Abstract
BACKGROUND: Although there is growing evidence of the use of artificial intelligence (AI) techniques in sports, ethical issues surrounding AI use are being discussed at a minimal level. Thus, this systematic scoping review aimed to summarize the current ethical implications associated with using AI in sports. METHODS: In this study, a total of 9 databases-MEDLINE/PubMed, Embase, Cochrane Library, ProQuest, EBSCOhost, IEEE Xplore, Web of Science, Scopus, and Google Scholar-were searched. The review protocol was registered (https://osf.io/42a8q) before extracting data. The search yielded 397 studies, and 25 studies met the inclusion and exclusion criteria. RESULTS: The 25 studies were categorized into 4 primary ethical concerns: fairness and bias, transparency and explainability, privacy and data ethics, and accountability in AI's application in sports. These categorizations were derived based on the systematic review of ethical issues highlighted across the selected studies. Fifteen studies delved into fairness and bias, focusing on how AI can perpetuate existing inequalities in sports. Thirteen studies addressed the lack of transparency, emphasizing the challenges in interpretability and trust in AI-driven decisions. Privacy and data ethics emerged as significant in 22 studies, highlighting risks related to the misuse of athletes' sensitive data. Finally, accountability was examined in 8 studies, stressing the ethical obligations of AI developers and users in sports contexts. The thematic analysis revealed overlapping concerns, as some studies addressed multiple issues simultaneously. CONCLUSION: Future research should focus on developing ethical frameworks tailored to underrepresented sports contexts and creating global standards for AI regulation in sports. This includes investigating the implications of AI applications in amateur sports, enhancing diversity in AI training datasets, and exploring the integration of ethical AI practices across various sports governance structures.