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Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
Home Archives Volume 13 Issue 12 ijcatr13121002

IJCATR Volume 13 Issue 12

Exploring the Limitations, Challenges, and Regulatory Strategies of AI-Based Content Filtering Systems

Ugorji Clinton Chikezie, Okeke Ogochukwu C.
10.7753/IJCATR1312.1002
keywords : AI-based content filtering, Content moderation, Ethical AI, Regulatory frameworks, Free speech, Online content regulation, Bias in machine learning

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AI-based content filtering systems have become essential for moderating the vast and dynamic online space. Widely adopted by online platforms and governments, these systems promise efficiency in detecting and removing harmful content. However, their reliance on machine learning introduces critical limitations, including biases in training datasets, lack of contextual understanding, and challenges in real-time moderation. These issues undermine the effectiveness of content moderation and raise significant ethical and legal concerns, such as threats to free speech, privacy, and transparency. This paper explores the limitations and challenges inherent in AI-based content filtering systems and examines the regulatory strategies needed to address them. The study advocates for a balanced regulatory framework that ensures technological innovation while safeguarding fundamental human rights by emphasising ethical principles such as fairness, explainability, and accountability.
@artical{u13122024ijcatr13121002,
Title = "Exploring the Limitations, Challenges, and Regulatory Strategies of AI-Based Content Filtering Systems",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "13",
Issue ="12",
Pages ="5 - 13",
Year = "2024",
Authors ="Ugorji Clinton Chikezie, Okeke Ogochukwu C."}
  • The paper examines the inherent limitations of AI-based content filtering systems in handling nuanced content.
  • It identifies critical challenges, including biases, scalability issues, and contextual misinterpretation.
  • The study explores the ethical and regulatory implications of deploying AI in content moderation.
  • Recommendations are proposed for robust regulatory strategies to enhance fairness and transparency.
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