Carin Håkansta

This project investigates the role of Artificial Intelligence in future-proofing long-term care (LTC). The sector faces multiple challenges: an ageing population, limited productivity gains in a labour-intensive sector, labour shortages, and the crisis of traditional modes of care provision amid rising female employment rates. This project explores AI’s potential to help the sector respond to long-standing and growing workforce challenges, improve its value proposition and care quality. We will inform industry standards, care models, and share best practices to inform viable and high-quality care solutions.The project focus is on algorithmic management (AM) as an element of AI and its effects on job & care quality. AM may alter the dynamics of the manager-worker-care recipient. However, existing literature rarely engages systematically with the job quality-AM/AI nexus. By offering a research study that compares five countries’ (Austria, Belgium, Sweden, Spain and the UK) this project will systematically investigate efforts to address issues affecting the sustainability of LTC. A key research focus is to explore the challenges and potential of AM/AI to (i) address recruitment & retention challenges through enhancing working conditions and (ii) improve care quality with potentially better outcomes for workers, care recipients and their families, using company case studies in three subsectors within LTC. Special attention will be paid to certain dimensions of job quality relevant to AM/AI: intrinsic elements (OH&S, work intensification, surveillance, consultative rights, and voice) and extrinsic elements (wages, working hours, benefits, employment conditions, skills).Empirically, the project will strengthen the LTC and job quality literature by exploring the less researched role of how public and private care providers across LTC regimes have embraced AM/AI. It will advance the understanding of the effects of deploying AM/AI at workplace level to shed light on the dynamics between AM and job quality within LTC. Theoretically, it will extend the job quality and LTC literature by refining and reframing present job indicators in the context of AM/AI with the aim to develop viable solutions to address labour shortage challenges. On the societal level the project contribute to national & EU policy agendas on the digital transformation of care work.

Algorithmic management (AM) is the application of digital technology to automate management decisions in the organization of work. AM is common among platform workers, for example food delivery men and taxi drivers, and research shows that this affects the design of the work as well as the work environment and health of employees. The phenomenon is becoming increasingly common in industries outside of platform work, which has contributed to a discussion about how it should be regulated and handled. The applicant is the PI of two projects on this theme: one from Forte (ALGOSH six-year program 2023-2029) and an AFA grant (AMOSH three-year project, ending in 2024). The purpose of this application is to present the research of the applicant through talks, seminars and workshops in various places in Australia, and to inform herself about Australian research and policy developments. The aim is to achieve: 1. Knowledge exchange between Swedish and Australian researchers on how AM in non-platform work affects occupational safety and health (OSH), health and labor market relations in different sectors

2. Research collaboration regarding AM and OSH in the mining industry (possibly also with Luleå University of Technology)

3. Joint publication(s) based on research data from ALGOSH, AMOSH and a similar data from projects led by Penny Williams at Queensland University of Technology

4. Discuss the possibility of replicating a national survey planned in Sweden within ALGOSH in Australia. The requested funding is intended to finance travel to and within Australia as well as accommodation costs for 6 weeks in the spring of 2025.

Algorithms are changing the World of Work: from the tasks that consitute work to how it is organised and governed. Lack of data and knowledge about the impacts of algorithmic management (AM) on work and workers pose a societal challenge today. This deficit is particularly pronounced outside of platform work - in economic sectors where the use of AM is growing, such as logistics, including transport, storage and delivery services and the retail and hospitality industry. In both platform and non-platform work there is a lack of research about the effects of AM on the work environment and workers’ health and well-being. Therefore, the overall aim of this multi-disciplinary research program is to improve data and knowledge about algorithmic management in non-platform sectors and its effects on health, safety, and well-being, as well as develop risk-reducing tools and strategies by:Facilitating the development of a standard for measurement of algorithmic management at work and related risks for health, safety and well-being.Increasing knowledge about the effects of algorithmic management on workers’ health, safety, and well-being.Investigating the balance of interests related to the control of algorithms in different legal contexts regarding occupational health and safety (OSH).The proposed program will contribute with enhanced data and knowledge about challenges and opportunities of AM to safety, health and well-being as well as evidence-based tools and strategies to be used by stakeholders in discussions and action related to AM. The program applies multiple methods including quantitative, qualitative, literature reviews and participatory research.The program will be performed by an international and multidisciplinary team of researchers, involving experts in human-computer-interaction, cognitive ergonomics, labour economics, political science, occupational epidemiology, comparative labour law, industrial relations, work organization and psychology.