{"title":"工作场所的人工智能和技能:一个综合研究议程","authors":"Anoush Margaryan","doi":"10.1177/20539517231206804","DOIUrl":null,"url":null,"abstract":"The development and diffusion of artificial intelligence (AI) technologies in workplaces are transforming the nature of work practices and their constituent skill requirements. This dual transformation is challenging for workers, organisations and societies, who are faced with the need to develop and enhance extant and new skills required to succeed in increasingly AI-mediated work settings. Although literature has recognised skills as a key factor in the development and uptake of AI technologies, there has been paucity of empirical research on the precise nature of skill requirements in AI-mediated workplaces. This commentary argues that to advance our understanding of skill requirements in AI-mediated workplaces, an integrative, multidisciplinary, multimethod and multistakeholder approach is required. The commentary proposes an agenda for future research in this societally important but poorly understood area.","PeriodicalId":47834,"journal":{"name":"Big Data & Society","volume":"3 1","pages":"0"},"PeriodicalIF":6.5000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence and skills in the workplace: An integrative research agenda\",\"authors\":\"Anoush Margaryan\",\"doi\":\"10.1177/20539517231206804\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development and diffusion of artificial intelligence (AI) technologies in workplaces are transforming the nature of work practices and their constituent skill requirements. This dual transformation is challenging for workers, organisations and societies, who are faced with the need to develop and enhance extant and new skills required to succeed in increasingly AI-mediated work settings. Although literature has recognised skills as a key factor in the development and uptake of AI technologies, there has been paucity of empirical research on the precise nature of skill requirements in AI-mediated workplaces. This commentary argues that to advance our understanding of skill requirements in AI-mediated workplaces, an integrative, multidisciplinary, multimethod and multistakeholder approach is required. The commentary proposes an agenda for future research in this societally important but poorly understood area.\",\"PeriodicalId\":47834,\"journal\":{\"name\":\"Big Data & Society\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":6.5000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Big Data & Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/20539517231206804\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data & Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/20539517231206804","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Artificial intelligence and skills in the workplace: An integrative research agenda
The development and diffusion of artificial intelligence (AI) technologies in workplaces are transforming the nature of work practices and their constituent skill requirements. This dual transformation is challenging for workers, organisations and societies, who are faced with the need to develop and enhance extant and new skills required to succeed in increasingly AI-mediated work settings. Although literature has recognised skills as a key factor in the development and uptake of AI technologies, there has been paucity of empirical research on the precise nature of skill requirements in AI-mediated workplaces. This commentary argues that to advance our understanding of skill requirements in AI-mediated workplaces, an integrative, multidisciplinary, multimethod and multistakeholder approach is required. The commentary proposes an agenda for future research in this societally important but poorly understood area.
期刊介绍:
Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government.
BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices.
BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.