Prevalence of Problematic Content

This project examines how AI systems operate within complex sociotechnical environments, investigating the interplay between algorithmic design, user behavior, and societal outcomes. We develop methodologies to audit AI systems across their entire lifecycle, from development to deployment.

Understanding AI impact requires examining the full sociotechnical system, including human-AI interactions, feedback loops, and emergent behaviors at scale.

Key contributions include:

Causal inference methods for measuring AI system effects
Cross-platform analysis of algorithmic influence
Longitudinal studies of AI system evolution and adaptation
Policy frameworks for responsible AI deployment and governance

Our research addresses fundamental questions about the balance between user agency and algorithmic influence in shaping online experiences and real-world outcomes. Through rigorous experimental design and field studies, we aim to separate correlation from causation in AI system evaluation.

References

2023

Deplatforming did not decrease Parler users’ activity on fringe social media

Manoel Horta Ribeiro, Homa Hosseinmardi, Robert West, and Duncan J Watts

PNAS nexus, 2023

Bib

@article{horta2023deplatforming,
  title = {Deplatforming did not decrease Parler users’ activity on fringe social media},
  author = {Horta Ribeiro, Manoel and Hosseinmardi, Homa and West, Robert and Watts, Duncan J},
  journal = {PNAS nexus},
  volume = {2},
  number = {3},
  pages = {pgad035},
  year = {2023},
  publisher = {Oxford University Press US},
}

2021

Examining the consumption of radical content on YouTube

Homa Hosseinmardi, Amir Ghasemian, Aaron Clauset, Markus Mobius, David M Rothschild, and Duncan J Watts

Proceedings of the National Academy of Sciences, 2021

Bib

@article{hosseinmardi2021examining,
  title = {Examining the consumption of radical content on YouTube},
  author = {Hosseinmardi, Homa and Ghasemian, Amir and Clauset, Aaron and Mobius, Markus and Rothschild, David M and Watts, Duncan J},
  journal = {Proceedings of the National Academy of Sciences},
  volume = {118},
  number = {32},
  pages = {e2101967118},
  year = {2021},
  publisher = {National Acad Sciences},
}