activity
20172022
most citedBias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting

296 citations · 549 across the 7 of their papers we have counts for

collaborators

11 papers

cs.LG20222 cited

Doubting AI Predictions: Influence-Driven Second Opinion Recommendation

Maria De-Arteaga, Alexandra Chouldechova, Artur Dubrawski

Effective human-AI collaboration requires a system design that provides humans with meaningful ways to make sense of and critically evaluate algorithmic recommendations. In this pa…

cs.CY202138 cited

The effect of differential victim crime reporting on predictive policing systems

Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova

Police departments around the world have been experimenting with forms of place-based data-driven proactive policing for over two decades. Modern incarnations of such systems are c…

cs.CY2020173 cited

A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores

Maria De-Arteaga, Riccardo Fogliato, Alexandra Chouldechova

The increased use of algorithmic predictions in sensitive domains has been accompanied by both enthusiasm and concern. To understand the opportunities and risks of these technologi…

cs.CY2020

Proceedings of NeurIPS 2019 Workshop on Machine Learning for the Developing World: Challenges and Risks of ML4D

Maria De-Arteaga, Tejumade Afonja, Amanda Coston

This is the proceedings of the 3rd ML4D workshop which was help in Vancouver, Canada on December 13, 2019 as part of the Neural Information Processing Systems conference.

stat.AP20191 cited

Killings of social leaders in the Colombian post-conflict: Data analysis for investigative journalism

Maria De-Arteaga, Benedikt Boecking

After the peace agreement of 2016 with FARC, the killings of social leaders have emerged as an important post-conflict challenge for Colombia. We present a data analysis based on o…

cs.LG201936 cited

What's in a Name? Reducing Bias in Bios without Access to Protected Attributes

Alexey Romanov, Maria De-Arteaga, Hanna Wallach +7

There is a growing body of work that proposes methods for mitigating bias in machine learning systems. These methods typically rely on access to protected attributes such as race,…