Research methodology

Ethnographic fieldwork

REELER will visit minimum 10 robot sites to observe and interview about processes of design, development and collaboration. In accordance with roboticists, we will present selected case material to directly and/or indirectly affected stakeholders and environment to hear about attitude to, envisaged use and implication of given robot.

The REELER project utilizes an ethnographic case study methodology that incorporates cases on the basis of variation within the field of robotics. Case study methodology can involve both qualitative and quantitative data collection methods. A focal point of REELER’s research is to observe and interview people who are, directly or indirectly, in contact with robots. We have chosen ethnographic fieldwork as our main research/data collection method since knowledge about the use of, or experience with, robots in real-life settings is necessary to achieve one of our main objectives: to better understand human-robot proximity.


Multi-sited cases

In REELER, each case is drawn with a particular robot as its center and engages those around the robot, including roboticists and other affected stakeholders. In this way, each case can be seen as multi-sited, mapping the network of people affecting and affected by the robot and exploring these threads. The main aim is not to address the particular concerns surrounding each robot, but to elicit, from these concerns, some general issues regarding collaboration and ethics. From the findings, REELER would develop some guidelines for future research and projects with the hope to benefit roboticists and society at large.



REELER uses the terms roboticists and affected stakeholders.

Roboticists we define as the people involved in creating robots whether they are designers, engineers, medical doctors or other types of expertise.

Affected stakeholders we define as both users expected to engage with the robots in close proximity and a wider spectrum of people, who may potentially experience the effects of the robots even if they never touch them. These may include people who expertise will change due to the implementation of robots, people who may have to learn new skills, people who may react positively or negatively to robots, people potentially made redundant, people saved by robots or whose health may be restored, or who in other ways can be said to be affected by the envisioned robotic design.  


Simulation models

Our ethnographic fieldwork will inform the development of agent-based computer models and validation tools. REELER will also develop an experimental “computational laboratory” to study collaborative learning routines in robot design, and to simulate outcomes of alternative routines, network configurations, meeting setup, schedules, etc. Additionally, we will generate a computational model, empirically calibrated with Eurostat data, that will conduct scenario analysis of the economic effects of implementation & diffusion of particular robots in terms of employment and real wages in the EU.

In combination with our qualitative analyses, these tools will be part of the ultimate REELER deliverable, the REELER Roadmap, with policy recommendations for responsible and ethical learning in robotics.