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Key factors affecting European reactions to AI in European full and flawed democracies

Pham, Long, O'Sullivan, Barry orcid logoORCID: 0000-0002-0090-2085 and Mai, Tai Tan orcid logoORCID: 0000-0001-6657-0872 (2023) Key factors affecting European reactions to AI in European full and flawed democracies. In: IJCAI-DemocrAI 2023: The 2nd International Workshop on Democracy and AI in conjunction with IJCAI 2023, 20 Aug 2023, Macau.

Abstract
This study examines the key factors that affect European reactions to artificial intelligence (AI) in the context of both full and flawed democracies in Europe. Analysing a dataset of 4,006 respondents, categorised into full democracies and flawed democracies based on the Democracy Index developed by the Economist Intelligence Unit (EIU), this research identifies crucial factors that shape European attitudes toward AI in these two types of democracies. The analysis reveals noteworthy findings. Firstly, it is observed that flawed democracies tend to exhibit higher levels of trust in government entities compared to their counterparts in full democracies. Additionally, individuals residing in flawed democracies demonstrate a more positive attitude toward AI when compared to respondents from full democracies. However, the study finds no significant difference in AI awareness between the two types of democracies, indicating a similar level of general knowledge about AI technologies among European citizens. Moreover, the study reveals that trust in AI measures, specifically ``Trust AI Solution,'' does not significantly vary between full and flawed democracies. This suggests that despite the differences in democratic quality, both types of democracies have similar levels of confidence in AI solutions.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:Full democracies; Flawed democracies, Attitudes; Trust ; Awareness; Policy implications; AI and democracy
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Copyright Information:© 2023 The Authors.
Funders:European Union’s Horizon 2020, Insight the SFI Research Centre for Data Analytics, European Regional Development Fund
ID Code:29009
Deposited On:13 Sep 2023 12:45 by Tai Mai . Last Modified 16 Nov 2023 15:35
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