City (1993)
Weizenbaum, J.: Computer Power and Human Reason: From Judgment to Calculation. Freeman Press, New York City (1977)
EU Commission: White Paper on Artificial Intelligence—A European Approach to Excellence and Trust, COM (2020) 65 Final. European Commission, Brussels (2020)
Schwab, K.: This is the first commercial chair made using generative design. https://www.fastcompany.com/90334218/this-is-the-first-commercial-product-made-using-generative-design. Accessed 26 Jan 2021
Frow, P., Nenonen, S., Payne, A., Storbacka, K.: Managing co-creation design: a strategic approach to innovation. Br. J. Manage. 26, 463–483 (2015). https://doi.org/10.1111/1467-8551.12087
Vilone, G., Longo, L.: Explainable Artificial Intelligence: a Systematic Review (2020). arXiv:2006.00093
Adadi, A., Berrada, M.: Peeking inside the black-box: a survey on explainable artificial intelligence (XAI). IEEE Access. 6, 52138–52160 (2018). https://doi.org/10.1109/ACCESS.2018.2870052
Arrieta, A.B., et al.: Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion. 58, 82–115 (2020). https://doi.org/10.1016/j.inffus.2019.12.012
Phillips, P.J., Hahn, C.A., Fontana, P.C., Broniatowski, D.A., Przybocki, M.A.: Four principles of explainable. Artif. Intell. (2020). https://doi.org/10.6028/NIST.IR.8312-draft
Tjoa, E., Guan, C.: A survey on explainable artificial intelligence (XAI): toward medical XAI. IEEE Trans. Neural Netw. Learn. Syst. 1–21 (2020). https://doi.org/10.1109/TNNLS.2020.3027314.
Thieme, A., Belgrave, D., Doherty, G.: Machine Learning in Mental Health: A Systematic Review of the HCI Literature to Support the Development of Effective and Implementable ML Systems. ACM Trans. Comput. Hum. Interact. 27, 34:1–34:53 (2020). https://doi.org/10.1145/3398069
Mohseni, S., Zarei, N., Ragan, E.D.: A multidisciplinary survey and framework for design and evaluation of explainable AI systems (2020). arXiv:1811.11839
Miller, T.: Explanation in Artificial Intelligence: Insights from the Social Sciences (2018). arXiv:1706.07269
OECD Principles on Artificial Intelligence - Organisation for Economic Co-operation and Development. https://www.oecd.org/going-digital/ai/principles/. Accessed 27 Jan 2021
Bird, E., Fox-Skelly, J., Jenner, N., Larbey, R., Weitkamp, E., Winfield, A.: The ethics of artificial intelligence: Issues and initiatives|Panel for the Future of Science and Technology (STOA)|European Parliament. https://www.europarl.europa.eu/stoa/en/document/EPRS_STU(2020)634452. Accessed 27 Jan 2021
Hagerty, A., Rubinov, I.: Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence (2019). arXiv:1907.07892
Jobin, A., Ienca, M., Vayena, E.: The global landscape of AI ethics guidelines. Nat. Mach. Intell. 1, 389–399 (2019). https://doi.org/10.1038/s42256-019-0088-2
Riedl, M.O.: Human-centered artificial intelligence and machine learning. Hum. Behav. Emerg. Technol. 1, 33–36 (2019). https://doi.org/10.1002/hbe2.117
Amershi, S., et al.: Guidelines for human-AI interaction. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–13. Association for Computing Machinery, Glasgow, Scotland, Uk (2019). https://doi.org/10.1145/3290605.3300233.
IBM Design for AI. https://www.ibm.com/design/ai/. Accessed 27 Jan 2021
People + AI Research. https://pair.withgoogle.com. Accessed 27 Jan 2021
Xu, W.: Toward human-centered AI: a perspective from human-computer interaction. Interactions. 26, 42–46 (2019). https://doi.org/10.1145/3328485
Shneiderman, B.: Human-centered artificial intelligence: reliable, safe & trustworthy. Int. J. Hum.Comput. Interact. 36, 495–504 (2020). https://doi.org/10.1080/10447318.2020.1741118
Margetis, G., Ntoa, S., Antona, M., Stephanidis, C.: Human-centered design of artificial intelligence. In: Salvendy, G., Karwowski, W. (Eds.) Handbook of Human Factors and Ergonomics, 5th Edition, Wiley (2021) (to appear)
Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., Pedreschi, D.: A survey of methods for explaining black box models. ACM Comput. Surv. 51(5), 1–42 (2019). https://doi.org/10.1145/3236009
Acknowledgements
The authors would like to thank the workshop participants for their valuable contributions (alphabetic order by first name): Al-Batool Al-Ghamdi (University of Jeddah, Saudi Arabia), Alice Baird (EIHW - University Augsburg, Germany), Brian Stanton (National Institute of Standards and Technology, USA), Christoph Brand (Siemens Technology, USA), Christof Budnik (Siemens Technology, USA), Esma Aïmeur (University of Montreal, Canada), Fatimah Alsayoud (Ryerson University, Canada), George Margetis (FORTH, Greece), Giuliana Vitiello (Università di Salerno, Italy), Jan Conrad (University of Applied Sciences Kaiserslautern, Germany), Kaveh Bazargan (UX24/7, United Kingdom), Margherιta Antona (FORTH, Greece), Marianna Di Gregorio (Università di Salerno, Italy), Ming Qian (Pathfinders Translation and Interpretation Research, USA), Nouf Aj (University of Jeddah, Saudi Arabia), Roberto Vezzani (University of Modena and Reggio Emilia, Italy), Sebastian Korfmacher (Commission for Occupational Health and Safety and Standardization (KAN), Germany), Siyu Zhao (Siemens Technology, USA), Xiang-yuan Yan (Beijing University of Posts and Telecommunications, China), XiaoLing Li (Xi'an Jiaotong University, China).
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Degen, H., Ntoa, S. (2021). From a Workshop to a Framework for Human-Centered Artificial Intelligence. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2021. Lecture Notes in Computer Science(), vol 12797. Springer, Cham. https://doi.org/10.1007/978-3-030-77772-2_11
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