The future of Big AI may lie with product-development teams. Meta reorganized its AI division. Henceforth, AI teams will report to departments that develop key products.

Officials in charge of protecting children stopped using a machine learning model designed to help them make decisions in difficult cases. The U.S. state of Oregon halted its use of an algorithm intended to identify children who may benefit from intervention.

A group of media and technology experts is working to give AI a better understanding of indigenous peoples. IVOW is a consultancy that aims to reduce machine learning bias against cultures that are underrepresented in training data by producing knowledge graphs and other resources.

OpenAI unveiled a more reliable successor to its GPT-3 natural language model. InstructGPT is a version of GPT-3 fine-tuned to minimize harmful, untruthful, and biased output. It's available via an application programming interface.

Some of the world’s largest corporations will use standardized criteria to evaluate AI systems that influence hiring and other personnel decisions.

The top artificial intelligence companies include many people who earned degrees at elite educational institutions and started their employment with prior work experience. Yet the world is full of people from nontraditional backgrounds.

There’s a reason why artificial intelligence is sometimes referred to as “software 2.0”: It represents the most significant technological advance in decades. Like any groundbreaking invention, it raises concerns about the future, and much of the media focus is on the threats it brings.

I believe that natural language processing in 2022 will re-embrace symbolic reasoning, harmonizing it with the statistical operation of modern neural networks. Let me explain what I mean by this.

From language to vision models, deep neural networks are marked by improved performance, higher efficiency, and better generalizations. Yet, these systems are also marked by perpetuation of bias and injustice.

Legislators worldwide wrote new laws — some proposed, some enacted — to rein in societal impacts of automation.What happened: Authorities at all levels ratcheted up regulatory pressure as

DeepMind released three papers that push the boundaries — and examine the issues — of large language models.

One year after her acrimonious exit from Google, ethics researcher Timnit Gebru launched an independent institute to study neglected issues in AI.

An independent investigation found evidence of racial and economic bias in a crime-prevention model used by police departments in at least nine U.S. states.

Microsoft is making GPT-3 available to selected customers through its Azure cloud service.

Is AI becoming inbred? The fear: The best models increasingly are fine-tuned versions of a small number of so-called foundation models that were pretrained on immense quantities of data scraped from the web.