Ethics and Society Newsletter #1

Hello, world!

Originating as an open-source company, Hugging Face was founded on some key ethical values in tech: collaboration, responsibility, and transparency. To code in an open environment means having your code – and the choices within – viewable to the world, associated with your account and available for others to critique and add to. As the research community began using the Hugging Face Hub to host models and data, the community directly integrated reproducibility as another fundamental value of the company. And as the number of datasets and models on Hugging Face grew, those working at Hugging Face implemented documentation requirements and free instructive courses, meeting the newly emerging values defined by the research community with complementary values around auditability and understanding the math, code, processes and people that lead to current technology.

How to operationalize ethics in AI is an open research area. Although theory and scholarship on applied ethics and artificial intelligence have existed for decades, applied and tested practices for ethics within AI development have only begun to emerge within the past 10 years. This is partially a response to machine learning models – the building blocks of AI systems – outgrowing the benchmarks used to measure their progress, leading to wide-spread adoption of machine learning systems in a range of practical applications that affect everyday life. For those of us interested in advancing ethics-informed AI, joining a machine learning company founded in part on ethical principles, just as it begins to grow, and just as people across the world are beginning to grapple with ethical AI issues, is an opportunity to fundamentally shape what the AI of the future looks like. It’s a new kind of modern-day AI experiment: What does a technology company with ethics in mind from the start look like? Focusing an ethics lens on machine learning, what does it mean to democratize good ML?

Thanks for reading! 🤗