Synthesis of a Framework for Applying Artificial Intelligence and Anti-Cheat Systems to Maintain Competitive Integrity in Professional Esports
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Abstract
The esports industry generates high economic value and has established a global audience base, making match credibility a critical determinant of its sustainability. However, competitive misconduct—such as auto-aim software, unauthorized environmental perception, hardware tampering, bot usage, and anti-cheat evasion techniques—severely threatens competitive integrity. This study aims to examine the role of artificial intelligence and anti-cheat systems in safeguarding competitive fairness in professional esports, while analyzing technological, ethical, privacy, and governance challenges. Utilizing a synthetic qualitative research methodology, this paper analyzes academic literature, industry reports, tournament standards, in-depth case studies, and semi-structured interviews with 15 domain experts.
The findings indicate that artificial intelligence demonstrates potential and plays a supporting role in detecting behavioral anomalies, analyzing real-time match data, reducing investigation latency, and incorporating field expert insights to assist tournament organizers' decision-making processes. Nevertheless, system effectiveness relies heavily on data quality, algorithmic explainability, false-positive mitigation, and balancing security measures with player privacy rights. Furthermore, this study proposes a framework comprising 5 core components for maintaining competitive integrity: (1) AI-driven behavioral detection, (2) multi-layered anti-cheat architecture, (3) ethical governance, (4) transparent data management, and (5) verifiable appeal mechanisms. The findings highlight that maintaining integrity in esports requires a multi-stakeholder integration of AI capabilities, regulatory frameworks, organizer accountability, and community trust.
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