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Artificial intelligence in physical education poses ethical risks regarding data privacy, algorithmic bias, and professional agencyArtificial intelligence in school physical education poses several ethical risks

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Key Takeaway
Recognize that AI in physical education poses risks to data privacy, teacher agency, and student-teacher relationships.

This systematic review synthesizes evidence from 92 studies to identify ethical risks associated with artificial intelligence in physical education (AIPE) for children and adolescents. The review categorizes these risks into three primary dimensions: technology, physical education, and the body.

In the technology dimension, the authors identify risks including data leakage, privacy infringement, algorithmic bias, and algorithmic limitations. Within the physical education dimension, risks include the homogenization of teaching, threats to teacher professional roles, deviation from educational goals, and the potential for alienation in student and teacher relationships. In the body dimension, the review notes risks such as blurred body boundaries and the deconstruction of body meaning.

To address these concerns, the authors suggest three primary alleviation strategies: technological governance, educational regulation, and body protection. While the review provides a theoretical reference for the ethical governance of AIPE within the field of public health, the specific limitations of the included studies were not reported. The findings suggest that while AI offers potential integration, structured governance is necessary to protect student development and professional integrity.

As schools look for new ways to use technology, the role of artificial intelligence in physical education is growing. However, bringing these tools into the gym or the field comes with real concerns. A review of 92 studies highlights that AI can create risks for students and teachers alike.

Researchers identified risks in three main areas. In terms of technology, issues like data leaks and biased algorithms are concerns. In the classroom, AI could weaken the bond between students and teachers or lead to a one-size-fits-all approach to physical education. Most importantly, there are concerns about how AI might change how children perceive their own bodies and physical health.

To protect students, the review suggests using specific strategies. These include better technological governance, clearer educational rules, and specific protections for the students' physical well-being. Because this is a review of existing research rather than a new trial, these findings serve as a guide for schools to think about safety as they adopt new tools.

What this means for you:
AI in physical education can risk student privacy, teacher roles, and how children view their own bodies.

Common questions

What are the risks of using AI in physical education?

The review identified several risks. These include technology issues like data leaks and biased algorithms. In the classroom, it could lead to less personal care for students and harm the relationship between teachers and students. There are also concerns about how AI might change the way students view their own bodies.

How does AI affect the role of teachers?

The research suggests that using artificial intelligence could threaten the professional roles and agency of teachers. It might lead to more uniform teaching methods that do not account for individual student needs, potentially distancing the teacher from the student during physical education activities.

How can schools manage the risks of AI technology?

The study suggests three main ways to manage these risks: technological governance, educational regulation, and body protection. These strategies aim to ensure that AI tools are used safely and do not compromise the goals of physical education or the well-being of the students.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedSep 2026
View Original Abstract ↓
Physical education is a key public health setting for promoting physical fitness and lifelong healthy behaviors among children and adolescents. However, ethically inappropriate applications of artificial intelligence in physical education (AIPE) may undermine students’ bodily autonomy, educational equity, and the quality of their participation in health-promoting activities. This study aims to systematically identify the ethical risks associated with AIPE, analyze their causes and potential harms, and integrate targeted alleviation strategies. Following the PRISMA guidelines, a systematic search was conducted across six databases: SpringerLink, Web of Science, EBSCOhost, ScienceDirect, Scopus, and CNKI. After multiple rounds of screening, a total of 92 studies published in English or Chinese between January 2016 and May 2026 were included. A hybrid deductive-inductive thematic analysis was employed, with two researchers independently coding the included studies and cross-checking their results to extract and synthesize the types of ethical risks associated with AIPE and the corresponding alleviation strategies. Ethical risks in the technology dimension include data leakage, privacy infringement, algorithmic bias, and algorithmic limitations. Risks in the physical education dimension include homogeneous physical education teaching, threats to teachers’ professional roles and agency, deviation from the goals of physical education, homogenization of student development, alienation in teacher-student relationships, alienation in student–student relationships, lack of humanistic care, value alienation, and academic misconduct. Risks in the body dimension include blurred body boundary, body meaning deconstruction, and body value alienation. Based on the analysis of the types, causes, and potential harms of these risks, this study adopts a stakeholder perspective to develop a systematic set of alleviation strategies encompassing three key dimensions: technological governance, educational regulation, and body protection. Achieving trustworthy AIPE requires balancing technological reliability, appropriateness for physical education, and the preservation of human agency. This study provides a theoretical reference for the ethical governance of AIPE within the field of public health. Future research should strengthen empirical validation, foster international cooperation, and advance research on artificial intelligence ethics. https://www.crd.york.ac.uk/PROSPERO/view/CRD420261338255, identifier PROSPERO (CRD420261338255).
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