The McDonaldization of Occupational Safety and Health (OSH) is a sociological concept describing how education, training, auditing, and certification in OSH have come to mirror the principles of McDonaldization: efficiency, calculability, predictability, and control. It explores how these industrial-era values, first outlined by sociologist George Ritzer in his 1993 book The McDonaldization of Society[1] have influenced modern OSH systems through digitalization, commercialization, and algorithmic management.
Since the late 20th century, OSH education and training have expanded rapidly in response to globalization, digitalization, and the growth of private training markets. This expansion coincided with a broader neoliberal shift in public policy, where governments reduced direct involvement in adult education and professional development. Commercial providers subsequently emerged offering low-cost, fast-track, and entirely online safety certifications.[2]
These developments reflect the wider Commodification of Education, where learning is treated as a market commodity rather than a public good. According to Karpov (2013), commodification reduces learners to consumers and knowledge to a transaction, resulting in a loss of intrinsic educational value.[3] Miller 2010 and Lawrence & Sharma 2002 argue that this shift prioritizes credentials over competence, reshaping both pedagogy and professional ethics.[4][5]
Parallel trends have emerged in the OSH sector, where mass-produced, self-accredited certification schemes emphasize growth and profitability over learning depth. Freeman (2020)[2] and Postdigital Science and Education (2022)[6] observe that digital transformation often conceals commercialization under the rhetoric of innovation, as institutions adopt corporate methods of marketing, scalability, and data monetization.
Complementing this, Treiber links McDonaldization to alienating work and the rise of the “McJob”— employment characterized by deskilling, scripted interactions, and tight managerial control. These forms of rationalized labour parallel modern OSH concerns about psychosocial risks, stress, and mental health at work.[7]
The term McDonaldization of OSH was first used by educator and OSH researcher Dave Magee in a 2025 article on LinkedIn,[8] where he applied Ritzer’s framework to the global commercialization of safety training. The concept has since been discussed in additional practitioner commentary, including a popular post by Clayton Kruger discussing 'The McDonaldisation of OSH'.[9] The term has also been increasingly used in the OSH-ai discourse events and conferences.
Core characteristics
Ritzer’s four dimensions of McDonaldization—efficiency, calculability, predictability, and control—are observable across modern OSH systems.
Efficiency: OSH courses are often designed for quick completion through automated online modules. Many commercial providers guarantee a 100 percent pass rate, reducing the need for deep comprehension or reflective learning.[10]
Calculability: Quantitative metrics such as completion time, number of certificates issued, or test scores are prioritized over qualitative outcomes like critical thinking or improved workplace safety. This reflects the 'audit culture' described in The Commodification of Education: An Academic Dilemma (2024).[11]
Predictability: Many training programs use standardized templates and repetitive content. While this creates consistency, it discourages contextual adaptation to local hazards or regulations.[12]
Control: Automated testing and learning management systems reduce human involvement in instruction and evaluation. This creates a uniform, software-driven experience that prioritizes compliance over critical engagement. The resulting loss of autonomy and deskilling has been linked to alienation in the workplace,[7] a psychosocial risk recognized in contemporary OSH discourse.
Ritzer called this process the 'irrationality of rationality': systems optimized for control and efficiency can produce irrational outcomes. In OSH, overly simplified training can create overconfident workers who misunderstand risks, ultimately increasing rather than reducing accidents.[1]
AI, algorithmic management, and McDonaldization in OSH
Algorithmic management uses AI-based tools to assign tasks, monitor performance, schedule shifts, and assess workers. The EU-OSHA describes it as a “double-edged sword” that can improve efficiency but also heighten 'psychosocial risks' when misused.[13]
A multiple-case study in Swedish logistics found that under algorithmic management, workers faced reduced autonomy, increased workload, and higher psychological strain.[14] The OECD’s Algorithmic Management in the Workplace (2025) similarly warned that these systems expand rapidly but raise concerns about accountability, transparency, and worker well-being.[15]
The Partnership for European Research in Occupational Safety and Health (PEROSH) project ALMA-AI examined how algorithmic systems affect worker health and psychosocial conditions across Europe.[16] Other studies highlight how constant monitoring and automated feedback loops intensify workloads and stress.[17]
Because algorithmic systems reinforce predictability and control, they deepen McDonaldization: workers are evaluated by algorithms, their actions optimized by software, and human discretion is minimized. To prevent these risks, researchers advocate a "human in command" model, where AI assists rather than replaces human oversight.[citation needed]
Benefits and opportunities
Despite criticism, researchers acknowledge that AI and digital tools can improve occupational safety when ethically deployed. EU-OSHA and the ILO note that AI-driven analytics can enhance ergonomic design, hazard detection, and the prevention of repetitive strain injuries.[18] Balanced implementation that combines technology with human judgment is seen as key to achieving "safe digital transformation."
Criticism and implications
Critics view McDonaldization in OSH as part of the broader commodification of education and work. Karpov (2013)[3] warned that focusing on quantity over quality reduces intellectual autonomy. In OSH, this manifests as certification-focused training pipelines and consultancy-linked audits. Studies on digital education show that reform rhetoric often conceals commercialization pressures.[6]
The growth of self-accredited certification bodies and proprietary audit systems raises potential conflicts of interest, particularly where training, auditing, and software sales are vertically integrated. Data monetization and surveillance risks further complicate this relationship.
Algorithmic systems can exacerbate psychosocial risks: stress, burnout, and anxiety, particularly when workers lack control or recourse. Life Against Algorithmic Management (2025) documents these pressures in gig work sectors.[19] Research on warehouse workers shows how metrics-based regimes lead to depersonalization and reduced autonomy.[20]
Regulatory challenges persist as labour law and data protection frameworks struggle to address algorithmic oversight.[21] Overall, McDonaldization in OSH risks turning safety into a mechanized, metric-driven process that may undermine human-centered values.
Potential remedies and alternatives
Scholars and regulators suggest several strategies to reduce McDonaldization in OSH:
Embed worker participation in system design and oversight.
Maintain human veto power over automated decisions.
Regulate AI systems through labour, safety, and data protection law.
Shift evaluation toward qualitative outcomes such as improved safety culture and reduced incidents.
Reintegrate professional judgment and local adaptability into safety practice.
These approaches aim to rehumanize OSH management while maintaining the benefits of efficiency, avoiding what Ritzer termed the "irrationality of rationality."
12Ritzer, George (1993). The McDonaldization of Society: An Investigation Into the Changing Character of Contemporary Social Life. Pine Forge Press. ISBN978-0-8039-9000-5.[pageneeded]
12Freeman, R (2020). "The Marketization of Professional Training: A Risk Perspective". Policy Futures in Education. 18 (7): 823–837.
12Karpov, A. O. (2013). "The Commodification of Education". Russian Education & Society. 55 (5): 75–90. doi:10.2753/RES1060-9393550506.
↑Miller, Brian (May 2010). "Skills for sale: what is being commodified in higher education?". Journal of Further and Higher Education. 34 (2): 199–206. doi:10.1080/03098771003695460.
↑Lawrence, Stewart; Sharma, Umesh (October 2002). "Commodification of Education and Academic LABOUR—Using the Balanced Scorecard in a University Setting". Critical Perspectives on Accounting. 13 (5–6): 661–677. doi:10.1006/cpac.2002.0562.
12Armila, Päivi; Sivenius, Ari; Stanković, Biljana; Juutilainen, Lauri (June 2024). "Digitalization of Education: Commodification Hidden in Terms of Empowerment?". Postdigital Science and Education. 6 (2): 556–571. doi:10.1007/s42438-022-00347-8.
↑Plante, Jarrad (2016). "The Conflict of Commodification of Traditional Higher Education Institutions". Academic Leadership Journal in Student Research. 4. doi:10.58809/OXMZ7657. ERICEJ1101248.
↑Rana, Tarek (4 January 2024). "The commodification of education: an academic dilemma". Accounting, Auditing & Accountability Journal. 37 (1): 428–429. doi:10.1108/AAAJ-01-2024-215.
↑Baker, Elisabeth (2002). "The Commodification of Higher Education: Tools of Management". The Vermont Connection. 23. hdl:20.500.14849/9370.
↑Nilsson, Karin Hennum; Matilla-Santander, Nuria; Lee, Min Kyung; Brulin, Emma; Bodin, Theo; Håkansta, Carin (July 2025). "Algorithmic management and occupational health: A comparative case study of organizational practices in logistics". Safety Science. 187 106863. doi:10.1016/j.ssci.2025.106863.
↑Cheon, Eunjeong; Erickson, Ingrid (2025). "Fulfillment of the Work Games: Warehouse Workers' Experiences with Algorithmic Management". Proceedings of the ACM on Human-Computer Interaction. 9 (7): 1–30. arXiv:2508.09438. doi:10.1145/3757409.
↑Lynn, Jonathan; Kim, Rachel Y.; Gao, Sicun; Schneider, Daniel; Pandya, Sachin S.; Lee, Min Kyung (2025). "Regulating Algorithmic Management: A Multi-Stakeholder Study of Challenges in Aligning Software and the Law for Workplace Scheduling". Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency. pp.547–572. arXiv:2505.02329. doi:10.1145/3715275.3732037. ISBN979-8-4007-1482-5.
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