| Prispievatelia: |
Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Technology and Society, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för teknik och samhälle, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Technology and Society, AI and Society, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för teknik och samhälle, AI och samhälle, Originator, Lund University, Faculty of Engineering, LTH, Departments at LTH, Department of Technology and Society, Real Estate Science, Lunds universitet, Lunds Tekniska Högskola, Institutioner vid LTH, Institutionen för teknik och samhälle, Fastighetsvetenskap, Originator, Lund University, Profile areas and other strong research environments, Lund University Profile areas, LU Profile Area: Human rights, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Lunds universitets profilområden, LU profilområde: Mänskliga rättigheter, Originator, Lund University, Profile areas and other strong research environments, Strategic research areas (SRA), eSSENCE: The e-Science Collaboration, Lunds universitet, Profilområden och andra starka forskningsmiljöer, Strategiska forskningsområden (SFO), eSSENCE: The e-Science Collaboration, Originator, Lund University, Faculty of Social Sciences, Departments of Administrative, Economic and Social Sciences, Department of Sociology, Gender Studies, Lunds universitet, Samhällsvetenskapliga fakulteten, Samhällsvetenskapliga institutioner och centrumbildningar, Sociologiska institutionen, Genusvetenskap, Originator |
| Popis: |
While recent progress has been made in several fields of data-intense AI-research, many applications have been shown to be prone to unintendedly reproduce social biases, sexism and stereotyping, including but not exclusive to gender. As more of these design-based, algorithmic or machine learning methodologies, here called adaptive technologies, become embedded in robotics, we see a need for a developed understanding of what role social norms play in social robotics, particularly with regards to fairness. To this end, we i) we propose a framework for a socio-legal robotics, primarily drawn from Sociology of Law and Gender Studies. This is then ii) related to already established notions of acceptability and personalisation in social robotics, here with a particular focus on iii) the interplay between adaptive technologies and social norms. In theorising this interplay for social robotics, we look not only to current statuses of social robots, but draw from identified AI-methods that can be seen to influence robotics in the near future. This theoretical framework, we argue, can help us point to concerns of relevance for questions of fairness in human-robot interaction. |
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