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IEEE AccessVolume 12, 2024, Pages 129765-129775

The Impact of Gender, Seniority, Knowledge, and Interest on Attitudes to Artificial Intelligence(Article)(Open Access)

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  • aUniversity of Belgrade, Faculty of Security Studies, Belgrade, 11000, Serbia
  • bUniversity of Belgrade, Faculty of Philosophy, Belgrade, 11000, Serbia

Abstract

Artificial intelligence (AI) has become deeply rooted in our lives, yet uncertainties persist regarding public attitudes to it, particularly among young individuals poised to engage with AI in their future careers. Understanding their perspectives is crucial not only for shaping educational frameworks, but also for assessing students' readiness to navigate the rapidly evolving technological landscape in the modern workspace. This paper examines students' attitudes to AI, as well as their interest in and knowledge about it. An adapted version of the Pew Research Center survey was used in our study to explore how gender and student seniority influence attitudes to AI generally and in specific applications such as facial recognition and self-driving cars. Our aim was to test the effects of these factors on AI attitudes, and to discover how various factors such as socio-demographics, knowledge, and interest may individually or collectively impact on AI attitudes in general, as well as in specific areas such as self-driving cars, facial recognition, or social media algorithms for fake news. We also investigated whether knowledge of AI and interest in it may serve to predict attitudes beyond the impacts of student seniority and gender. Our findings indicate that males self-report greater interest than females, but similar knowledge and general attitudes as female participants. Senior students possessed more AI knowledge compared to freshmen, but similar attitudes towards AI in general and self-driving cars. Interest in AI emerged as a significant predictor of general attitudes to AI and to self-driving cars, suggesting that increased interest correlates with more positive attitudes. © 2013 IEEE.

Author keywords

Artificial intelligenceeducationtechnological innovation

Indexed keywords

Engineering uncontrolled termsFacial recognitionPublic attitudesResearch centerSelf drivingsSociodemographicsSpecific areasStudent attitudesStudent readinessTechnological innovationUncertainty

Funding details

Funding sponsor Funding number Acronym
Science Fund of the Republic of Serbia
University of BelgradeUB
7749151
  • 1

    This work was supported by the Science Fund of the Republic of Serbia within the Framework of the \"IDEAS\" Program-Management of New Security Risks Research and Simulation Development, NEWSiMR&D, under Grant 7749151. This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the Faculty of Security Studies at the University of Belgrade.

  • 2

    The work was supported by the Science Fund of the Republic of Serbia within the framework of the 'IDEAS' Program \u2013 Management of New Security Risks Research and Simulation Development, NEWSiMR&D, #7749151.

  • ISSN: 21693536
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1109/ACCESS.2024.3454801
  • Document Type: Article
  • Publisher: Institute of Electrical and Electronics Engineers Inc.

  Kovacevic, A.; University of Belgrade, Faculty of Security Studies, Belgrade, Serbia;
© Copyright 2024 Elsevier B.V., All rights reserved.

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