Transparency in artificial intelligence
(2020) In Internet Policy Review 9(2). p.1-16- Abstract
- This conceptual paper addresses the issues of transparency as linked to artificial intelligence (AI) from socio-legal and computer scientific perspectives. Firstly, we discuss the conceptual distinction between transparency in AI and algorithmic transparency, and argue for the wider concept ‘in AI’, as a partly contested albeit useful notion in relation to transparency. Secondly, we show that transparency as a general concept is multifaceted, and of widespread theoretical use in multiple disciplines over time, particularly since the 1990s. Still, it has had a resurgence in contemporary notions of AI governance, such as in the multitude of recently published ethics guidelines on AI. Thirdly, we discuss and show the relevance of the fact... (More)
- This conceptual paper addresses the issues of transparency as linked to artificial intelligence (AI) from socio-legal and computer scientific perspectives. Firstly, we discuss the conceptual distinction between transparency in AI and algorithmic transparency, and argue for the wider concept ‘in AI’, as a partly contested albeit useful notion in relation to transparency. Secondly, we show that transparency as a general concept is multifaceted, and of widespread theoretical use in multiple disciplines over time, particularly since the 1990s. Still, it has had a resurgence in contemporary notions of AI governance, such as in the multitude of recently published ethics guidelines on AI. Thirdly, we discuss and show the relevance of the fact that transparency expresses a conceptual metaphor of more general significance, linked to knowing, bringing positive connotations that may have normative effects to regulatory debates. Finally, we draw a possible categorisation of aspects related to transparency in AI, or what we interchangeably call AI transparency, and argue for the need of developing a multidisciplinary understanding, in order to contribute to the governance of AI as applied on markets and in society. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3f98e132-7c2f-478f-9740-734fed37ec25
- author
- Larsson, Stefan LU and Heintz, Fredrik LU
- organization
- publishing date
- 2020-05-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- transparency in AI, algorithmic transparency, explainable AI, AI governance
- in
- Internet Policy Review
- volume
- 9
- issue
- 2
- pages
- 16 pages
- publisher
- The Alexander Humboldt Institute for Internet and Society
- external identifiers
-
- scopus:85088989394
- ISSN
- 2197-6775
- DOI
- 10.14763/2020.2.1469
- project
- Lund University AI Research
- Ramverk för Hållbar AI
- Automated decision-making – Nordic perspectives
- DATA/TRUST: Tillitsbaserad personuppgiftshantering i den digitala ekonomin
- AI Transparency and Consumer Trust
- AIR Lund - Artificially Intelligent use of Registers
- language
- English
- LU publication?
- yes
- additional info
- 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 and 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. In addition, Dr. Larsson is scientific advisor for the Swedish Consumer Agency, the AI Sustainability Center (AISC), as well as the Swedish agency for digital government (DIGG). Fredrik Heintz is an Associate Professor of Computer Science at Linköping University, where he leads the Stream Reasoning group within the Division of Artificial Intelligence and Integrated Systems (AIICS), at the Department of Computer Science (IDA). His research focus is artificial intelligence, especially autonomous systems, stream reasoning and the intersection between knowledge representation and machine learning. He is the Director of the Graduate School for the Wallenberg AI, Autonomous Systems and Software Program (WASP), the President of the Swedish AI Society (SAIS), a member of the European Commission High-Level Expert Group on AI (AI HLEG), and a scientific advisor for DIGG and AISC.
- id
- 3f98e132-7c2f-478f-9740-734fed37ec25
- date added to LUP
- 2020-04-07 22:25:13
- date last changed
- 2024-05-02 06:47:29
@article{3f98e132-7c2f-478f-9740-734fed37ec25,
abstract = {{This conceptual paper addresses the issues of transparency as linked to artificial intelligence (AI) from socio-legal and computer scientific perspectives. Firstly, we discuss the conceptual distinction between transparency in AI and algorithmic transparency, and argue for the wider concept ‘in AI’, as a partly contested albeit useful notion in relation to transparency. Secondly, we show that transparency as a general concept is multifaceted, and of widespread theoretical use in multiple disciplines over time, particularly since the 1990s. Still, it has had a resurgence in contemporary notions of AI governance, such as in the multitude of recently published ethics guidelines on AI. Thirdly, we discuss and show the relevance of the fact that transparency expresses a conceptual metaphor of more general significance, linked to knowing, bringing positive connotations that may have normative effects to regulatory debates. Finally, we draw a possible categorisation of aspects related to transparency in AI, or what we interchangeably call AI transparency, and argue for the need of developing a multidisciplinary understanding, in order to contribute to the governance of AI as applied on markets and in society.}},
author = {{Larsson, Stefan and Heintz, Fredrik}},
issn = {{2197-6775}},
keywords = {{transparency in AI; algorithmic transparency; explainable AI; AI governance}},
language = {{eng}},
month = {{05}},
number = {{2}},
pages = {{1--16}},
publisher = {{The Alexander Humboldt Institute for Internet and Society}},
series = {{Internet Policy Review}},
title = {{Transparency in artificial intelligence}},
url = {{https://lup.lub.lu.se/search/files/79208055/Larsson_Heintz_2020_Transparency_in_artificial_intelligence_2020_05_05.pdf}},
doi = {{10.14763/2020.2.1469}},
volume = {{9}},
year = {{2020}},
}