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Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps.
Brain writing for new product ideas: an alternative to brainstorming
Arthur B VanGundy. 1984 · 1984
Earlier work this paper cites.
Basics of Qualitative Research: Grounded Theory Techniques and Procedures
Anselm Strauss and Juliet M. Corbin. 1990 · 1990
Earlier work this paper cites.
Creating the invisible interface: (invited talk). In Proceedings of the 7th annual ACM symposium on User interface software and technology . 1
Mark Weiser. 1994 · 1994
Earlier work this paper cites.
Toward a critical technical practice: Lessons learned in trying to reform AI in Bowker
P Agre. 1997 · 1997
Earlier work this paper cites.
The Intellectual Challenge of CSCW: The Gap between Social Requirements and Technical Feasibility
Mark S. Ackerman. 2000 · 2000
Earlier work this paper cites.
Seamful Design and Ubicomp Infrastructure
Matthew Chalmers. 2003 · 2003
Earlier work this paper cites.
Seamful design: showing the seams in wearable computing. In 2003 IEE Eurowearable . 11–16
M. Chalmers, I. MacColl, and M. Bell. 2003 · 2003
Earlier work this paper cites.
Ambiguity as a resource for design. In Proceedings of the SIGCHI conference on Human factors in computing systems . 233–240
William W Gaver, Jacob Beaver, and Steve Benford. 2003 · 2003
Earlier work this paper cites.
Social Navigation and Seamful Design. In In Japanese Journal of Cognitive Science, Special Issue on Social Navigation . 171–181
Matthew Chalmers, Andreas Dieberger, Kristina Höök, and Åsa Rudström. 2004 · 2004
Earlier work this paper cites.
Seamful Design for Location-Based Mobile Games. In Entertainment Computing - ICEC 2005 , Fumio Kishino, Yoshifumi Kitamura, Hirokazu Kato, and Noriko Nagata (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 155–166
Gregor Broll and Steve Benford. 2005 · 2005
Earlier work this paper cites.
Scenario based design
Mary Beth Rosson and John M Carroll. 2009 · 2009
Earlier work this paper cites.
Anticipatory ethics for emerging technologies
Philip AE Brey. 2012 · 2012
Earlier work this paper cites.
Jugaad innovation: Think frugal, be flexible, generate breakthrough growth
Navi Radjou, Jaideep Prabhu, and Simone Ahuja. 2012 · 2012
Earlier work this paper cites.
A review of TRIZ, and its benefits and challenges in practice
Imoh M Ilevbare, David Probert, and Robert Phaal. 2013 · 2013
Earlier work this paper cites.
Theoretical foundations for the study of sociomateriality
Paul M Leonardi. 2013 · 2013
Earlier work this paper cites.
Constructing Grounded Theory (Introducing Qualitative Methods series) 2nd Edition
Kathy Charmaz. 2014 · 2014
Earlier work this paper cites.
Seamful spaces: Heterogeneous infrastructures in interaction
Janet Vertesi. 2014 · 2014
Earlier work this paper cites.
Using TRIZ to invent failures–concept and application to go beyond traditional FMEA
Christian M Thurnes, Frank Zeihsel, Svetlana Visnepolschi, and Frank Hallfell. 2015 · 2015
Earlier work this paper cites.
The mythos of model interpretability
Zachary C Lipton. 2016 · 2016
Earlier work this paper cites.
Applying seamful design in location-based mobile museum applications
Tommy Nilsson, Carl Hogsden, Charith Perera, Saeed Aghaee, David J Scruton, Andreas Lund, and Alan F Blackwell. 2016 · 2016
Earlier work this paper cites.
UX Design Innovation: Challenges for Working with Machine Learning as a Design Material. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI ’17) . Association for Computing Machinery, New York, NY, USA, 278–288
Graham Dove, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017 · 2017
Earlier work this paper cites.
Intelligence on Tap: Artificial Intelligence as a New Design Material
Lars Erik Holmquist. 2017 · 2017
Earlier work this paper cites.
Integrating User eXperience practices into software development processes: implications of the UX characteristics
Pariya Kashfi, Agneta Nilsson, and Robert Feldt. 2017 · 2017
Earlier work this paper cites.
Applying the anticipatory failure determination at a very early stage of a system’s development: overview and case study
Leszek Chybowski, Katarzyna Gawdzińska, and Valeri Souchkov. 2018 · 2018
Earlier work this paper cites.
Explaining explanations: An overview of interpretability of machine learning. In 2018 IEEE 5th International Conference on data science and advanced analytics (DSAA) . IEEE, 80–89
Leilani H Gilpin, David Bau, Ben Z Yuan, Ayesha Bajwa, Michael Specter, and Lalana Kagal. 2018 · 2018
Earlier work this paper cites.
A survey of methods for explaining black box models
Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Franco Turini, Fosca Giannotti, and Dino Pedreschi. 2018 · 2018
Earlier work this paper cites.
Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects
Samir Passi and Steven J. Jackson. 2018 · 2018
Earlier work this paper cites.
Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance
Gagan Bansal, Besmira Nushi, Ece Kamar, Walter S. Lasecki, Daniel S. Weld, and Eric Horvitz. 2019 · 2019
Earlier work this paper cites.
Responsible AI by design in practice
Richard Benjamins, Alberto Barbado, and Daniel Sierra. 2019 · 2019
Earlier work this paper cites.
Explaining models: an empirical study of how explanations impact fairness judgment. In Proceedings of the 24th international conference on intelligent user interfaces . 275–285
Jonathan Dodge, Q Vera Liao, Yunfeng Zhang, Rachel KE Bellamy, and Casey Dugan. 2019 · 2019
Earlier work this paper cites.
XAI—Explainable artificial intelligence
David Gunning, Mark Stefik, Jaesik Choi, Timothy Miller, Simone Stumpf, and Guang-Zhong Yang. 2019 · 2019
Earlier work this paper cites.
Improving fairness in machine learning systems: What do industry practitioners need?. In Proceedings of the 2019 CHI conference on human factors in computing systems . 1–16
Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miro Dudik, and Hanna Wallach. 2019 · 2019
Cited alongside, same era.
"Beautiful Seams": Strategic Revelations and Concealments. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19) . Association for Computing Machinery, New York, NY, USA, 1–14
Sarah Inman and David Ribes. 2019 · 2019
Cited alongside, same era.
Identifying the Intersections: User Experience + Research Scientist Collaboration in a Generative Machine Learning Interface. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI EA ’19) . Association for Computing Machinery, New York, NY, USA, 1–8
Claire Kayacik, Sherol Chen, Signe Noerly, Jess Holbrook, Adam Roberts, and Douglas Eck. 2019 · 2019
Cited alongside, same era.
Model cards for model reporting. In Proceedings of the conference on fairness, accountability, and transparency . 220–229
Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford. 2021 · 2021
Later among the works it cites.
Explainable active learning (xal) toward ai explanations as interfaces for machine teachers
Bhavya Ghai, Q Vera Liao, Yunfeng Zhang, Rachel Bellamy, and Klaus Mueller. 2021 · 2021
Later among the works it cites.
Do Explanations Help Users Detect Errors in Open-Domain QA? An Evaluation of Spoken vs. Visual Explanations. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 . Association for Computational Linguistics, Online, 1103–1116
Ana Valeria González, Gagan Bansal, Angela Fan, Yashar Mehdad, Robin Jia, and Srinivasan Iyer. 2021 · 2021
Later among the works it cites.
Planning for natural language failures with the ai playbook. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–11
Matthew K Hong, Adam Fourney, Derek DeBellis, and Saleema Amershi. 2021 · 2021
Later among the works it cites.
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Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. 2019 · 2019
Cited alongside, same era.
Problem Formulation and Fairness. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* ’19) . Association for Computing Machinery, New York, NY, USA, 39–48
Samir Passi and Solon Barocas. 2019 · 2019
Cited alongside, same era.
Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency . ACM, Atlanta GA USA, 59–68
Andrew D. Selbst, Danah Boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019 · 2019
Cited alongside, same era.
Designing theory-driven user-centric explainable AI. In Proceedings of the 2019 CHI conference on human factors in computing systems . 1–15
Danding Wang, Qian Yang, Ashraf Abdul, and Brian Y Lim. 2019 · 2019
Cited alongside, same era.
Designing for human rights in AI
Evgeni Aizenberg and Jeroen Van Den Hoven. 2020 · 2020
Cited alongside, same era.
Toward Responsible AI by Planning to Fail. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Virtual Event, CA, USA) (KDD ’20) . Association for Computing Machinery, New York, NY, USA, 3607
Saleema Amershi. 2020 · 2020
Cited alongside, same era.
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-López, Daniel Molina, Richard Benjamins, et al · 2020
Cited alongside, same era.
Human-centered explainable ai: Towards a reflective sociotechnical approach. In International Conference on Human-Computer Interaction . Springer, 449–466
Upol Ehsan and Mark O Riedl. 2020 · 2020
Cited alongside, same era.
Ores: Lowering barriers with participatory machine learning in wikipedia
Aaron Halfaker and R Stuart Geiger. 2020 · 2020
Cited alongside, same era.
Designing AI for trust and collaboration in time-constrained medical decisions: a sociotechnical lens. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–14
Maia Jacobs, Jeffrey He, Melanie F. Pradier, Barbara Lam, Andrew C Ahn, Thomas H McCoy, Roy H Perlis, Finale Doshi-Velez, and Krzysztof Z Gajos. 2021 · 2021
Later among the works it cites.
Algorithmic recourse: from counterfactual explanations to interventions. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency . 353–362
Amir-Hossein Karimi, Bernhard Schölkopf, and Isabel Valera. 2021 · 2021
Later among the works it cites.
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences
Q Vera Liao and Kush R Varshney. 2021 · 2021
Later among the works it cites.
Conceptualising contestability: Perspectives on contesting algorithmic decisions
Henrietta Lyons, Eduardo Velloso, and Tim Miller. 2021 · 2021
Later among the works it cites.
Algorithmic Impact Assessments and Accountability: The Co-Construction of Impacts. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (Virtual Event, Canada) (FAccT ’21) . Association for Computing Machinery, New York, NY, USA, 735–746
Jacob Metcalf, Emanuel Moss, Elizabeth Anne Watkins, Ranjit Singh, and Madeleine Clare Elish. 2021 · 2021
Later among the works it cites.
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML. In 26th International Conference on Intelligent User Interfaces . 170–174
Shweta Narkar, Yunfeng Zhang, Q Vera Liao, Dakuo Wang, and Justin D Weisz. 2021 · 2021
Later among the works it cites.
Making Data Work: The Human and Organizational Lifeworlds of Data Science Practices
Samir Passi. 2021 · 2021
Later among the works it cites.
Manipulating and measuring model interpretability. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–52
Forough Poursabzi-Sangdeh, Daniel G Goldstein, Jake M Hofman, Jennifer Wortman Wortman Vaughan, and Hanna Wallach. 2021 · 2021
Later among the works it cites.
Where Responsible AI Meets Reality: Practitioner Perspectives on Enablers for Shifting Organizational Practices
Bogdana Rakova, Jingying Yang, Henriette Cramer, and Rumman Chowdhury. 2021a · 2021
Later among the works it cites.
Where responsible AI meets reality: Practitioner perspectives on enablers for shifting organizational practices
Bogdana Rakova, Jingying Yang, Henriette Cramer, and Rumman Chowdhury. 2021b · 2021
Later among the works it cites.
Responsible AI: Bridging from ethics to practice
Ben Shneiderman. 2021 · 2021
Later among the works it cites.
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–16
Harini Suresh, Steven R Gomez, Kevin K Nam, and Arvind Satyanarayan. 2021 · 2021
Later among the works it cites.
Visual, textual or hybrid: the effect of user expertise on different explanations. In 26th International Conference on Intelligent User Interfaces . 109–119
Maxwell Szymanski, Martijn Millecamp, and Katrien Verbert. 2021 · 2021
Later among the works it cites.
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits
Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein, and Haiyi Zhu. 2022 · 2022
Closest in time.
The Algorithmic Imprint. In 2022 ACM Conference on Fairness, Accountability, and Transparency . 1305–1317
Upol Ehsan, Ranjit Singh, Jacob Metcalf, and Mark Riedl. 2022 · 2022
Closest in time.
Understanding Machine Learning Practitioners’ Data Documentation Perceptions, Needs, Challenges, and Desiderata
Amy Heger, Liz B. Marquis, Mihaela Vorvoreanu, Hanna Wallach, and Jennifer W. Vaughan. 2022 · 2022
Closest in time.
Undoing Seamlessness: Exploring Seams for Critical Visualization. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI EA ’22) . Association for Computing Machinery, New York, NY, USA, Article 364, 7 pages
Nicole Hengesbach. 2022 · 2022
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Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory
Harmanpreet Kaur, Eytan Adar, Eric Gilbert, and Cliff Lampe. 2022 · 2022
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Q Vera Liao, Yunfeng Zhang, Ronny Luss, Finale Doshi-Velez, and Amit Dhurandhar. 2022 · 2022
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Assessing the Fairness of AI Systems: AI Practitioners’ Processes, Challenges, and Needs for Support
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Seamless Visions, Seamful Realities: Anticipating Rural Infrastructural Fragility in Early Design of Digital Agriculture. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22) . Association for Computing Machinery, New York, NY, USA, Article 451, 15 pages
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Identifying Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
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