Emily Black

Emily Black is Assistant Professor of Computer Science and Engineering at NYU Tandon and Data Science at NYU CDS. Her research develops methods for fairness and accountability in AI systems, focusing on high-stakes domains like government and law.

Key research areas:

• Legal implications of model multiplicity and less discriminatory algorithms
• Pipeline-aware fairness across ML development lifecycle
• Consistent predictions and counterfactuals for reliable AI
• Algorithmic fairness in tax auditing and public policy

Her interdisciplinary approach bridges computer science, law, and policy to prevent algorithmic harm. Current projects examine how model instability creates unfair outcomes and how pipeline interventions can mitigate bias while maintaining utility.