I am appalled by the policy, announced on Monday by U.S. Immigrations and Customs Enforcement (ICE), that international students in the country on an F-1 visa must leave if their school goes fully online to cope with Covid-19.

We know that biased data leads to biased machine learning. But does the problem go beyond that? A few colleagues asked about this after a heated exchange on Twitter between Yann LeCun and Timnit Gebru (see “Image Resolution in Black and White” below).

I was dismayed on Monday to read that the U.S. is suspending the H1-B visa program at least through the end of the year. This effort to discourage immigration can only bring distress to workers from other countries and harm to the U.S.

I’m thrilled to announce our new Natural Language Processing Specialization! Courses 1 and 2 are available on Coursera. We expect to release Courses 3 and 4 soon.

Last week, I wrote about the diversity problem in AI and why we need to fix it. I asked you to tell us about your experiences as a Black person in AI or share the names of Black colleagues you admire.

Like many of you, I’m deeply saddened by the events of the past week. I’m horrified by the senseless violence perpetrated against Black communities and appalled by the persistent racial injustice of our society. It’s long past time to right these terrible wrongs.

I’m proud to announce that we held the 100th Pie & AI last Friday. Pie & AI is our meetup series that brings together members of the AI community worldwide for education, conversation, and a slice of pie.

I recently received an email from one of you who lives far from the major AI hubs, saying, “I feel like I’m all alone.” I want to tell you all: Even if it sometimes feels like you’re facing the challenges of work and life in isolation, you are not alone!

Inflection points in society create opportunities. The rise of online video was an inflection point that enabled scalable online education. The rise of the GPS-enabled smartphones similarly enabled Uber, Lyft, Airbnb, and many other services.

There has been a lot of excitement about the idea of using deep learning to diagnose diabetic retinopathy: That is by taking a photo of the retina and using AI to detect signs of disease.

In an earlier letter, I wrote about the challenge of robustness: A learning algorithm that performs well on test data often doesn’t work well in a practical production environment because the real world turns out to be different than the test set.

I spoke on Tuesday at Coursera’s annual conference. It was the company’s most well-attended conference yet, and the first to be held online. Higher education is in for turbulent times. With campuses shut down indefinitely...

This week’s issue of The Batch is all about medical applications of AI. Amid the current pandemic, the marriage of AI and medicine is more urgent than ever. My father is a practicing doctor, and I grew up seeing firsthand how the right...

Last week, I asked readers to tell me what they’re doing to address the Covid-19 pandemic. Many of you wrote to say you’re taking actions such as shopping for neighbors, making masks, and creating posters that promote Covid-safe practices...

In the earlier weeks of Covid-19, I didn’t want to contribute noise, so that experts in infectious disease could be heard. But now the situation has worsened. I spoke yesterday with Eric Topol, a cardiologist at Scripps Institute and author of Deep...