Module 1 - Articles - mandatory
Grudin, Jonathan. AI and HCI: Two Fields Divided by a Common Focus. AI magazine 30, no 4 (September 18, 2009).
https://aaai.org/ojs/index.php/aimagazine/article/view/2271
Dautenhahn, K., 2018. Some Brief Thoughts on the Past and Future of Human-Robot Interaction. ACM Trans. Hum.-Robot Interact. 7, 4:1–4:3.
https://dl.acm.org/citation.cfm?id=3209769
Thrun, S., 2004. Toward a Framework for Human-robot Interaction. Hum.-Comput. Interact. 19, 9–24.
https://www.tandfonline.com/doi/pdf/10.1080/07370024.2004.9667338
Schulz, T., Herstad, J., & Torresen, J. (2018). Classifying Human and
Robot Movement at Home and Implementing Robot Movement
Using the Slow In, Slow Out Animation Principle. International
Journal on Advances in Intelligent Systems, 11, 234–244.
Norman, D (1990). The problem of automation: Inappropirate feedback and interaction, not over-automation. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, Vol. 327, No. 1241, Human Factors in Hazardous Situations (Apr. 12, 1990), pp. 585-593 (9 pages)
https://www.jstor.org/stable/55330?seq=9#metadata_info_tab_contents
Verne, G, Bratteteig, 2018, Does AI make PD obsolete?; exploring challenges from Artificial Intelligence to Participatory design,
https://dl.acm.org/citation.cfm?id=3210646
Module 1 books; check them out. Not mandatory reading;)
Agre, P.E., 1997. Computation and Human Experience. Cambridge University Press, New York, NY, USA.
Module 1 - films/video (check them out) - not mandatory viewing;)
Plug and Pray; documentary with Weizenbaum and others.
Module 2 (Design of interaction with AI) – articles – mandatory
Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., ... & Teevan, J. (2019). Guidelines for human-AI interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (paper no. 3). ACM. (https://www.microsoft.com/en-us/research/uploads/prod/2019/01/Guidelines-for-Human-AI-Interaction-camera-ready.pdf)
Kocielnik, R., Amershi, S., & Bennett, P. N. (2019). Will You Accept an Imperfect AI?: Exploring Designs for Adjusting End-user Expectations of AI Systems. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (paper no. 411). ACM. (https://www.microsoft.com/en-us/research/uploads/prod/2019/01/chi19_kocielnik_et_al.pdf)
Liao, Q. V., Gruen, D., & Miller, S. (2020, April). Questioning the AI: Informing Design Practices for Explainable AI User Experiences. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (paper no. 463). ACM. (https://dl.acm.org/doi/abs/10.1145/3313831.3376590)
Yang, Q., Steinfeld, A., Rosé, C., & Zimmerman, J. (2020, April). Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. In Proceedings of the 2020 chi conference on human factors in computing systems (Paper no. 164). (https://dl.acm.org/doi/abs/10.1145/3313831.3376301)
Module 2 (Design of interaction with AI) – articles – optional / suggested reading
F?lstad, A., & Brandtz?g, P. B. (2017). Chatbots and the new world of HCI. interactions, 24(4), 38-42. (https://dl.acm.org/citation.cfm?id=3085558)
Luger, E., & Sellen, A. (2016). Like having a really bad PA: the gulf between user expectation and experience of conversational agents. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (pp. 5286-5297). ACM. (https://www.microsoft.com/en-us/research/wp-content/uploads/2016/08/p5286-luger.pdf)
Carter, S., & Nielsen, M. (2017). Using artificial intelligence to augment human intelligence. Distill, 2(12), e9. (https://distill.pub/2017/aia/)
Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: humans and AI are joining forces. Harvard Business Review, 96(4), 114-123. (https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-forces)
Frey, C. B., & Osborne, M. A. (2017). The future of employment: how susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280. (https://www.sciencedirect.com/science/article/pii/S0040162516302244)
Module 2 (Design of interaction with AI) – books – optional / suggested reading
Hall, E. (2018). Conversational design. A Book Apart
McAfee, A., & Brynjulfsson, E. (2016). Machine, Platform, Crowd. Harnessing Our Digital Future. Norton & Company.
Noessel, C. (2017). Designing Agentive technology: AI that works for people. Rosenfeld Media.
Module 3 (Living and working with AI) - articles -mandatory
Hagras, H., Toward Human-Understandable, Explainable AI, Computer, 51, 9, 2018, 28- 36 https://ieeexplore.ieee.org/document/8481251
Phillips, E., Ososky, S., Swigert, B. and Jentsch, F. Human-animal teams as an analog for future human-robot teams, Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol 56, Issue 1, (2016) pp. 1553 – 1557
Shneiderman, B., Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy, arXiv.org (February 23, 2020). https://arxiv.org/abs/2002.04087v1 (Extract from forthcoming book by the same title)
Smith-Renner, A., Fan, R., Birchfield, M., Wu, T., Boyd-Graber, J., Weld, D.S., and Findlater. L. 2020. No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20). Association for Computing Machinery, New York, NY, USA, 1–13. DOI: https://doi.org/10.1145/3313831.3376624
Module 3 (Living and working with AI) – articles optional /suggested reading
Buolamwini, J. and Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, in PMLR 81:77-91 http://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf
De-Arteaga, M., Fogliato, R., and Chouldechova. A., 2020. A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20). Association for Computing Machinery, New York, NY, USA, 1–12. DOI: https://doi.org/10.1145/3313831.3376638
Herna?ndez-Orallo, Evaluation in artificial intelligence: from task-oriented to ability-oriented measurement, J. Artif Intell Rev (2017) 48: 397. https://dl.acm.org/doi/10.1007/s10462-016- 9505-7
Lindblom J., Andreasson R. (2016) Current Challenges for UX Evaluation of Human-Robot Interaction. In: Schlick C., Trzcielin?ski S. (eds) Advances in Ergonomics of Manufacturing: Managing the Enterprise of the Future. Advances in Intelligent Systems and Computing, vol 490. Springer, Cham. DOI: https://doi.org/10.1007/978-3-319-41697-7_24
Maroengsit, W. et al. (2019) A Survey on Evaluating Methods for Chatbots., ICIET 2019
https://doi.org/10.1145/3323771.3323824
Jain M. et al. (2018) Evaluating and Informing the Design of Chatbots. In Proceedings of the 2018 Designing Interactive Systems Conference (DIS '18). Association for Computing Machinery, New York, NY, USA, 895–906. DOI:https://doi.org/10.1145/3196709.3196735
Module 3 (Living and working with AI) – books optional /suggested reading
Endsley, Mica R. Designing for Situation Awareness: An Approach to User-Centered Design, Second Edition CRC Press. 2011 (chapters 2 and 10)
Hosanagar, K. A human's guide to machine intelligence, Viking, 2019 (chapters 7- 10)
Module 3 (Living and working with AI) – film (check it out) not mandatory
iHUMAN documentary by Tonje Hessen Schei https://tv.nrk.no/program/KOID75003817