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Well-being impact assessment of artificial intelligence-A search for causality and proposal for an open platform for well-being impact assessment of AI systems
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SYSNO ASEP 0571239 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Well-being impact assessment of artificial intelligence-A search for causality and proposal for an open platform for well-being impact assessment of AI systems Tvůrce(i) Havrda, M. (CZ)
Klocek, Adam (PSU-E) ORCID, RID, SAIČíslo článku 102294 Zdroj.dok. Evaluation and Program Planning. - : Elsevier - ISSN 0149-7189
Roč. 99, srpen (2023)Poč.str. 43 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova artificial intelligence ; well-being ; impact assessment ; causality ; open science ; complexity Vědní obor RIV AN - Psychologie Obor OECD Psychology (including human - machine relations) Způsob publikování Omezený přístup Institucionální podpora PSU-E - RVO:68081740 UT WOS 001001561000001 EID SCOPUS 85159587686 DOI 10.1016/j.evalprogplan.2023.102294 Anotace In recent years, the well-being impact assessment approach has been applied in the area of Artificial Intelligence (AI). Existing well-being frameworks and tools provide a relevant starting point. Taking into account its multidimensional nature, well-being assessment is well suited to assess both the expected positive effects of the technology as well as unintended negative consequences. To-date the establishment of causal links mostly stems from intuitive causal models. Such approaches neglect the fact that to prove causal links between the operation of an AI system and observed effects is difficult due to the immense complexity of the socio-technical context. This article aims at providing a framework for ascertaining the attribution of effects of observed impact of AI on well-being. An elaborated approach to impact assessment potentially enabling causal inferences is demonstrated. Furthermore, a new Open Platform for Well-Being Impact Assessment of AI systems (OPIA) is introduced, which is based on a distributed community to build reproducible evidence through effective identification, refinement, iterative testing, and cross-validation of expected causal structures. Pracoviště Psychologický ústav Kontakt Štěpánka Halamová, Halamova@praha.psu.cas.cz, Tel.: 222 222 096 Rok sběru 2024 Elektronická adresa https://www.sciencedirect.com/science/article/pii/S014971892300071X?via%3Dihub
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