Standard
Relevant distinctions in relation to explainability in the public sector. / Motzfeldt, Hanne Marie; Næsborg-Andersen, Ayo.
Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020. red. / Florinda Matos. Academic Conferences and Publishing International, 2020. s. 86-92 (Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Motzfeldt, HM & Næsborg-Andersen, A 2020,
Relevant distinctions in relation to explainability in the public sector. i F Matos (red.),
Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020. Academic Conferences and Publishing International, Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020, s. 86-92, 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020, Lisbon, Portugal,
22/10/2020.
https://doi.org/10.34190/EAIR.20.002
APA
Motzfeldt, H. M., & Næsborg-Andersen, A. (2020).
Relevant distinctions in relation to explainability in the public sector. I F. Matos (red.),
Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020 (s. 86-92). Academic Conferences and Publishing International. Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020
https://doi.org/10.34190/EAIR.20.002
Vancouver
Motzfeldt HM, Næsborg-Andersen A.
Relevant distinctions in relation to explainability in the public sector. I Matos F, red., Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020. Academic Conferences and Publishing International. 2020. s. 86-92. (Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020).
https://doi.org/10.34190/EAIR.20.002
Author
Motzfeldt, Hanne Marie ; Næsborg-Andersen, Ayo. / Relevant distinctions in relation to explainability in the public sector. Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020. red. / Florinda Matos. Academic Conferences and Publishing International, 2020. s. 86-92 (Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020).
Bibtex
@inproceedings{f45728300cb147c5bc01ff6d48128413,
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 = "Administrative law, Artificial intelligence, Explainability, Machine learning, Ombudsman, Transparency",
author = "Motzfeldt, {Hanne Marie} and Ayo N{\ae}sborg-Andersen",
year = "2020",
doi = "10.34190/EAIR.20.002",
language = "English",
series = "Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020",
pages = "86--92",
editor = "Florinda Matos",
booktitle = "Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020",
publisher = "Academic Conferences and Publishing International",
address = "United Kingdom",
note = "2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020 ; Conference date: 22-10-2020 Through 23-10-2020",
}
RIS
TY - GEN
T1 - Relevant distinctions in relation to explainability in the public sector
AU - Motzfeldt, Hanne Marie
AU - Næsborg-Andersen, Ayo
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 - 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
AN - SCOPUS:85097849338
T3 - Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020
SP - 86
EP - 92
BT - Proceedings of the 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020
A2 - Matos, Florinda
PB - Academic Conferences and Publishing International
T2 - 2nd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2020
Y2 - 22 October 2020 through 23 October 2020
ER -
