Martin Gonzalez-Cabello , Auyon Siddiq , Charles J. Corbett , Catherine Hu
{"title":"众包中的公平:让人类人工智能供应链更人性化","authors":"Martin Gonzalez-Cabello , Auyon Siddiq , Charles J. Corbett , Catherine Hu","doi":"10.1016/j.bushor.2024.09.003","DOIUrl":null,"url":null,"abstract":"<div><div>The vast quantities of data required to build artificial intelligence (AI) technologies are often annotated and processed manually, making human labor a critical component of the AI supply chain. The workers who input this data are sourced through digital labor (“crowdwork”) platforms that often are unregulated and offer low wages, raising concerns about labor standards in AI development. Using the results of a survey, this article aims to shed light on the experiences and perceptions of fair treatment among workers in the AI supply chain. The study reveals significant variability in workers’ experiences, identifies potential drivers of fairness, and highlights how design choices by labor platforms can significantly affect worker welfare. Drawing on lessons from physical supply chains, this article offers practical guidance to managers on how to enhance worker welfare within the AI supply chain and how to ensure that AI technologies are responsibly sourced.</div></div>","PeriodicalId":48347,"journal":{"name":"Business Horizons","volume":"68 5","pages":"Pages 645-657"},"PeriodicalIF":7.0000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fairness in crowdwork: Making the human AI supply chain more humane\",\"authors\":\"Martin Gonzalez-Cabello , Auyon Siddiq , Charles J. Corbett , Catherine Hu\",\"doi\":\"10.1016/j.bushor.2024.09.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The vast quantities of data required to build artificial intelligence (AI) technologies are often annotated and processed manually, making human labor a critical component of the AI supply chain. The workers who input this data are sourced through digital labor (“crowdwork”) platforms that often are unregulated and offer low wages, raising concerns about labor standards in AI development. Using the results of a survey, this article aims to shed light on the experiences and perceptions of fair treatment among workers in the AI supply chain. The study reveals significant variability in workers’ experiences, identifies potential drivers of fairness, and highlights how design choices by labor platforms can significantly affect worker welfare. Drawing on lessons from physical supply chains, this article offers practical guidance to managers on how to enhance worker welfare within the AI supply chain and how to ensure that AI technologies are responsibly sourced.</div></div>\",\"PeriodicalId\":48347,\"journal\":{\"name\":\"Business Horizons\",\"volume\":\"68 5\",\"pages\":\"Pages 645-657\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2024-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Business Horizons\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0007681324001265\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business Horizons","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0007681324001265","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Fairness in crowdwork: Making the human AI supply chain more humane
The vast quantities of data required to build artificial intelligence (AI) technologies are often annotated and processed manually, making human labor a critical component of the AI supply chain. The workers who input this data are sourced through digital labor (“crowdwork”) platforms that often are unregulated and offer low wages, raising concerns about labor standards in AI development. Using the results of a survey, this article aims to shed light on the experiences and perceptions of fair treatment among workers in the AI supply chain. The study reveals significant variability in workers’ experiences, identifies potential drivers of fairness, and highlights how design choices by labor platforms can significantly affect worker welfare. Drawing on lessons from physical supply chains, this article offers practical guidance to managers on how to enhance worker welfare within the AI supply chain and how to ensure that AI technologies are responsibly sourced.
期刊介绍:
Business Horizons, the bimonthly journal of the Kelley School of Business at Indiana University, is dedicated to publishing original articles that appeal to both business academics and practitioners. Our editorial focus is on covering a diverse array of topics within the broader field of business, with a particular emphasis on identifying critical business issues and proposing practical solutions. Our goal is to inspire readers to approach business practices from new and innovative perspectives. Business Horizons occupies a distinctive position among business publications by offering articles that strike a balance between academic rigor and practical relevance. As such, our articles are grounded in scholarly research yet presented in a clear and accessible format, making them relevant to a broad audience within the business community.