Artificial intelligence and skills in the workplace: An integrative research agenda

IF 6.5 1区社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY

Big Data & Society Pub Date : 2023-07-01 DOI:10.1177/20539517231206804

Anoush Margaryan

引用次数: 0

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.

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工作场所的人工智能和技能:一个综合研究议程

人工智能(AI)技术在工作场所的发展和传播正在改变工作实践的性质及其构成技能要求。这种双重转变对工人、组织和社会来说是一项挑战，他们需要发展和加强现有技能和新技能，以便在日益以人工智能为媒介的工作环境中取得成功。尽管文献已经认识到技能是开发和采用人工智能技术的关键因素，但对于人工智能介导的工作场所中技能要求的确切性质，缺乏实证研究。这篇评论认为，为了提高我们对人工智能介导的工作场所技能要求的理解，需要一种综合的、多学科的、多方法的和多利益相关者的方法。评论提出了一个议程，未来的研究在这个重要的社会，但知之甚少的领域。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-

CiteScore

10.90

自引率

10.60%

发文量

审稿时长

11 weeks

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.