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

^*Kontaktforfatter

Københavns Universitet

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › 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.

Originalsprog	Engelsk
Titel	Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020 : ECIAIR 2020
Redaktører	Florinda Matos
Udgivelsessted	Reading, UK
Forlag	Academic Conferences and Publishing International
Publikationsdato	2020
Sider	86-92
ISBN (Trykt)	9781912764747
ISBN (Elektronisk)	9781912764747
DOI	https://doi.org/10.34190/EAIR.20.002
Status	Udgivet - 2020
Begivenhed	European Conference on the Impact of Artificial Intelligence and Robotics - Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugal Varighed: 22. okt. 2020 → 23. okt. 2020 Konferencens nummer: 2

Konference

Konference	European Conference on the Impact of Artificial Intelligence and Robotics
Nummer	2
Lokation	Instituto Universitário de Lisboa (ISCTE-IUL)
Land/Område	Portugal
By	Lisbon
Periode	22/10/2020 → 23/10/2020

Bibliografisk note

Conference was held virtually.

Emneord

digital government
egovernment
explainability
administrative law

Dokumenter og links

10.34190/EAIR.20.002

Open Access VersionForlagets udgivne version, 153 KB

SDU link

Tjek adgangen til materialet i Syddansk Universitetsbiblioteks søgemaskine

Citationsformater

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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",

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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. i F Matos (red.), Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020: ECIAIR 2020. Academic Conferences and Publishing International, Reading, UK, s. 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. red. / Florinda Matos. Reading, UK: Academic Conferences and Publishing International, 2020. s. 86-92.

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

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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

Konference

Bibliografisk note

Emneord

Dokumenter og links

SDU link

Fingeraftryk

Citationsformater