Teaching Artificial Intelligence and Machine Learning to "Everyone Else"

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dc.contributor.authorLocke, James
dc.contributor.authorRainer, Kelly
dc.date.accessioned2023-12-26T18:51:15Z
dc.date.available2023-12-26T18:51:15Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.811
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other4b2fff72-b9c9-47fb-a6aa-4dc4dde30d8f
dc.identifier.urihttps://hdl.handle.net/10125/107197
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSpecial Topics in Organizational Systems and Technology
dc.subjectartificial intelligence
dc.subjectmachine learning
dc.subjectteaching
dc.titleTeaching Artificial Intelligence and Machine Learning to "Everyone Else"
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractArtificial intelligence (AI) and machine learning (ML) have become essential technologies in modern organizations, but there currently is a lack of AI/ML literacy across workforces. To help alleviate this problem, universities should offer courses providing a basic understanding of AI and ML. To date, mainly (or only) Computer Science departments offer such courses. In this paper, we discuss the importance of offering introductory courses on AI/ML to undergraduate business students. We focus on business students to keep the paper length manageable but note that the paper applies to most university majors. We first offer a rationale for these courses and follow with a brief course design for a three-course introductory sequence in AI and ML.
dcterms.extent7 pages
prism.startingpage6777

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