<ul><li>Advances in AI-generated content have raised concerns about misinformation, copyright infringement, security threats, and erosion of public trust.</li><li>Detection techniques include observation-based strategies, linguistic and statistical analysis, model-based pipelines, watermarking and fingerprinting, and ensemble approaches.</li><li>The paper highlights the importance of robustness, adaptation to improving generative architectures, and human-in-the-loop verification.</li><li>Challenges include adversarial transformations, domain generalization, and ethical concerns.</li></ul>

A Practical Synthesis of Detecting AI-Generated Textual, Visual, and Audio Content

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