Ashton Anderson

Ashton Anderson is an Associate Professor in the Department of Computer Science at the University of Toronto. He specializes in research at the intersection of AI, data, and society, focusing on human-AI collaboration, algorithmic fairness, and computational social science. Anderson leads the Computational Social Science Lab, which investigates social dynamics through computational models.

• Education: Master's in Computer Science (Stanford University, 2010)
• Education: Bachelor of Engineering in Software Engineering (McGill University, 2008)

His work bridges artificial intelligence with social science, examining behavioral modeling, algorithmic ethics, and social media dynamics. Recent projects analyze human-AI alignment in chess, transparency in LLMs, and polarization in online discourse.

Key publication trends include:

• Human-AI interaction frameworks
• Explainability and fairness in algorithmic systems
• Behavioral stylometry through chess data
• LLM optimization and contextual learning
• Social polarization and content virality

Scientific recognition includes:

• Best Paper runner-up at WWW 2014
• Google PhD Fellowship in Social Computing (2012)
• Two Honorable Mentions at CHI 2025

Anderson's research involves collaborations with institutions like Microsoft Research, Google, and Facebook's Core Data Science team. His lab explores societal impacts of large language models and develops methodologies for ethically aligned AI systems.