Artificial Intelligence (AI) is often portrayed as a magical black box where data goes in and something like a self-driving car comes out. Unfortunately, the magical black box is subject to any constraints on data going in. For example, poor
As practitioners and consumers of data science, how do we make ethical decisions when confronted with thorny dilemmas in artificial intelligence (AI)? How do we even recognize when those dilemmas emerge before they become public relations catastrophes? Humanities and social
We build AI and machine learning solutions for high-risk industries. We understand the unique challenges – the need to maintain safety, compliance and minimize risk, while improving robustness, fairness, and trust.