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{{Paper
|id=Vol-3857/short1
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|title=How sociotechnical reflection influence wellbeing and productivity during GenAI integration
|pdfUrl=https://ceur-ws.org/Vol-3857/short1.pdf
|volume=Vol-3857
|authors=Louise Harder Fischer
|dblpUrl=https://dblp.org/rec/conf/stpis/Fischer24
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==How sociotechnical reflection influence wellbeing and productivity during GenAI integration==
https://ceur-ws.org/Vol-3857/short1.pdf
How sociotechnical reflection influence wellbeing and
productivity during GenAI integration
Louise Harder Fischer1
1 IT-University of Copenhagen, Rued Langgaardsvej 7, 2100, Copenhagen, Denmark
Abstract
This brief paper summarizes the key insights from a keynote address at the STPIS 2024 workshop by
Louise Harder Fischer, an Associate Professor at the IT University of Copenhagen. Louise has long
pursued research grounded in the sociotechnical perspective, exploring how this approach—when adap-
ted to the modern world of work—can help shape workplaces where technology enhances not only pro-
ductivity but also long-term well-being. In her keynote, she shared findings from an ongoing research
project that examines how sociotechnical principles can support organizations, teams, and individuals in
achieving both productivity and well-being when integrating emerging technologies, especially intelli-
gent systems, into various professions. The first paper from this project was published in June 2024, co-
inciding with the European Conference on Information Systems.
Keywords
Sociotechnical principles, GenAI integration, STAIR Method 1
1. Introduction
This invited keynote presentation focused on showing how the development of sociotechnical
principles can guide the integration of Generative AI (GenAI) in the workplace in meaningful
ways. Reporting from a specific interventionist case study centred around a Communication
Department of a large Danish Municipality [1], the aim of the interventionist study was to
balance the benefits of AI technology with considerations of well-being, autonomy, and ethics in
knowledge work. The study is inspired by how sociotechnical principles historically has
delivered on these outcomes [2,3,4,5] emphasizing the creation of a balanced relationship
between humans and technology, that foster learning, innovation, and ethical practice in an AI-
driven future.
2. Theoretical framework and methodology
The research draws on sociotechnical theory and perspectives [2,3,4,6,7] and work design the-
ory [5]. These frameworks focus on understanding how technology shapes work and the import-
ance of well-designed jobs in promoting well-being, maintaining skills, and fostering creativity.
Theoretical underpinnings emphasize the need for a proactive approach to work design in re-
sponse to GenAI, ensuring that technology enhances rather than diminishes the quality of work
life.
An Action Design Research (ADR) approach [8] is employed, consisting of four phases and
seven guiding principles. The present research reports on the first two phases. The first phase be-
ing ‘Problem Formulation’, which centers on practice-inspired research, exploring how to facilitate
the adoption of GenAI and support meaningful knowledge work using sociotechnical
STPIS’24: 10th International Conference on Sociotechnical Perspectives in IS, Sept. 16-17, 2024, Jönköping, Sweden
Louf@itu.dk (LH, Fischer)
0000-0001-7193-3797 (LH. Fischer)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
9
principles. Theoretical foundations were integrated into the creation of an artifact that serves as
the guiding principles for GenAI adoption. The second phase of ‘Building. Intervention &
Evaluation’ covered extensive collaboration with the Communication Department, including
group interviews, workplace observations, and co-creation sessions, in which employees
actively participated in shaping the sociotechnical principles that could guide the ongoing
integration of GenAI in their work processes.
3. Development of Sociotechnical Principles
During the second intervention phase, eight sociotechnical principles were co-created with the
employees, ensuring that GenAI integration aligns with workplace values. In table 1 the eight prin-
ciples are presented. Applying these principles requires an active dialogue and reflection systemat-
ically organized making sure that when GenAI is integrated in a workflow, STP 1-8 have been con-
sidered.
Table 1. Sociotechnical principles for ongoing reflection
STP 1 Value Addition GenAI must demonstrably enhance the work and contribute
meaningfully to organizational goals.
STP2 Framework and Clear frameworks must be in place to guide the ethical and legal
Guideline Support use of GenAI, ensuring alignment with regulations such as the EU
AI Act.
STP3 Opportunities for The workplace must foster continuous learning and
Experimentation and experimentation with GenAI, supporting innovation and
Learning adaptation to new tools and usecases.
STP4 Competency Ensuring that employees have or can acquire the skills necessary to
Development effectively use GenAI in their workflows.
STP5 Autonomy and Self- Employees retain control over how GenAI is used in their tasks,
Determination safeguarding their ability to shape their work processes.
STP6 Social and Relational Maintaining the human element in workflows, ensuring that AI
Considerations does not erode social interactions and collaborative relationships.
STP7 Enhancing Vocation GenAI should support professional growth and creativity, helping
and Creativity employees to enhance their roles rather than replace them.
STP8 Ethical Reflection: Ethical considerations must be part of the discussion when using
AI, ensuring that individual beliefs and societal norms are
respected.
4. The STAIR Method, Outcomes and Reflections
The resulting framework’ is termed the STAIR Method and is an acronym for Sociotechnical
AI Reflection. The method is designed to help employees and organizations navigate the
complexities of AI integration, viewing the process as a continuous and non-linear journey. When
a new usage opportunity comes into focus, it is recommended to go through all the STP’s. In this
way the STAIR method provides a metaphorical "staircase" where professionals from various fields
(e.g., communication, law, IT, accounting) can ascend based on their interactions with GenAI. This
method emphasizes ongoing reflection, allowing organizations to respond dynamically to the
changing nature of GenAI's role in work.
The presentation emphasized that the STAIR Method and the developed principles can
support leaders in the responsible integration of GenAI, ensuring transparency, governance, and
compliance with emerging regulations such as the EU AI Act. The sociotechnical principles also
10
help maintain a balance between accountability to organizational rules and the autonomy
necessary for creative and meaningful work at the levels of individuals and groups.
5. Contributions and Future Research
The study so far offers both theoretical and practical contributions. Theoretically it proposes
the development of a "sociotechnical job crafting theory" that bridges the gap between individual
job crafting and organizational governance, focusing on a human-centered, profession-first
perspective. Practically, the STAIR Method provides a tangible framework for organizations to
manage the integration of GenAI technologies in a way that enhances productivity, well-being,
and ethical practice amidst continuous technological change on several levels.
The work suggests avenues for future research, particularly in understanding how
sociotechnical principles can continue to evolve in response to the increasing integration of
GenAI across different professions. It also emphasizes the need for practical methods to support
organizations during ongoing shifts in technology, ensuring that genAI adoption remains aligned
with professional standards, well-being, and ethical norms.
Acknowledgements
Thanks to Martin Lassen-Vernal, Head of Communication, and the entire communication
department in TMF-KK (Copenhagen Municipality), for the valuable collaboration.
References
[1] L.H. Fischer, H.W. Nicolajsen, S. Marttila, S. Sandbukt, "Crafting Meaningful Generative AI-
Enabled Knowledge Work" (2024). ECIS 2024 Proceedings. 10.
[2] A. Cherns, (1976). The Principles of Sociotechnical Design. Human Relations, 29(8), 783–
792.
[3] W. Pasmore, S. Winby, S.A Mohrman, & R. Vanasse, (2019). Reflections: Sociotechnical
Systems Design and Organization Change. Journal of Change Management, 19(2), 67–85.
[4] L.H. Fischer, N. Wunderlich & R. Baskerville (2023). Artificial Intelligence and Digital Work:
The Sociotechnical Reversal, in Proceedings of the 56th HICCS, 226-235
[5] S. K. Parker & G. Grote (2022, February 13). Automation, Algorithms, and Beyond: Why
Work Design Matters More Than Ever in a Digital World. Applied Psychology, 71(4), 1171-
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for the IS Discipline: Its Historical Legacy and its Continued Relevance. MIS Quarterly, 43(3),
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[7] L.H. Fischer & R. Baskerville (2023). Explaining sociotechnical change: An unstable
equilibrium perspective. European Journal of Information Systems, 32(4), 634-652.
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[8] M.K. Sein, O. Henfridsson, S. Purao, M. Rossi & R. Lindgren (2011). Action Design Research.
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