# The Frontiers of Fairness in Machine Learning

**Authors:** Alexandra Chouldechova, Aaron Roth  
**arXiv:** [1810.08810](https://arxiv.org/abs/1810.08810)  
**Date:** 2018-10-20  
**Summary page:** https://www.summarizepaper.com/en/paper/1810.08810v1/

## Key points

- Surge of interest in algorithmic fairness in academic and popular spheres
- Foundational science of fairness in machine learning still in early stages
- CCC visioning workshop in March 2018 to evaluate current state and identify future research avenues
- Report titled "The Frontiers of Fairness in Machine Learning" encapsulates workshop outcomes
- Summarizes findings, delves into recent theoretical advancements, highlights potential directions for further exploration
- Authored by Alexandra Chouldechova and Aaron Roth
- Valuable resource for understanding and contributing to evolving landscape of algorithmic fairness
- Aims to propel the field forward and foster continued innovation in ensuring fairness within machine learning systems

## Summary

In recent years, there has been a surge of interest in algorithmic fairness within the academic and popular spheres. Despite the considerable amount of work that has been generated on this topic, the foundational science of fairness in machine learning is still in its early stages. In March 2018, a group of experts gathered as part of a CCC visioning workshop to evaluate the current state of the field and identify promising avenues for future research. This report, titled "The Frontiers of Fairness in Machine Learning," encapsulates the outcomes of that workshop. The document not only summarizes the findings but also delves into recent theoretical advancements in the field and highlights potential directions for further exploration. Authored by Alexandra Chouldechova and Aaron Roth, this report serves as a valuable resource for those interested in understanding and contributing to the evolving landscape of algorithmic fairness. By providing insights from leading experts and outlining key research trajectories, it aims to propel the field forward and foster continued innovation in ensuring fairness within machine learning systems. With its comprehensive overview and forward-looking perspective, "The Frontiers of Fairness in Machine Learning" stands as a pivotal contribution to advancing our understanding and practices related to fairness in AI technologies.