{"title":"算法偏见:通过三维可靠人工智能框架整合社会科学研究","authors":"Kalinda Ukanwa","doi":"10.1016/j.copsyc.2024.101836","DOIUrl":null,"url":null,"abstract":"<div><p>Algorithmic bias has emerged as a critical challenge in the age of responsible production of artificial intelligence (AI). This paper reviews recent research on algorithmic bias and proposes increased engagement of psychological and social science research to understand antecedents and consequences of algorithmic bias. Through the lens of the 3-D Dependable AI Framework, this article explores how social science disciplines, such as psychology, can contribute to identifying and mitigating bias at the Design, Develop, and Deploy stages of the AI life cycle. Finally, we propose future research directions to further address the complexities of algorithmic bias and its societal implications.</p></div>","PeriodicalId":48279,"journal":{"name":"Current Opinion in Psychology","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352250X24000496/pdfft?md5=db9280dadbd4af45a3b4670a405a5422&pid=1-s2.0-S2352250X24000496-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Algorithmic bias: Social science research integration through the 3-D Dependable AI Framework\",\"authors\":\"Kalinda Ukanwa\",\"doi\":\"10.1016/j.copsyc.2024.101836\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Algorithmic bias has emerged as a critical challenge in the age of responsible production of artificial intelligence (AI). This paper reviews recent research on algorithmic bias and proposes increased engagement of psychological and social science research to understand antecedents and consequences of algorithmic bias. Through the lens of the 3-D Dependable AI Framework, this article explores how social science disciplines, such as psychology, can contribute to identifying and mitigating bias at the Design, Develop, and Deploy stages of the AI life cycle. Finally, we propose future research directions to further address the complexities of algorithmic bias and its societal implications.</p></div>\",\"PeriodicalId\":48279,\"journal\":{\"name\":\"Current Opinion in Psychology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352250X24000496/pdfft?md5=db9280dadbd4af45a3b4670a405a5422&pid=1-s2.0-S2352250X24000496-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352250X24000496\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Psychology","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352250X24000496","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
Algorithmic bias: Social science research integration through the 3-D Dependable AI Framework
Algorithmic bias has emerged as a critical challenge in the age of responsible production of artificial intelligence (AI). This paper reviews recent research on algorithmic bias and proposes increased engagement of psychological and social science research to understand antecedents and consequences of algorithmic bias. Through the lens of the 3-D Dependable AI Framework, this article explores how social science disciplines, such as psychology, can contribute to identifying and mitigating bias at the Design, Develop, and Deploy stages of the AI life cycle. Finally, we propose future research directions to further address the complexities of algorithmic bias and its societal implications.
期刊介绍:
Current Opinion in Psychology is part of the Current Opinion and Research (CO+RE) suite of journals and is a companion to the primary research, open access journal, Current Research in Ecological and Social Psychology. CO+RE journals leverage the Current Opinion legacy of editorial excellence, high-impact, and global reach to ensure they are a widely-read resource that is integral to scientists' workflows.
Current Opinion in Psychology is divided into themed sections, some of which may be reviewed on an annual basis if appropriate. The amount of space devoted to each section is related to its importance. The topics covered will include:
* Biological psychology
* Clinical psychology
* Cognitive psychology
* Community psychology
* Comparative psychology
* Developmental psychology
* Educational psychology
* Environmental psychology
* Evolutionary psychology
* Health psychology
* Neuropsychology
* Personality psychology
* Social psychology