The Future of Work Working Group

Aleah (not her real name) is an Amazon “Warehouse Associate”, working at one of the many fulfilment centres based in the UK.1 Associates, also referred to as “Warehouse Operatives” by Amazon, are the workers who receive and stow products, and pick and pack them for customers, before they are sent to another node in Amazon’s supply chain for last-mile delivery. In the words of the company, associates are “essential”; they “literally bring customers’ orders to life, every day”.2 Working in an “on task” role (also referred to as a “direct” role), Aleah and associates like her, are subject to an algorithmically determined, pace-based target, colloquially referred to as the “rate”. Aleah doesn’t really know how the “rate” is calculated. All she knows is that she needs to hit an acceptable pace to avoid coaching and potential disciplinary action, including receiving a negative ADAPT. ADAPT stands for Associate Development and Performance Tracker. According to the limited public information available and data collected for this research, ADAPT is a software used by management to track employee performance and provide positive and negative validation across a range of dimensions including productivity, quality, safety and behaviour. — May 21, 2025

The first Fairwork AI report presents the results of a case study into Sama, a data annotation company that aims to have a positive social impact, which was conducted as part of the Global Partnership on Artificial Intelligence (GPAI) “AI for Fair Work” project. Across the world, there is increasing attention paid to the precarious situation of workers that are part of the AI supply chain. The Fairwork AI ratings presented in this report, which assess the working conditions of workers at Sama in different job roles and performing various tasks, show that fairness at work is not a given, but that by pointing to shortcomings and encouraging meaningful pro-worker change, substantial improvements can be achieved. The key improvements Sama made to the working conditions of its workers through their engagement with Fairwork are the focus of this report. Concretely, as a result of engagement with Fairwork, Sama has made some 24 significant changes in the past year to their operational model and business practices, including guaranteeing the living wage for its workers, eliminating unpaid overtime and extending employment contracts.— May 21, 2025

Launched in 2021, this project is aimed at observing AI at the workplace and analyzing its impact on workers. The project methodology involves recruiting and coaching students’ communities, who conduct interviews with workers in their geographical area. The FoW WG provides the students with a common questionnaire and pays them for the use cases collected. Since this project’s inception, three generations of students have been hired from different countries, and two reports on the impacts of AI on workers have been published. The project continued using the same questionnaire as previous years but, in 2023, saw some modifications in its methodology, by incorporating a new vision focused on gig workers (this year in Mexico). The complete report is available at the link below. It presents three studies, two conducted by the Students’ Communities in Japan and Mexico, and a third from Yann Ferguson, a FoW Expert, that has included the perspective of LaborIA, a French initiative on AI at work.— May 21, 2025

The Observation Platform of AI at the workplace project was born in 2021. To understand the motivations behind this project, we can quote the first 2 sentences of this project's report in this year 2021: “To build a better future for workers collaborating with AI, to be more inclusive on various criteria such as disability, gender, ethnicity... a mandatory initial step is observation. The aim is to capture what is happening in the real context of workplaces: observe AI at the workplace, gather as diverse as possible use cases, conduct qualitative analyses of its impact in different situations, geographies, sectors, users.” And indeed, since then, three generations of students have been hired (in Europe/Canada, Japan and Mexico) and two reports have been published on the impacts that could be observed of AI on the worker's environment.— May 21, 2025

The GPAI Future of Work group has translated the OECD AI principles into concrete workplace standards to inform the practices of employers. This process of standard development initially began with a global stakeholder consultation, which generated a first version. Now, the research team have conducted two in-depth workplace studies to connect these standards to empirical data collected on the frontlines of AI system deployment. This process has allowed for a revision of the principles, conducted in association with research partner Fairwork. The new principles have a stronger focus on pay, conditions, contracts, management and representation, because these fundamental issues were consistently highlighted by research participants. A second report containing the results of the two case studies is to follow in early 2024. — May 21, 2025

n response to the expanding landscape of digital technologies and the growing complexity of AI-based software solutions, we propose a single framework for gathering the best practices related to the development of AI-based solutions. This endeavour is driven by global digitalisation and “AI-tisation”, both horizontally (i.e., covering new industries) and vertically (i.e., infiltrating existing use cases). Let us consider a case study of an autonomous intralogistic platform1 vendor based in Poland: a manufacturer of robots that usually work in warehouses. This company stands as an illustration of the transformative power of intelligent technologies: starting as the producer of Autonomous Mobile Robots (AMR), the company has evolved into a vendor of digital AI-platform supporting the design, implementation, and management of autonomous intralogistic operations for manufacturing facilities and warehouses.— May 21, 2025

Generative AI and the Future of Work remains notably absent from the global AI governance dialogue. Given the transformative potential of this technology in the workplace, this oversight suggests a significant gap, especially considering the substantial implications this technology has for workers, economies and society at large. As interest grows in the effects of Generative AI on occupations, debates centre around roles being replaced or enhanced by technology. Yet there is an incognita, the "Big Unknown", an important number of workers whose future depends on decisions yet to be made In this brief, recent articles about the topic are surveyed with special attention to the "Big Unknown". It is not a marginal number: nearly 9% of the workforce, or 281 million workers worldwide, are in this category.— May 21, 2025

The GPAI Future of Work (FoW) Working Group’s mandate and scope are to: • Conduct critical technical analysis on how the deployment of AI can affect workers and working environments as well as how workers and employers can better design the future of work. • Address how AI can be used in the workplace to empower workers, how employers and workers can prepare for the future of work, and how job quality, inclusiveness, and health & safety can be preserved or even improved. • Include a focus on the education and training needed to prepare the future workforce. The Steering Committee encourages future projects that focus on the education and training needed to prepare people for jobs of the future, as well as on how AI can be leveraged in this education and training. — May 21, 2025

The Future of Work (FoW) Working Group (WG) started its work in 2020 with the objective to analyze how AI affects the worker, and how one can improve the AI/human cohabitation in the workplace. In 2021 the FoW WG launched two projects, (i) the AI observation Platform collecting use cases of AI at work, and (ii) AI for Fair Work, a project aiming to propose principles for a fairer AI at work. With that in mind the AI Living Lab, launched in 2022 and presented below, has found its place in the activities of the WG. The AI Living Lab would make available to a large public the use cases collected in the AI Observation Platform project. These use cases could then be confronted with the principles of the AI for Fair Work project and thus launch discussions on how to make AI fairer at work. — May 21, 2025

The Observation Platform of AI in the Workplace conducts empirical investigations on reallife use cases of Artificial Intelligence systems at work. The objective of this approach is to understand AI systems in national, cultural, sectoral, organizational, professional and individual contexts. This allows us to highlight different processes of "AI socialization", i.e. how the promises and characteristics of AI systems meet and confront systems of norms and values that will give them meaning beyond the functional objectives motivating their integration.— May 21, 2025