ML Assurance Newsletter

Aug 31, 2022

Trust & AI: Must Reads

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This article resonated with the team at Monitaur, where we're dedicated to a holistic lifecycle approach to AI governance - including how we manage bias and fairness.

AI fairness is a complex topic. In this article for Protocol, Kate Kaye starts to unpack flaws in some AI fairness tools - namely the 80% (or 4/5) rule that has been used widely by both corporations as well as the government.

The harder, holistic approach to AI fairness is often ignored by conceptually "simple" fixes. We believe, along with other companies and researchers, that there's a better approach.

Ethics & Responsibility

The new NYC AI bias law that goes into effect in January 2023 is the first of its kind and leaves employers with questions that need to be answered as far as establishing compliance.

"Though it’s the first time US employers will be subject to these requirements, laws addressing AI bias in hiring are on the rise, with several states and the federal government taking steps to regulate those tools."

In this article for Bloomberg Law, J. Edward Moreno explores what this new law means for companies in New York - and why there are more laws like it to come.

Regulation & Legislation

Monitaur CEO Anthony Habayeb breaks down the recent bulletin from the California Department of Insurance, as well as other AI regulation news.

Regulation & Legislation

"Over the past 10 years — a period some A.I. researchers have begun referring to as a 'golden decade' — there’s been a wave of progress in many areas of A.I. research, fueled by the rise of techniques like deep learning and the advent of specialized hardware for running huge, computationally intensive A.I. models," writes Kevin Roose in this New York Times article.

Read the full article to learn why experts are predicting that "a wave of world-changing A.I." is right around the corner, as well as the three ideas that could help us communicate better about the risks and opportunities associated with AI.

Risks & Liability
Ethics & Responsibility

Radiologists screen more successfully for breast cancer when they are assisted by AI, than when they work alone. That same AI also produces more accurate results in the hands of a radiologist than it does when operating solo.

Learn more on this new research in this MIT Technology Review article by Hana Kiros.

This is the first article in our AI Trust library under a new category: AI impact & society. Follow our newsletter for monthly updates on this topic and more.

Impact & Society