Background:
The rise of Artificial Intelligence (AI) sparks concerns across various societal domains, particularly in the realm of employment. While fears of widespread job loss persist, proponents argue that AI will only replace specific tasks rather than entire occupations. Moreover, AI holds the potential to enhance workplace safety through smart digital systems. However, the advent of Algorithmic Management, utilizing AI for work coordination, introduces new challenges such as reduced worker autonomy and heightened work intensity.
Objectives:
The ALMA-AI project seeks to understand Algorithmic Management’s essence and its implications, both in terms of occupational health and safety (OSH) risks and opportunities. Additionally, it aims to contribute to the ethical development of AI and other advanced organizational systems for workers.
Target Groups:
This project targets policymakers, enterprises, workers, and OSH professionals who may require support in navigating this evolving landscape.
Deliverables:
The primary deliverable will be a comprehensive scientific report, including literature reviews and statistical analyses. Depending on the research findings, supplementary deliverables may include scientific papers, checklists, infographics, factsheets, or guidelines tailored to specific stakeholders’ needs.
Research Methods:
The project will employ two main research methods:
- Literature Review: A thorough examination of scientific literature and reports concerning the OSH implications of AI-based systems and Algorithmic Management.
- Data Analysis: Utilizing existing surveys or generating new data, statistical analysis will provide quantitative evidence of OSH risks associated with Algorithmic Management and AI.
Scientific Relevance:
AI and Algorithmic Management have gained significant attention in recent years. While numerous publications focus on these topics individually, there is a dearth of literature analyzing their combined effects, especially concerning OSH. The ALMA-AI project aims to address this gap in knowledge.
Practical and Societal Relevance:
In addition to its scientific importance, the project holds practical significance, particularly considering impending EU regulations. Legislative initiatives such as the EU AI Act and directives on working conditions in platform work underscore the need for guidelines to assess risks and implement OSH measures in Algorithmic Management and AI utilization.
Project Leader:
Jorge Martín González (INSST, Spain)
Project Participants:
The project includes participants from various PEROSH partner institutions:
- Marie Jelenko & Thomas Strobach (AUVA, Austria)
- Joanna Kamińska & Karolina Pawłowska-Cyprysiak (CIOP-PIB, Poland)
- Teppo Valtonen (FIOH, Finland)
- Giuliana Buresti & Fabio Boccuni (INAIL, Italy)
- Benjamin Paty & Virginie Govaere (INRS, France)
- Jon Zubizarreta (INSST, Spain)
- Elsbeth de Korte & Hardy van den Ven (TNO, The Netherlands)
Observer Partners:
Representatives from relevant institutions including EU-OSHA and the EU Commission’s Joint Research Center are also involved in the project.
- Maurizio Curtarelli & Emmanuelle Brun (EU Agency for Safety and Health at Work, EU-OSHA)
- Enrique Fernández-Macías & Ignacio González-Vázquez (EU Commission´s Joint Research Center, JRC)
More information:
For additional information, view our project video or contact the project coordinator Jorge Martin González, jorge.martin@insst.mites.gob.es
