The Socio-Legal Relevance of Artificial Intelligence

Stefan Larsson

The Socio-Legal Relevance of Artificial Intelligence

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Abstract

This article 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 analyzes a set of problematic cases, e.g., image recognition based on gender-biased databases. It then presents seven aspects of transparency that may complement notions of explainable AI (XAI) within AI-research undertaken by computer scientists. The article finally discusses the normative mirroring effect of using human values and societal structures as training data for learning technologies; it concludes by arguing for the need for a multidisciplinary approach in AI research, development, and governance.

Original language	English
Pages (from-to)	573
Number of pages	593
Journal	Droit et Société
Volume	103
Issue number	3
Publication status	Published - 2019 Dec 11

Bibliographical note

Stefan Larsson is a lawyer (LLM) and Associate Professor in Technology 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 digital, data-driven markets, and the socio-legal impact of autonomous and AI-driven technologies. Among his publications:
— “Algorithmic Governance and the Need for Consumer Empowerment in Data-Driven Markets”, Internet Policy Review, 7 (2), 2018.
— Conceptions in the Code. How Metaphors Explain Legal Challenges in Digital Times, Oxford: Oxford University Press, 2017.

Subject classification (UKÄ)

Law
Computer Sciences

Free keywords

Algorithmic accountability and normative design
Applied artificial intelligence
Explainable AI and algorithmic transparency
Machine learning and law
Technology and Social change

Access to Document

Stefan Larsson 2019 THE SOCIO-LEGAL RELEVANCE OF ARTIFICIAL INTELLIGENCEFinal published version, 488 KBLicence: Unspecified

Cite this

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title = "The Socio-Legal Relevance of Artificial Intelligence",

abstract = "This article 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 analyzes a set of problematic cases, e.g., image recognition based on gender-biased databases. It then presents seven aspects of transparency that may complement notions of explainable AI (XAI) within AI-research undertaken by computer scientists. The article finally discusses the normative mirroring effect of using human values and societal structures as training data for learning technologies; it concludes by arguing for the need for a multidisciplinary approach in AI research, development, and governance.",

keywords = "applied artificial intelligence, AI and normativity, algorithmic accountability and normative design, AI transparency, AI \& society, FAT, Sociology of Law, Algorithmic accountability and normative design, Applied artificial intelligence, Explainable AI and algorithmic transparency, Machine learning and law, Technology and Social change",

author = "Stefan Larsson",

note = "Stefan Larsson is a lawyer (LLM) and Associate Professor in Technology 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 digital, data-driven markets, and the socio-legal impact of autonomous and AI-driven technologies. Among his publications: — “Algorithmic Governance and the Need for Consumer Empowerment in Data-Driven Markets”, Internet Policy Review, 7 (2), 2018. — Conceptions in the Code. How Metaphors Explain Legal Challenges in Digital Times, Oxford: Oxford University Press, 2017.",

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N2 - This article 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 analyzes a set of problematic cases, e.g., image recognition based on gender-biased databases. It then presents seven aspects of transparency that may complement notions of explainable AI (XAI) within AI-research undertaken by computer scientists. The article finally discusses the normative mirroring effect of using human values and societal structures as training data for learning technologies; it concludes by arguing for the need for a multidisciplinary approach in AI research, development, and governance.

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KW - Explainable AI and algorithmic transparency

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KW - Technology and Social change

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The Socio-Legal Relevance of Artificial Intelligence

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The Socio-Legal Relevance of Artificial Intelligence

Abstract

Bibliographical note

Subject classification (UKÄ)

Free keywords

Access to Document

Other files and links

Fingerprint

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