Assessing the Appetite for Trustworthiness and the Regulation of Artificial Intelligence in Europe

Title: Assessing the Appetite for Trustworthiness and the Regulation of Artificial Intelligence in Europe
Authors: NíFhaoláin, LabhaoiseHines, AndrewNallur, Vivek
Permanent link: http://hdl.handle.net/10197/12396
Date: 8-Dec-2020
Online since: 2021-08-09T15:07:11Z
Abstract: While Artificial Intelligence (AI) is near ubiquitous, there is no effective control framework within which it is being advanced. Without a control framework, trustworthiness of AI is impacted. This negatively affects adoption of AI and reduces its potential for social benefit. For international trade and technology cooperation, effective regulatory frameworks need to be created. This study presents a thematic analysis of national AI strategies for European countries in order to assess the appetite for an AI regulatory framework. A Declaration of Cooperation on AI was signed by EU members and non-members in 2018. Many of the signatories have adopted national strategies on AI. In general there is a high level of homogeneity in the national strategies. An expectation of regulation, in some form, is expressed in the strategies, though a reference to AI specific legislation is not universal. With the exception of some outliers, international cooperation is supported. The shape of effective AI regulation has not been agreed upon by stakeholders but governments are expecting and seeking regulatory frameworks. This indicates an appetite for regulation. The international focus has been on regulating AI solutions and not on the regulation of individuals. The introduction of a professional regulation system may be a complementary or alternative regulatory strategy. Whether the appetite and priorities seen in Europe are mirrored worldwide will require a broader study of the national AI strategy landscape.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: CEUR Workshop Proceedings
Series/Report no.: CEUR Workshop Proceedings; 2771
Copyright (published version): 2020 the Authors
Keywords: Artificial intelligenceRegulationTrustworthiness
Other versions: http://ceur-ws.org/Vol-2771/
Language: en
Status of Item: Peer reviewed
Is part of: Longo, L., Rizzo, L., Hunter, E. and Pakrushi, A. AICS 2020: Artificial Intelligence and Cognitive Science: Proceedings of The 28th Irish Conference on Artificial Intelligence and Cognitive Science Dublin, Republic of Ireland, December 7-8, 2020
Conference Details: The 28th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Republic of Ireland, 7-8 December 2020
ISSN: 1613-0073
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by/3.0/ie/
Appears in Collections:Computer Science Research Collection

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