SIENNA D4.6: Qualitative research exploring public attitudes to AI and robotics

Open Access

Abstract

The SIENNA project – Stakeholder-informed ethics for new technologies with high socio-economic and human rights impact (website: http://www.sienna-project.eu/) – is a European Union (EU) funded project which is part of the Horizon 2020 research and innovation programme under grant agreement no. 786641. It deals with three emerging technology areas: human genomics, human enhancement, and artificial intelligence (AI) and robots. This report presents findings from qualitative research which involved a day-long workshop in five countries comprising three two-hour discussion sessions, with one session focused on AI and robots. The overarching aim of this qualitative research was to engage a range of citizens to consider issues raised by the three technology areas. The specific objectives for the AI and robots sessions were to briefly explore citizen views and concerns about the following applications: Artificial Intelligence (AI), Robots, Drones, and Self-driving cars. Workshops were held in 5 countries: France, Germany, Poland, Greece, and Spain. Each workshop consisted of 50-53 participants (total n= 253) including a minimum of 10 participants from pre-specified vulnerable groups. This report outlines initial participant associations with the technologies and perceived benefits and concerns for their use, and provides some very early insights into what mitigation measures citizens may want to see in place to address their concerns. This qualitative research was conducted by a social research agency rather than academics. There are a number of important limitations to this research, which include referencing, methodological, sampling and analytical limitations. The results in this report should be read with reference to and in the context of these limitations. The results serve as indicative findings about public attitudes to this technology area and should be treated as a starting point for further academic research and analysis to build from. They should not be read in isolation and should be read with reference ...