An Implementable Guideline for Developing Ethical AI Systems: The Evaluation of Child Abuse and Neglect Prediction

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dc.contributor.authorHan, Yuzhang
dc.contributor.authorLandau, Aviv
dc.contributor.authorKulkarni, Paritosh
dc.contributor.authorModaresnezhad, Minoo
dc.contributor.authorNemati, Hamid
dc.date.accessioned2023-12-26T18:51:29Z
dc.date.available2023-12-26T18:51:29Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2023.819
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.othere33147a7-22e4-431e-87b0-d283d9bc2f43
dc.identifier.urihttps://hdl.handle.net/10125/107205
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.subjectArtificial Intelligence and Digital Discrimination
dc.subjectartificial intelligence
dc.subjectmachine learning
dc.subjectethical guideline
dc.subjectimplementation
dc.subjectevaluation
dc.subjectai quality metrics
dc.subjectchild abuse and neglect
dc.titleAn Implementable Guideline for Developing Ethical AI Systems: The Evaluation of Child Abuse and Neglect Prediction
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractArtificial Intelligence (AI) is becoming a crucial part of our lives. Although AI applications, such as facial recognition, autonomous driving and ChatGPT, can benefit different industries, users are more and more concerned about the ethical issues associated with AI systems. As a result, various ethics frameworks and standards have been proposed for regulating AI systems. Nevertheless, existing ethics frameworks and standards are hardly actionable or implementable for AI developers. To fill this gap, the current study proposes an actionable ethics-aware guideline for AI developers, as well as a set of quality metrics for ethical AI systems. Further, we implement the guideline using numerous AI predictive models constructed on a national big data set that estimates children’s risk of experiencing abuse and neglect in the United States. Evaluation results indicate that the proposed guideline can effectively enhance the quality of predictive models in utility, ethicality and cost dimensions.
dcterms.extent10 pages
prism.startingpage6828

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