Karen Hao

Frances Haugen’s testimony at the Senate hearing today raised serious questions about how Facebook’s algorithms work—and echoes many findings from our previous investigation.

Her AI techniques are efficient and accurate while preserving fairness and privacy.

Visionaries  MIT Technology Review

Anming Hu’s case was meant to be a victory for the “China Initiative,” a US effort to root out spies. Instead, it turned more attention on the FBI.

Our understanding of progress in machine learning has been colored by flawed testing data.

An AI pioneer reflects on how companies can use machine learning to transform their operations and solve critical problems.

Algorithms are meaningless without good data. The public can exploit that to demand change.

The erratic consumer behavior during the pandemic helped Chinese e-commerce giants prepare for Singles’ Day.

Thirty years ago, Hinton’s belief in neural networks was contrarian. Now it’s hard to find anyone who disagrees, he says.

The model, a culmination of various automated and machine learning techniques, is being open-sourced to the research community.

By training GPT-2 on pixels instead of words, the model can accept half an image and predict how to complete it.

The context: One of the greatest unsolved flaws of deep learning is its vulnerability to so-called adversarial attacks. When added to the input of an AI system, these perturbations, seemingly random or undetectable to the human eye, can make things go completely awry.

When coronavirus ground the country to a halt, the agricultural industry could no longer sell its produce. E-commerce giants used the chance to bring the sector online.

We can now run powerful AI algorithms on our phones. AI has a problem: in the quest to build more powerful algorithms, researchers are using ever greater amounts of data and computing power, and relying on centralized cloud services. This not only generates alarming amounts of carbon emissions but a…

Fraudsters use fake accounts to spread spam, phishing links, or malware. Now Facebook is revealing details on how it uses AI to fight back.

Almost 200 face recognition algorithms—a majority in the industry—had worse performance on nonwhite faces, according to a landmark study. What they tested: The US National Institute of Standards and Technology (NIST) tested every algorithm on two of the most common tasks for face recognition. The fi…

A new generation of specialized hardware could make drug development and material discovery orders of magnitude faster.

The US criminal legal system uses predictive algorithms to try to make the judicial process less biased. But there’s a deeper problem.

In the last few years, the machine-learning community has blossomed, applying the technology to challenges like food security and health care.

Hackers have demonstrated some worrisome ways to manipulate and confuse the various systems on a Tesla Model S. Their most dramatic feat: sending the car careening into the oncoming traffic lane by placing a series of small stickers on the road. Attack vector: This an example of an “adversarial atta…