{"title":"Using AI Tools to Develop Training Materials for Aviation: Ethical, Technical, and Practical Concerns","authors":"Blake Nguyen, Nathan Sonnenfeld, Lindsay Finkelstein, Alex Alonso, Caroline Gomez, Fiona Duruaku, Florian Jentsch","doi":"10.1177/21695067231192904","DOIUrl":null,"url":null,"abstract":"A key potential advantage of modern training technologies relates to the ability to use them to automate aspects of training. Although in the early stages of adoption within the aviation industry, artificial intelligence (AI) tools and methods have many promises for training design, development, delivery, and assessment. We applied the use-case technology-mapping framework (UCTM) to identify and analyze how automation and AI technologies may be used within the flightcrew training design pipeline, integrating perspectives from relevant literature, informal discussions with stakeholders, and workshops with domain experts. Our preliminary findings highlight current/near-future applications of AI methods and tools in the training design pipeline. Here, we discuss ethical/legal, technical, and practical considerations for flightcrew training. We urge practitioners and researchers in the aviation human factors community to engage in this discussion and to conduct empirical research that will allow for a positive use of the technology across applications, including in aviation training. Practical Takeaways/Applications. • We present a wide range of potential use cases of AI in flightcrew training. • We discuss the ethical/legal, technical, and practical implications of automation and AI. • This information may inform future training processes and practices in the aviation domain.","PeriodicalId":74544,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","volume":"13 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Human Factors and Ergonomics Society. Annual meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/21695067231192904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A key potential advantage of modern training technologies relates to the ability to use them to automate aspects of training. Although in the early stages of adoption within the aviation industry, artificial intelligence (AI) tools and methods have many promises for training design, development, delivery, and assessment. We applied the use-case technology-mapping framework (UCTM) to identify and analyze how automation and AI technologies may be used within the flightcrew training design pipeline, integrating perspectives from relevant literature, informal discussions with stakeholders, and workshops with domain experts. Our preliminary findings highlight current/near-future applications of AI methods and tools in the training design pipeline. Here, we discuss ethical/legal, technical, and practical considerations for flightcrew training. We urge practitioners and researchers in the aviation human factors community to engage in this discussion and to conduct empirical research that will allow for a positive use of the technology across applications, including in aviation training. Practical Takeaways/Applications. • We present a wide range of potential use cases of AI in flightcrew training. • We discuss the ethical/legal, technical, and practical implications of automation and AI. • This information may inform future training processes and practices in the aviation domain.