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To address the complexity of this phenomenon and envision more just and meaningful work, we should consider and investigate the current and future relationships that exist and might exist, between workers and robots from a transdisciplinary perspective. 

The framework we are developing is designed to foster and guide transdisciplinary speculative practices that bring together multiple disciplines, such as engineering and design, together with practitioners and workers to collaboratively envision and shape just and meaningful work when robots are implemented in the workspace alongside the workers.

Our framework explores the overarching task dimension, which is the primary context where most relationships between workers and robots are established. We chose to focus on the task dimension, recognizing several important reasons for this decision. Work is typically structured around tasks of varying complexity, and it is within this dimension that both workers and robots exercise the capabilities necessary to perform activities and actions.  

This focus serves as a crucial lever for engaging workers in becoming active participants during the speculative processes, as it is through this lens that workers’ knowledge, expertise, and experience can emerge. Lastly, by focusing on the task dimension, we can create a space where workers can actively envision and imagine possible and preferable relationships with robots, as it can provide them with connections that directly relate to their experiences. This approach can enhance their agency and empower them to express their desires, expectations, needs, and concerns, giving them a voice in meaningfully shaping these relationships. 

Our approach to speculation has four distinct characteristics: it must be collaborative and participatory to involve workers as co-creators of the speculations and to allow their agency to emerge; rooted in the contextual knowledge, experience, and expertise of the workers; present-oriented, placing greater emphasis on the present and its alternatives; and grounded in technological knowledge and understanding. 

 

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Project team

Name:
Dr. Alessandro Ianniello
Supervisor:
Prof.dr.ir. David Abbink
Partners:
FRAIM, KLM