Realizing AI in healthcare: challenges appearing in the wild

Tariq Osman Andersen; Francisco  Nunes; Lauren  Wilcox; Elizabeth  Kaziunas; Stina Matthiesen; Farah Magrabi

doi:10.1145/3411763.3441347

Realizing AI in healthcare: challenges appearing in the wild

Tariq Osman Andersen^*, Francisco Nunes^*, Lauren Wilcox, Elizabeth Kaziunas, Stina Matthiesen, Farah Magrabi^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

5 Citations (Scopus)

Abstract

The last several years have shown a strong growth of Artificial Intelligence (AI) technologies with promising results for many areas of healthcare. HCI has contributed to these discussions, mainly with studies on explainability of advanced algorithms. However, there are only few AI-systems based on machine learning algorithms that make it to the real world and everyday care. This challenging move has been named the “last mile” of AI in healthcare, emphasizing the sociotechnical uncertainties and unforeseen learnings from involving users in the design or use of AI-based systems. The aim of this workshop is to set the stage for a new wave of HCI research that accounts for and begins to develop new insights, concepts, and methods, for transitioning from development to implementation and use of AI in healthcare. Participants are invited to collaboratively define an HCI research agenda focused on healthcare AI in the wild, which will require examining end-user engagements and questioning underlying concepts of AI in healthcare.

Original language	English
Title of host publication	CHI EA '21
Subtitle of host publication	extended abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
Editors	Yoshifumi Kitamura, Aaron Quigley, Katherine Isbister, Takeo Igarashi
Place of Publication	New York, NY
Publisher	Association for Computing Machinery (ACM)
Number of pages	5
ISBN (Electronic)	9781450380959
DOIs	https://doi.org/10.1145/3411763.3441347
Publication status	Published - 8 May 2021
Event	2021 CHI Conference on Human Factors in Computing Systems - Virtual event, Yokohama, Japan Duration: 8 May 2021 → 13 May 2021

Conference

Conference	2021 CHI Conference on Human Factors in Computing Systems
Abbreviated title	CHI 2021
Country/Territory	Japan
City	Yokohama
Period	8/05/21 → 13/05/21

Keywords

artificial intelligence
human computer interaction

Access to Document

10.1145/3411763.3441347

Cite this

Osman Andersen, T., Nunes, F., Wilcox, L., Kaziunas, E., Matthiesen, S., & Magrabi, F. (2021). Realizing AI in healthcare: challenges appearing in the wild. In Y. Kitamura, A. Quigley, K. Isbister, & T. Igarashi (Eds.), CHI EA '21: extended abstracts of the 2021 CHI Conference on Human Factors in Computing Systems [108] Association for Computing Machinery (ACM). https://doi.org/10.1145/3411763.3441347

Osman Andersen, Tariq ; Nunes, Francisco ; Wilcox, Lauren ; Kaziunas, Elizabeth ; Matthiesen, Stina ; Magrabi, Farah. / Realizing AI in healthcare : challenges appearing in the wild. CHI EA '21: extended abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. editor / Yoshifumi Kitamura ; Aaron Quigley ; Katherine Isbister ; Takeo Igarashi. New York, NY : Association for Computing Machinery (ACM), 2021.

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title = "Realizing AI in healthcare: challenges appearing in the wild",

abstract = "The last several years have shown a strong growth of Artificial Intelligence (AI) technologies with promising results for many areas of healthcare. HCI has contributed to these discussions, mainly with studies on explainability of advanced algorithms. However, there are only few AI-systems based on machine learning algorithms that make it to the real world and everyday care. This challenging move has been named the “last mile” of AI in healthcare, emphasizing the sociotechnical uncertainties and unforeseen learnings from involving users in the design or use of AI-based systems. The aim of this workshop is to set the stage for a new wave of HCI research that accounts for and begins to develop new insights, concepts, and methods, for transitioning from development to implementation and use of AI in healthcare. Participants are invited to collaboratively define an HCI research agenda focused on healthcare AI in the wild, which will require examining end-user engagements and questioning underlying concepts of AI in healthcare.",

keywords = "artificial intelligence, human computer interaction",

author = "{Osman Andersen}, Tariq and Francisco Nunes and Lauren Wilcox and Elizabeth Kaziunas and Stina Matthiesen and Farah Magrabi",

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doi = "10.1145/3411763.3441347",

language = "English",

editor = "Yoshifumi Kitamura and Aaron Quigley and Katherine Isbister and Takeo Igarashi",

booktitle = "CHI EA '21",

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Osman Andersen, T, Nunes, F, Wilcox, L, Kaziunas, E, Matthiesen, S & Magrabi, F 2021, Realizing AI in healthcare: challenges appearing in the wild. in Y Kitamura, A Quigley, K Isbister & T Igarashi (eds), CHI EA '21: extended abstracts of the 2021 CHI Conference on Human Factors in Computing Systems., 108, Association for Computing Machinery (ACM), New York, NY, 2021 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8/05/21. https://doi.org/10.1145/3411763.3441347

Realizing AI in healthcare : challenges appearing in the wild. / Osman Andersen, Tariq; Nunes, Francisco ; Wilcox, Lauren ; Kaziunas, Elizabeth ; Matthiesen, Stina; Magrabi, Farah.

CHI EA '21: extended abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. ed. / Yoshifumi Kitamura; Aaron Quigley; Katherine Isbister; Takeo Igarashi. New York, NY : Association for Computing Machinery (ACM), 2021. 108.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Matthiesen, Stina

AU - Magrabi, Farah

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AB - The last several years have shown a strong growth of Artificial Intelligence (AI) technologies with promising results for many areas of healthcare. HCI has contributed to these discussions, mainly with studies on explainability of advanced algorithms. However, there are only few AI-systems based on machine learning algorithms that make it to the real world and everyday care. This challenging move has been named the “last mile” of AI in healthcare, emphasizing the sociotechnical uncertainties and unforeseen learnings from involving users in the design or use of AI-based systems. The aim of this workshop is to set the stage for a new wave of HCI research that accounts for and begins to develop new insights, concepts, and methods, for transitioning from development to implementation and use of AI in healthcare. Participants are invited to collaboratively define an HCI research agenda focused on healthcare AI in the wild, which will require examining end-user engagements and questioning underlying concepts of AI in healthcare.

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M3 - Conference proceeding contribution

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A2 - Isbister, Katherine

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ER -

Osman Andersen T, Nunes F, Wilcox L, Kaziunas E, Matthiesen S, Magrabi F. Realizing AI in healthcare: challenges appearing in the wild. In Kitamura Y, Quigley A, Isbister K, Igarashi T, editors, CHI EA '21: extended abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. New York, NY: Association for Computing Machinery (ACM). 2021. 108 https://doi.org/10.1145/3411763.3441347

Realizing AI in healthcare: challenges appearing in the wild

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