Relevant Distinctions in Relation to Explainability in the Public Sector

Hanne Marie Motzfeldt; Ayo Næsborg-Andersen

doi:10.34190/EAIR.20.002

Relevant Distinctions in Relation to Explainability in the Public Sector

Hanne Marie Motzfeldt^*, Ayo Næsborg-Andersen

^*Corresponding author for this work

University of Copenhagen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

This paper argues that jurisprudence can offer a relevant contribution to the international debate on the use of artificial intelligence in the public sector. From a legal perspective, a distinction can and should be made between two types of AI-based solutions, namely fact-producing and those that represent a transformation of norms (legislation). Under Danish Administrative Law, mainly the latter solutions must be fully explainable. This distinction might be relevant for other disciplines than jurisprudence and be a contribution to the internationally debated hot topic of whether transparency must be ensured via ethical principles or regulation.

Original language	English
Title of host publication	Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020 : ECIAIR 2020
Editors	Florinda Matos
Place of Publication	Reading, UK
Publisher	Academic Conferences and Publishing International
Publication date	2020
Pages	86-92
ISBN (Print)	9781912764747
ISBN (Electronic)	9781912764747
DOIs	https://doi.org/10.34190/EAIR.20.002
Publication status	Published - 2020
Event	European Conference on the Impact of Artificial Intelligence and Robotics - Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugal Duration: 22. Oct 2020 → 23. Oct 2020 Conference number: 2

Conference

Conference	European Conference on the Impact of Artificial Intelligence and Robotics
Number	2
Location	Instituto Universitário de Lisboa (ISCTE-IUL)
Country/Territory	Portugal
City	Lisbon
Period	22/10/2020 → 23/10/2020

Bibliographical note

Conference was held virtually.

Keywords

Administrative law
Artificial intelligence
Explainability
Machine learning
Ombudsman
Transparency

Documents & Links

10.34190/EAIR.20.002

Open Access VersionFinal published version, 153 KB

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Cite this

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title = "Relevant Distinctions in Relation to Explainability in the Public Sector",

abstract = "This paper argues that jurisprudence can offer a relevant contribution to the international debate on the use of artificial intelligence in the public sector. From a legal perspective, a distinction can and should be made between two types of AI-based solutions, namely fact-producing and those that represent a transformation of norms (legislation). Under Danish Administrative Law, mainly the latter solutions must be fully explainable. This distinction might be relevant for other disciplines than jurisprudence and be a contribution to the internationally debated hot topic of whether transparency must be ensured via ethical principles or regulation.",

keywords = "digital government, egovernment, explainability, administrative law, Administrative law, Artificial intelligence, Explainability, Machine learning, Ombudsman, Transparency",

author = "Motzfeldt, \{Hanne Marie\} and Ayo N{\ae}sborg-Andersen",

note = "Conference was held virtually.; European Conference on the Impact of Artificial Intelligence and Robotics , ECIAIR ; Conference date: 22-10-2020 Through 23-10-2020",

year = "2020",

doi = "10.34190/EAIR.20.002",

language = "English",

isbn = "9781912764747",

pages = "86--92",

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publisher = "Academic Conferences and Publishing International",

address = "United Kingdom",

}

Motzfeldt, HM & Næsborg-Andersen, A 2020, Relevant Distinctions in Relation to Explainability in the Public Sector. in F Matos (ed.), Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020: ECIAIR 2020. Academic Conferences and Publishing International, Reading, UK, pp. 86-92, European Conference on the Impact of Artificial Intelligence and Robotics , Lisbon, Portugal, 22/10/2020. https://doi.org/10.34190/EAIR.20.002

Relevant Distinctions in Relation to Explainability in the Public Sector. / Motzfeldt, Hanne Marie; Næsborg-Andersen, Ayo.
Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020: ECIAIR 2020. ed. / Florinda Matos. Reading, UK: Academic Conferences and Publishing International, 2020. p. 86-92.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Relevant Distinctions in Relation to Explainability in the Public Sector

AU - Motzfeldt, Hanne Marie

AU - Næsborg-Andersen, Ayo

N1 - Conference code: 2

PY - 2020

Y1 - 2020

N2 - This paper argues that jurisprudence can offer a relevant contribution to the international debate on the use of artificial intelligence in the public sector. From a legal perspective, a distinction can and should be made between two types of AI-based solutions, namely fact-producing and those that represent a transformation of norms (legislation). Under Danish Administrative Law, mainly the latter solutions must be fully explainable. This distinction might be relevant for other disciplines than jurisprudence and be a contribution to the internationally debated hot topic of whether transparency must be ensured via ethical principles or regulation.

AB - This paper argues that jurisprudence can offer a relevant contribution to the international debate on the use of artificial intelligence in the public sector. From a legal perspective, a distinction can and should be made between two types of AI-based solutions, namely fact-producing and those that represent a transformation of norms (legislation). Under Danish Administrative Law, mainly the latter solutions must be fully explainable. This distinction might be relevant for other disciplines than jurisprudence and be a contribution to the internationally debated hot topic of whether transparency must be ensured via ethical principles or regulation.

KW - digital government

KW - egovernment

KW - explainability

KW - administrative law

KW - Administrative law

KW - Artificial intelligence

KW - Explainability

KW - Machine learning

KW - Ombudsman

KW - Transparency

U2 - 10.34190/EAIR.20.002

DO - 10.34190/EAIR.20.002

M3 - Article in proceedings

SN - 9781912764747

SP - 86

EP - 92

BT - Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020

A2 - Matos, Florinda

PB - Academic Conferences and Publishing International

CY - Reading, UK

T2 - European Conference on the Impact of Artificial Intelligence and Robotics

Y2 - 22 October 2020 through 23 October 2020

ER -

Relevant Distinctions in Relation to Explainability in the Public Sector

Abstract

Conference

Bibliographical note

Keywords

Documents & Links

SDU Link

Fingerprint

Cite this