219 citations · 1.8k across the 99 of their papers we have counts for
7 papers · 1 filter
Accountability of AI Under the Law: The Role of Explanation
Finale Doshi-Velez, Mason Kortz, Ryan Budish +9
The ubiquity of systems using artificial intelligence or "AI" has brought increasing attention to how those systems should be regulated. The choice of how to regulate AI systems wi…
Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017)
Been Kim, Dmitry M. Malioutov, Kush R. Varshney +1
This is the Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017), which was held in Sydney, Australia, August 10, 2017. Invited speakers w…
Transparency: Motivations and Challenges
Adrian Weller
Transparency is often deemed critical to enable effective real-world deployment of intelligent systems. Yet the motivations for and benefits of different types of transparency can…
From Parity to Preference-based Notions of Fairness in Classification
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez +2
The adoption of automated, data-driven decision making in an ever expanding range of applications has raised concerns about its potential unfairness towards certain social groups.…
On Fairness, Diversity and Randomness in Algorithmic Decision Making
Nina Grgić-Hlača, Muhammad Bilal Zafar, Krishna P. Gummadi +1
Consider a binary decision making process where a single machine learning classifier replaces a multitude of humans. We raise questions about the resulting loss of diversity in the…
Lost Relatives of the Gumbel Trick
Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani +1
The Gumbel trick is a method to sample from a discrete probability distribution, or to estimate its normalizing partition function. The method relies on repeatedly applying a rando…