Towards a Human-Centered Approach for Automating Data Science

HCAIAutoDS Teaser

Abstract

Technology for Automating Data Science (AutoDS) consistently undervalues the role of human labor, resulting in tools that, at best, are ignored and, at worst, can actively mislead or even cause harm. Even if full and frictionless automation were possible, human oversight is still desired and required to review the outputs of AutoDS tooling and integrate them into decision-making processes. We propose a human-centered lens to AutoDS that emphasizes the collaborative relationships between humans and these automated processes and elevates the effects these interactions have on downstream decision-making. Our approach leverages a provenance framework that integrates user-, data-, and model-centric approaches to make AutoDS platforms observable and interrogable by humans.


Citation

Anamaria Crisan, Lars Kotthoff, Marc Streit, Kai Xu
Towards a Human-Centered Approach for Automating Data Science
Workshop on Human-Centered AI at NeurIPS (Preprint), 2022.

BibTeX

@article{,
    title = {Towards a Human-Centered Approach for Automating Data Science},
    author = {Anamaria Crisan and Lars Kotthoff and Marc Streit and Kai Xu},
    journal = {Workshop on Human-Centered AI at NeurIPS (Preprint)},
    url = {https://research.tableau.com/paper/towards-human-centered-approach-automating-data-science},
    month = {December},
    year = {2022}
}