Algorithmic management

About this course

Algorithmic management refers to the use of digital systems in work planning, task allocation, and monitoring of work processes. It has predominantly been discussed as a source of concern, particularly in relation to surveillance, work intensification, transparency, and reduced worker autonomy.

This course takes a more balanced and exploratory perspective by examining how digital and algorithmic systems may be designed and implemented to also improve the working environment.

Through empirical examples and critical discussions, participants will explore both risks and potentials of algorithmic management. The course focuses on the conditions under which digital management systems can support better work organisation, health, and safety, rather than undermine them.

Main topics

• Core concepts and forms of algorithmic management
• How algorithmic and digital systems make decisions
• Surveillance, control, work intensification, transparency, and autonomy
• Physical and psychosocial working-environment impacts
• Empirical cases of algorithmic management
• Design, participation, and organisational conditions for creating a sustainable and healthy working environment through algorithmic systems
• Ethical considerations with algorithmic management, digital systems, and AI

Course objectives

The overall objective is to provide participants with an understanding of how algorithmic management and related digital systems shape work organisation, and how they may be designed, implemented, and governed to support healthier and safer working conditions. The course takes a balanced perspective on both the challenges and the occupational health and safety potential of algorithmic management.

This will be explored through a range of themes, where participants discuss:

• Core concepts of algorithmic management, including how digital and algorithmic systems support decisions, allocate tasks, and organise work
• Potential risks related to surveillance, control, work intensification, transparency, autonomy, fairness, and ethics
• How algorithmic management may affect physical, psychosocial, and cognitive working conditions
• Empirical examples of both positive and negative consequences of algorithmic management
• How algorithmic management can be used as a tool to support better work organisation and improved working conditions
• Design, implementation, and governance approaches that support healthier, safer, and more sustainable work practices
• Ethical considerations across the design, implementation, and use of algorithmic management systems

Target group

The course is intended for researchers, PhD students, specialists, practitioners, policymakers, and system developers working with or interested in algorithmic management, occupational health and safety, and the future of work.

Subject background

Algorithmic management has become increasingly widespread across sectors such as logistics, warehousing, platform work, and in health care, driven by advances in digital technologies, data analytics, and automation. Research and public debate have largely focused on the risks and challenges associated with these systems, including intensified monitoring, reduced worker autonomy, low transparency, and negative consequences for physical and psychosocial working environments.

However, algorithmic management may not only lead to poor working conditions. When designed and implemented under appropriate organisational, regulatory, and participatory conditions, digital systems may also offer opportunities to improve work organisation, transparency, safety, and workload management.

This course brings together critical perspectives, empirical research, and working-environment approaches to explore both the risks and the potential of algorithmic management. Using concrete cases and examples, it contributes to a more nuanced understanding of how digital management systems can be shaped to support sustainable and healthy working environments in line with Industry 5.0.

General course fee and cancellation information

The courses and workshops vary in price. Please note that the course fee does not cover meals or accommodation. The course fee and day-package fee are invoiced after the registration deadline.

Travel arrangements

Please refrain from booking any travel tickets until we have confirmed the course. The confirmation, which will be sent at the latest after the registration deadline, will include detailed information on the payment of the course fee and day-packages, as well as information on practical arrangements. Please note that you are not insured by NIVA.

Cancellation policy

Cancellations received by 29th of March 2027: full refund
Cancellations received by 30th of March 2027 or later: no refund

NIVA will issue an invoice or send information on how to pay the course with credit card (depending on the option chosen in the registration form) after the registration deadline.

The price is subject to minor changes.

Contact persons

Course leader

Rúni Bláfoss, Researcher at National Research Centre for the Working Environment, Denmark
email: rub@nfa.dk

Markus Due Jakobsen, Senior Researcher at National Research Centre for the Working Environment, Denmark
email: mdj@nfa.dk

In practical matters, please contact:

Nora Tobiasson, Project Manager at NIVA
email: nora.tobiasson@niva.org