A1 Journal article (refereed)
AI Ethics : An Empirical Study on the Views of Practitioners and Lawmakers (2023)


Khan Arif, A., Akbar, M. A., Fahmideh, M., Liang, P., Waseem, M., Ahmad, A., Niazi, M., & Abrahamsson, P. (2023). AI Ethics : An Empirical Study on the Views of Practitioners and Lawmakers. IEEE Transactions on Computational Social Systems, 10(6), 2971-2984. https://doi.org/10.1109/tcss.2023.3251729


JYU authors or editors


Publication details

All authors or editorsKhan Arif, Ali; Akbar, Muhammad Azeem; Fahmideh, Mahdi; Liang, Peng; Waseem, Muhammad; Ahmad, Aakash; Niazi, Mahmood; Abrahamsson, Pekka

Journal or seriesIEEE Transactions on Computational Social Systems

ISSN2373-7476

eISSN2373-7476

Publication year2023

Volume10

Issue number6

Pages range2971-2984

PublisherIEEE

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1109/tcss.2023.3251729

Publication open accessOpenly available

Publication channel open accessPartially open access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/85993

Web address of parallel published publication (pre-print)https://arxiv.org/abs/2207.01493


Abstract

Artificial intelligence (AI) solutions and technologies are being increasingly adopted in smart systems contexts; however, such technologies are concerned with ethical uncertainties. Various guidelines, principles, and regulatory frameworks are designed to ensure that AI technologies adhere to ethical well-being. However, the implications of AI ethics principles and guidelines are still being debated. To further explore the significance of AI ethics principles and relevant challenges, we conducted a survey of 99 randomly selected representative AI practitioners and lawmakers (e.g., AI engineers and lawyers) from 20 countries across five continents. To the best of our knowledge, this is the first empirical study that unveils the perceptions of two different types of population (AI practitioners and lawmakers) and the study findings confirm that transparency, accountability, and privacy are the most critical AI ethics principles. On the other hand, lack of ethical knowledge, no legal frameworks, and lacking monitoring bodies are found to be the most common AI ethics challenges. The impact analysis of the challenges across principles reveals that conflict in practice is a highly severe challenge. Moreover, the perceptions of practitioners and lawmakers are statistically correlated with significant differences for particular principles (e.g. fairness and freedom) and challenges (e.g. lacking monitoring bodies and machine distortion). Our findings stimulate further research, particularly empowering existing capability maturity models to support ethics-aware AI systems’ development and quality assessment.


Keywordsartificial intelligenceethicschallenges

Free keywordsaccountable artificial intelligence; artificial intelligence (AI); AI ethics; AI ethics principles; challenges; machine ethics


Contributing organizations


Ministry reportingYes

Reporting Year2023

Preliminary JUFO rating1


Last updated on 2024-03-04 at 18:46