Putting ethical principles at the core of the research lifecycle

Ethical charter - Multimodal project

Purpose of the ethical charter

It has been well documented that machine learning research and applications can potentially lead to "data privacy issues, algorithmic biases, automation risks and malicious uses" (NeurIPS 2021 ethics guidelines). The purpose of this short document is to formalize the ethical principles that we (the multimodal learning group at Hugging Face) adopt for the project we are pursuing. By defining these ethical principles at the beginning of the project, we make them core to our machine learning lifecycle.

By being transparent about the decisions we're making in the project, who is working on which aspects of the system, and how the team can be contacted, we hope to receive feedback early enough in the process to make meaningful changes, and ground discussions about choices in an awareness of the goals we aim to achieve and the values we hope to incorporate.

This document is the result of discussions led by the multimodal learning group at Hugging Face (composed of machine learning researchers and engineers), with the contributions of multiple experts in ethics operationalization, data governance, and personal privacy.

Limitations of this ethical charter

Content policy

Studying the current state-of-the-art multimodal systems, we foresee several misuses of the technologies we aim at as part of this project. We provide guidelines on some of the use cases we ultimately want to prevent:

Values for the project

We note that some of these values can sometimes be in conflict (for instance being fair and sharing open and reproducible work, or respecting individuals’ privacy and sharing datasets), and emphasize the need to consider risks and benefits of our decisions on a case by case basis.