University of Oulu

A. A. Khan et al., "AI Ethics: An Empirical Study on the Views of Practitioners and Lawmakers," in IEEE Transactions on Computational Social Systems, doi: 10.1109/TCSS.2023.3251729

AI ethics : an empirical study on the views of practitioners and lawmakers

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Author: Khan, Arif Ali1; Akbar, Muhammad Azeem2; Fahmideh, Mahdi3;
Organizations: 13S Empirical Software Engineering Research Unit, University of Oulu, 90014 Oulu, Finland
2Software Engineering Department, Lappeenranta-Lahti University of Technology, 15210 Lappeenranta, Finland
3School of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia
4School of Computer Science, Wuhan University, Wuhan 430072, China
5Faculty of Information Technology, University of Jyväskylä, 40014 Jyväskylä, Finland
6School of Computing and Communica- tions, Lancaster University Leipzig, 04109 Leipzig, Germany
7Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
8Faculty of Information Technology and Communication Sciences, Tampere University, 33014 Tampere, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.6 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2023
Publish Date: 2023-03-31


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.

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Series: IEEE transactions on computational social systems
ISSN: 2373-7476
ISSN-E: 2329-924X
ISSN-L: 2329-924X
Issue: Online first
DOI: 10.1109/tcss.2023.3251729
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
520 Other social sciences
Copyright information: © The Author(s) 2023. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see