Like many people in the AI community, I am saddened by the sudden departure from Google of ethical AI researcher Timnit Gebru. Timnit is a tireless champion of diversity and fairness in AI. Her work, for example highlighting bias in face recognition systems, has been a productive influence on many researchers and companies. At the same time, my friend Jeff Dean built Google AI into a world-class engineering organization. I’ve seen him speak up for diversity when no one else in the room was doing so.
Having not yet spoken to either of them, I hesitate to offer my opinion on the matter at this time. But the situation highlights a larger problem in the AI community: lack of a shared set of values (such as fairness, diversity, and transparency) and norms (such as what to do when there’s a problem).
In academia, all scholars place high value on the pursuit and dissemination of knowledge. In medicine, all doctors recognize that the wellbeing of patients is their primary duty. We need that kind universal commitment in AI.
We’re building technology that affects billions of people without a coherent set of guiding principles. Many companies and think tanks have published their own codes of ethics, and these statements are important — but they are far from sufficient. We need a set of values and norms that are shared across our entire community and transcend any one company. That way, we can collectively hold individuals, companies, and perhaps even governments accountable to them and operate for the common good even when we disagree.
How can we bring the AI community together around shared values and norms? I encourage you to spend time with your teams, collaborators, and peers to discuss this difficult question. It’s past time to lay the foundation for a set of values and norms that all AI practitioners will proudly stand up for.