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Exploring the Influence of AI-Based Recommenders on Human Behavior: Methodologies, Outcomes, and Future Research Directions

Exploring the Influence of AI-Based Recommenders on Human Behavior: Methodologies, Outcomes, and Future Research Directions

Practical Solutions and Value of AI-Based Recommenders

Methodologies Employed

The survey analyzes the role of recommenders in human-AI ecosystems using empirical and simulation studies. Empirical studies derive insights from real-world data, while simulation studies create synthetic data through models for controlled experimentation.

Outcomes Observed

The outcomes of AI-based recommenders are categorized into diversity, echo chambers, polarization, radicalization, inequality, and volume. These outcomes impact user behavior and societal dynamics across various online platforms.

Future Directions

The survey suggests future research in multi-disciplinary approaches, longitudinal studies, ethical considerations, and policy implications to ensure the positive development of recommender systems.

AI Solutions for Your Company

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Vladimir Dyachkov, Ph.D
Editor-in-Chief itinai.com

I believe that AI is only as powerful as the human insight guiding it.

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