T. Andersen, Francisco Nunes, Lauren Wilcox, Elizabeth Kaziunas, Stina Matthiesen, F. Magrabi
{"title":"在医疗保健领域实现人工智能:野外出现的挑战","authors":"T. Andersen, Francisco Nunes, Lauren Wilcox, Elizabeth Kaziunas, Stina Matthiesen, F. Magrabi","doi":"10.1145/3411763.3441347","DOIUrl":null,"url":null,"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.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Realizing AI in Healthcare: Challenges Appearing in the Wild\",\"authors\":\"T. Andersen, Francisco Nunes, Lauren Wilcox, Elizabeth Kaziunas, Stina Matthiesen, F. Magrabi\",\"doi\":\"10.1145/3411763.3441347\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":265192,\"journal\":{\"name\":\"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3411763.3441347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3411763.3441347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Realizing AI in Healthcare: Challenges Appearing in the Wild
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.