| Summary: | This report examines how artificial intelligence (AI) is being used in workplaces. Artificial intelligence technologies are composites of many different kinds of data and technologies and depend on how they are integrated into everyday practices—at work, with workers, in workplaces. Funding for AI ventures last year topped a record US$ 9 billion. As AI moves from the technology sector to more areas of our economy, it is time to take stock critically and comprehensively of its impact on workplaces and workers.
The aim of this report is to inform a more comprehensive dialogue around the use of AI as more workplaces roll out new kinds of AI-enabled systems by looking at the challenges of integrating new systems into existing workplaces.
We analysed themes in over 400 news, academic and industry reports from January 2019 through May 2020, focusing on how they covered AI in workplaces in a wide range of settings. We specifically sought reports on the challenges or failures in the gap between AI technologies and the environments where people use them. We find evidence of this gap, especially in how AI tools used and how people talk about what they are supposed to do.
As we discovered in our thematic gap analysis, there are broadly three major ways that AI fails workers and workplaces. 1) Integration challenges happen when settings are not yet primed for AI use, or when these technologies operate at a disjoint between workers and their employers. 2) Reliance challenges stem from over and under reliance on AI in workplace systems. 3) Transparency challenges, as we define them in this report, arise when the work required by these systems—and where that work is done—is not transparent to users.
From perfumers to oil rigs, AI is now being used outside of the large tech companies that “exist to capture and use digital data. . . That’s different than the rank and file of most enterprise companies.”1 AI requires global supply chains and a wide range of workers, many in the Global South who increasingly do routine and routinized work to ensure that AI systems function.
Overall, the stories about AI outside of the tech industry show there is much more work to be done in ensuring safe, fair and effective systems that function for workers and in workplaces.
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