2.3k citations · 2.8k across the 8 of their papers we have counts for
3 papers · 1 filter
Zero-shot causal learning
Hamed Nilforoshan, Michael Moor, Yusuf Roohani +5
Predicting how different interventions will causally affect a specific individual is important in a variety of domains such as personalized medicine, public policy, and online mark…
Causal Conceptions of Fairness and their Consequences
Hamed Nilforoshan, Johann Gaebler, Ravi Shroff +1
Recent work highlights the role of causality in designing equitable decision-making algorithms. It is not immediately clear, however, how existing causal conceptions of fairness re…
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…