{"title":"Mind the gender gap: Inequalities in the emergent professions of artificial intelligence (AI) and data science","authors":"Erin Young, J. Wajcman, Laila Sprejer","doi":"10.1111/ntwe.12278","DOIUrl":null,"url":null,"abstract":"The emergence of new prestigious professions in data science and artificial intelligence (AI) provide a rare opportunity to explore the gendered dynamics of technical careers as they are being formed. In this paper, we contribute to the literature on gender inequality in digital work by curating and analysing a unique cross‐country data set. We use innovative data science methodology to investigate the nature of work and skills in these under‐researched fields. Our research finds persistent disparities in jobs, qualifications, seniority, industry, attrition and even self‐confidence in these fields. We identify structural inequality in data and AI, with career trajectories of professionals differentiated by gender, reflecting the broader history of computing. Our work is original in illuminating gendering processes within elite high‐tech jobs as they are being configured. Paying attention to these nascent fields is crucial if we are to ensure that women take their rightful place at forefront of technological innovation.","PeriodicalId":51550,"journal":{"name":"New Technology Work and Employment","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2023-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Technology Work and Employment","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1111/ntwe.12278","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ERGONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The emergence of new prestigious professions in data science and artificial intelligence (AI) provide a rare opportunity to explore the gendered dynamics of technical careers as they are being formed. In this paper, we contribute to the literature on gender inequality in digital work by curating and analysing a unique cross‐country data set. We use innovative data science methodology to investigate the nature of work and skills in these under‐researched fields. Our research finds persistent disparities in jobs, qualifications, seniority, industry, attrition and even self‐confidence in these fields. We identify structural inequality in data and AI, with career trajectories of professionals differentiated by gender, reflecting the broader history of computing. Our work is original in illuminating gendering processes within elite high‐tech jobs as they are being configured. Paying attention to these nascent fields is crucial if we are to ensure that women take their rightful place at forefront of technological innovation.
期刊介绍:
New Technology, Work and Employment presents analysis of the changing contours of technological and organisational systems and processes in order to encourage an enhanced and critical understanding of the dimensions of technological change in the workplace and in employment more generally. The journal is eclectic and invites contributions from across the social sciences, with the primary focus on critical and non-managerial approaches to the subject. It has the aim of publishing papers from perspectives concerned with the changing nature of new technology and workplace and employment relations. The objective of the journal is to promote deeper understanding through conceptual debate firmly rooted in analysis of current practices and sociotechnical change.