activity
20172022
most citedHuman Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making

72 citations · 104 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CY20221 cited

Taking Advice from (Dis)Similar Machines: The Impact of Human-Machine Similarity on Machine-Assisted Decision-Making

Nina Grgić-Hlača, Claude Castelluccia, Krishna P. Gummadi

Machine learning algorithms are increasingly used to assist human decision-making. When the goal of machine assistance is to improve the accuracy of human decisions, it might seem…

cs.CY202172 cited

Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making

Gabriel Lima, Nina Grgić-Hlača, Meeyoung Cha

How to attribute responsibility for autonomous artificial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines. This work…

cs.CY201919 cited

An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision

Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti +2

The notion of individual fairness requires that similar people receive similar treatment. However, this is hard to achieve in practice since it is difficult to specify the appropri…

cs.LG2018

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Till Speicher, Hoda Heidari, Nina Grgic-Hlaca +4

Discrimination via algorithmic decision making has received considerable attention. Prior work largely focuses on defining conditions for fairness, but does not define satisfactory…

stat.ML2018

Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Prediction

Nina Grgić-Hlača, Elissa M. Redmiles, Krishna P. Gummadi +1

As algorithms are increasingly used to make important decisions that affect human lives, ranging from social benefit assignment to predicting risk of criminal recidivism, concerns…

stat.ML201712 cited

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…