Bias

EPIC published a summary of AI-related laws that states and cities considered between January 2021 and August 2022.

Images in the wild may not come with labels, but they often include metadata. A new training method takes advantage of this information to improve contrastive learning.

Microsoft tightened the reins on both AI developers and customers.What’s new: The tech titan revised its Responsible AI Standard and restricted access to some AI capabilities accordingly.

Regulators are forcing Meta (formerly Facebook) to display certain advertisements more evenly across its membership.What’s new: The United States government compelled Meta to revise its ad-

The future of Big AI may lie with product-development teams.What’s new: 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.What’s new: The U.S. state of Oregon halted its use of an algorithm intended to

A group of media and technology experts is working to give AI a better understanding of indigenous peoples.What’s new: Intelligent Voices of Wisdom, or IVOW, is a consultancy that aims

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

Some of the world’s largest corporations will use standardized criteria to evaluate AI systems that influence hiring and other personnel decisions.What’s new: The Data and Trust Alliance, a nonprofit group devoted to

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.