The Role of Explainable AI in the Research Field of AI Ethics
Publiceringsår
2023
Upphovspersoner
Vainio-Pekka, Heidi; Agbese, Mamia Ori-Otse; Jantunen, Marianna; Vakkuri, Ville; Mikkonen, Tommi; Rousi, Rebekah; Abrahamsson, Pekka;
Abstrakt
Ethics of Artiicial Intelligence (AI) is a growing research ield that has emerged in response to the challenges related to AI. Transparency poses a key challenge for implementing AI ethics in practice. One solution to transparency issues is AI systems that can explain their decisions. Explainable AI (XAI) refers to AI systems that are interpretable or understandable to humans. The research ields of AI ethics and XAI lack a common framework and conceptualization. There is no clarity of the ield’s depth and versatility. A systematic approach to understanding the corpus is needed. A systematic review ofers an opportunity to detect research gaps and focus points. This paper presents the results of a systematic mapping study (SMS) of the research ield of the Ethics of AI. The focus is on understanding the role of XAI and how the topic has been studied empirically. An SMS is a tool for performing a repeatable and continuable literature search. This paper contributes to the research ield with a Systematic Map that visualizes what, how, when, and why XAI has been studied empirically in the ield of AI ethics. The mapping reveals research gaps in the area. Empirical contributions are drawn from the analysis. The contributions are relected on in regards to theoretical and practical implications. As the scope of the SMS is a broader research area of AI ethics the collected dataset opens possibilities to continue the mapping process in other directions.
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Publikationstyp
Publikationsform
Artikel
Moderpublikationens typ
Tidning
Artikelstyp
En originalartikel
Målgrupp
VetenskapligKollegialt utvärderad
Kollegialt utvärderadUKM:s publikationstyp
A1 Originalartikel i en vetenskaplig tidskriftPublikationskanalens uppgifter
Förläggare
Volym
13
Nummer
4
Artikelnummer
26
ISSN
Publikationsforum
Publikationsforumsnivå
1
Öppen tillgång
Öppen tillgänglighet i förläggarens tjänst
Ja
Öppen tillgång till publikationskanalen
Delvis öppen publikationskanal
Licens för förläggarens version
CC BY
Parallellsparad
Ja
Övriga uppgifter
Vetenskapsområden
Data- och informationsvetenskap
Nyckelord
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Publiceringsland
Förenta staterna (USA)
Förlagets internationalitet
Internationell
Språk
engelska
Internationell sampublikation
Nej
Sampublikation med ett företag
Nej
DOI
10.1145/3599974
Publikationen ingår i undervisnings- och kulturministeriets datainsamling
Ja