Being a multidisciplinary research collaboration, REELER initially focused on establishing a solid foundation for common ground and collaborative learning within the project. This was achieved through literature reviews of relevant concepts and their implication for our research practices, a mapping of selected robotics activities per country in Europe, and a Best Practice Research and Observation Guide.
Through our ‘multi-variation’ approach, we have explored 11 different robot types in multi-sited fieldworks in 13 different European countries. This has ensured variation across country/nationality, human proximity, robot type, sector and/or application, and organization and funding type. In all, we have conducted 160 qualitative interviews. Each case study is summarized in a report providing a review of the type of robot and an overview of empirical findings.
After the fieldwork period, our data processing and analytical efforts began. To look for variation across cases is also a methodological take in our work, where we seek to identify diverse or aligned understandings of robotics among the interviewed robot makers and affected stakeholders. We identified 12 analytical themes that all feed into one of our main outcomes: the collectively written research publication Perspectives on Robots.
Moreover, REELER has developed and tested two tools for collaborative learning across disciplines and between affected stakeholders-robot makers. These tools are Mini-publics and Sociodrama. Mini-publics have proven to be a strong knowledge-sharing tool to facilitate collaborative learning, and it is our belief that it can improve opportunities for citizens to contribute to parliamentary deliberation on a given topic.
https://responsiblerobotics.eu/(s’ouvre dans une nouvelle fenêtre) offers guidelines for running mini-publics in project contexts.
Sociodrama and social drama have also rendered positive results of facilitating interdisciplinary collaboration that allow for new perspectives on robot design and robot uptake to be explored. Nonetheless, these action methods do come with certain limitations and thus cannot be defined as easily-accessible tools.
Alongside this work, REELER has developed a computer model on the economic impact of the introduction and diffusion of robotics notably in terms of employment, composition of the labour force, wages, income inequality, and need for labour mobility (i.e. upgrading skills). This includes estimates of various scenarios of economic added value as well as potential negative effects. It is used to study the impact of various policy measures such as robot tax, universal basic income, and flexicurity. The team has made great efforts to integrate innovation economics perspectives with the qualitative ethnographic data, which ultimately translated into an ABM-inspired ‘serious game’ which proved useful for clarifying how agents act in relation to marketing and design.
Our main results, presented at our REELER roadmap website (
https://responsiblerobotics.eu/(s’ouvre dans une nouvelle fenêtre)) are:
- The Human Proximity Model; a descriptive and prescriptive model for collaboration between robot makers and affected stakeholders
- Perspectives on Robots; an interdisciplinary publication that challenges existing notions of robots and users
- Online Toolbox; an interactive website presenting core results through fun and interactive games and illustrations
- BuildBot; a board game using data from ethnographic interviews to simulate a reflective robot design process
- Adapted Mini-Publics; new methods for engaging with different stakeholder groups
REELER researchers have disseminated results in a range of scientific journals and at various conferences; always actively involving the audience in activities of collaborative learning to engage and influence robot makers and SSH-researchers with REELER knowledge.
Conferences include
● ERF, 2017-2019
● 4S, 2017
● RoboPhilosophy 2018
● Responsible Robotics, 2018
● HRI, 2018-2019.
● SIENNA project, 2019.
● ICRES, 2019
● European Research and Innovation Days, 2019
● HAI, 2019
● IROS, 2019
● AAA, 2019