Auste Simkute, Aditi Surana, E. Luger, Michael Evans, Rhianne Jones
{"title":"XAI for learning: Narrowing down the digital divide between “new” and “old” experts","authors":"Auste Simkute, Aditi Surana, E. Luger, Michael Evans, Rhianne Jones","doi":"10.1145/3547522.3547678","DOIUrl":null,"url":null,"abstract":"Regular eXplainable AI (XAI) approaches are often ineffective in supporting decision-makers across domains. In some instances, it can even lead to automation bias or algorithmic aversion or would simply be ignored as a redundant feature. Based on cognitive psychology literature we outline a strategy for how XAI interface design could be tailored to have a long-lasting educational value. We suggest the features that could support domain-related and technical skills development this way narrowing the digital divide between “new” and “old” experts. Lastly, we suggest an intermitted explainability approach that could help to find a balance between seamless and cognitively engaging explanations.","PeriodicalId":265029,"journal":{"name":"Adjunct Proceedings of the 2022 Nordic Human-Computer Interaction Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 2022 Nordic Human-Computer Interaction Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3547522.3547678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Regular eXplainable AI (XAI) approaches are often ineffective in supporting decision-makers across domains. In some instances, it can even lead to automation bias or algorithmic aversion or would simply be ignored as a redundant feature. Based on cognitive psychology literature we outline a strategy for how XAI interface design could be tailored to have a long-lasting educational value. We suggest the features that could support domain-related and technical skills development this way narrowing the digital divide between “new” and “old” experts. Lastly, we suggest an intermitted explainability approach that could help to find a balance between seamless and cognitively engaging explanations.