The Socio-Legal Relevance of Artificial Intelligence (report)

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The Socio-Legal Relevance of Artificial Intelligence (report). / Larsson, Stefan.

Stockholm : AI Sustainability Center, 2019. 40 p.

Research output: Book/ReportReport

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Larsson S 2019. The Socio-Legal Relevance of Artificial Intelligence (report). Stockholm: AI Sustainability Center. 40 p.

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Larsson S. The Socio-Legal Relevance of Artificial Intelligence (report). Stockholm: AI Sustainability Center, 2019. 40 p.

Author

Larsson, Stefan. / The Socio-Legal Relevance of Artificial Intelligence (report). Stockholm : AI Sustainability Center, 2019. 40 p.

RIS

TY - BOOK

T1 - The Socio-Legal Relevance of Artificial Intelligence (report)

AU - Larsson, Stefan

N1 - Stefan Larsson is a lawyer (LLM) and Associate Professor in Techno- logy and Social Change at Lund University, Department of Technology and Society. He holds a PhD in Sociology of Law as well as a PhD in Spatial Planning. In addition, Dr. Larsson is a senior researcher and head of the Digital Society program at the Swedish think tank Fores and scientific advisor for the Swedish Consumer Agency as well as the AI Sustainability Center. His research focuses on issues of trust and transparency on dig- ital, data-driven markets, and the socio-legal impact of autonomous and AI-driven technologies.

PY - 2019/12/3

Y1 - 2019/12/3

N2 - The report draws on socio-legal theory in relation to growing concerns over fairness, accountability and transparency of societally applied artificial intelligence (AI) and machine learning. The purpose is to contribute to a broad socio-legal orientation by describing legal and normative challenges posed by applied AI. To do so, the article first analyses a set of problematic cases, e.g. image recognition based on gender-biased data-bases. It then presents seven aspects of transparency that may complement notions of explainable AI within computer scientific AI-research. The article finally discusses the normative mirroring effect of using human values and societal structures as training data for learning technologies and concludes by arguing for the need for a multidisciplinary approach in AI research, development and governance.

AB - The report draws on socio-legal theory in relation to growing concerns over fairness, accountability and transparency of societally applied artificial intelligence (AI) and machine learning. The purpose is to contribute to a broad socio-legal orientation by describing legal and normative challenges posed by applied AI. To do so, the article first analyses a set of problematic cases, e.g. image recognition based on gender-biased data-bases. It then presents seven aspects of transparency that may complement notions of explainable AI within computer scientific AI-research. The article finally discusses the normative mirroring effect of using human values and societal structures as training data for learning technologies and concludes by arguing for the need for a multidisciplinary approach in AI research, development and governance.

KW - Socio-legal relevance of AI

KW - Transparency in AI

KW - Sociology of law

KW - Technology and society

KW - Fairness in AI

KW - Accountability in AI

KW - The normative mirroring effect

UR - http://www.aisustainability.org/wp-content/uploads/2019/11/Socio-Legal_relevance_of_AI.pdf

UR - http://www.aisustainability.org/the-socio-legal-relevance-of-artificial-intelligence/

M3 - Rapport

BT - The Socio-Legal Relevance of Artificial Intelligence (report)

PB - AI Sustainability Center

CY - Stockholm

ER -