Developing a Conceptual Framework for Analyzing People in Unstructured Data
Abstract
Unstructured data used in foundation model development is a challenge for systematic analyses to make data use and documentation decisions. From a Responsible AI perspective, these decisions often rely upon understanding how people are represented in data. We propose a framework to guide analysis of human representation in unstructured data and identify downstream risks.
Cite
Text
Diaz et al. "Developing a Conceptual Framework for Analyzing People in Unstructured Data." NeurIPS 2023 Workshops: SoLaR, 2023.Markdown
[Diaz et al. "Developing a Conceptual Framework for Analyzing People in Unstructured Data." NeurIPS 2023 Workshops: SoLaR, 2023.](https://mlanthology.org/neuripsw/2023/diaz2023neuripsw-developing/)BibTeX
@inproceedings{diaz2023neuripsw-developing,
title = {{Developing a Conceptual Framework for Analyzing People in Unstructured Data}},
author = {Diaz, Mark and Dev, Sunipa and Reif, Emily and Denton, Emily and Prabhakaran, Vinodkumar},
booktitle = {NeurIPS 2023 Workshops: SoLaR},
year = {2023},
url = {https://mlanthology.org/neuripsw/2023/diaz2023neuripsw-developing/}
}