research
∙
05/31/2023
Designing Closed-Loop Models for Task Allocation
Automatically assigning tasks to people is challenging because human per...
share
research
∙
05/30/2022
Diverse Representation via Computational Participatory Elections – Lessons from a Case Study
Elections are the central institution of democratic processes, and often...
research
∙
05/22/2022
Addressing Strategic Manipulation Disparities in Fair Classification
In real-world classification settings, individuals respond to classifier...
research
∙
02/09/2022
Designing Closed Human-in-the-loop Deferral Pipelines
In hybrid human-machine deferral frameworks, a classifier can defer unce...
research
∙
07/15/2021
Auditing for Diversity using Representative Examples
Assessing the diversity of a dataset of information associated with peop...
research
∙
02/25/2021
Towards Unbiased and Accurate Deferral to Multiple Experts
Machine learning models are often implemented in cohort with humans in t...
research
∙
07/15/2020
Dialect Diversity in Text Summarization on Twitter
Extractive summarization algorithms can be used on Twitter data to retur...
research
∙
06/05/2019
Fair Distributions from Biased Samples: A Maximum Entropy Optimization Framework
One reason for the emergence of bias in AI systems is biased data -- dat...
research
∙
01/29/2019
Improved Adversarial Learning for Fair Classification
Motivated by concerns that machine learning algorithms may introduce sig...
research
∙
01/29/2019
Implicit Diversity in Image Summarization
Case studies, such as Kay et al., 2015 have shown that in image summariz...
research
∙
06/24/2018
Balanced News Using Constrained Bandit-based Personalization
We present a prototype for a news search engine that presents balanced v...
research
∙
06/15/2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
Developing classification algorithms that are fair with respect to sensi...
research
∙
02/12/2018
