With drought spreading around the globe, battles over water are erupting between AI companies seeking more computing power and communities where their facilities are located.

People are turning to chatbot impersonations of lost loved ones to help them grieve. Will AI help us live after we’re dead?

Because of a bad facial recognition match and other hidden technology, Randal Reid spent nearly a week in jail, falsely accused of stealing purses in a state he said he had never even visited.

This startup wants to help millions of people whose languages are marginalized online gain better access to AI tools

Academia.edu is a platform for academics to share research papers.

The work of building public knowledge bases of AI failures can’t happen without rigorous and practical taxonomies. Check out this new report on AI harms…

With politicians struggling to curb AI harms, it’s boom time for tech lawyers.

It was only a matter of time before the Federal Trade Commission (FTC) initiated a law enforcement investigation focusing on artificial intelligence (AI).

The US already has a road map for the deployment of AI systems. Biden's promised executive order just needs to put these guidelines into practice.

With drought spreading around the globe, battles over water are erupting between AI companies seeking more computing power and communities where their facilities are located.

Companies that use AI know that they need to worry about ethics, but when they start, they tend to follow the same broken three-step process: They identify ethics with “fairness,” they focus on bias, and they look to use technical tools and stakeholder outreach to mitigate their risks. Unfortunately, this sets them up for failure. When it comes to AI, focusing on fairness and bias ignores a huge swath of ethical risks; many of these ethical problems defy technical solutions. Instead of trying to reinvent the wheel, companies should look to the medical profession, and adopt internal review boards (IRBs). IRBs, which are composed of diverse team of experts, are well suited to complex ethical questions. When given jurisdiction and power, and brought in early, they’re a powerful tool that can help companies think through hard ethical problems — saving money and brand reputation in the process.

“GPT-4, being trained off of our own textual communication, shows the same — or maybe even more exaggerated — racial and sex biases as humans" in health care.

The technology giant will stop offering automated tools that predict a person’s gender, age and emotional state and will restrict the use of its facial recognition tool.

Amid a growing call for governments to rein in the use of the technology, Microsoft became the first tech giant to join the chorus.

Dr. Alex Hanna from the Distributed AI Research (DAIR) Institute explains some of the causes of gender and racial bias in AI and discusses using a community- and value-based approach for AI development to improve equity outcomes.

The application of face recognition technology in the criminal justice system threatens to perpetuate racial inequality.

The WGA and SAG-AFTRA strikes are among the first labor protests to raise concerns about the effects of generative AI.

A quartet of the world's most famous AI labs — OpenAI, DeepMind, Anthropic and now xAI — are focused on AGI, and AI's existential risks.

It’s difficult to see how artificial intelligence systems work, and to see whose interests they work for. Regulation could make AI more trustworthy. Until then, user beware.

A guide to support responsible investing in AI and other data technologies

Dear AI researchers, please put less effort into researching how to minimize the carbon footprint of training machine learning models. Instead, please focus…

GPT-4 surprised many people with its abilities at coding, creative brainstorming, letter-writing, and other skills. How can we be less surprised by developments in machine learning? In this post, I’ll forecast the properties of large pretrained ML systems in 2030.

Left unattended, leading AI firms that threaten to exercise near-total control of the technology have devoured troves of data, novels and art from creators without permission or payment.

By Jeremy Kirshbaum, Instructor at the Generative AI Masterclass, founder of LibraryofBabel.ai and IFTF Research Affiliate

Autonowashing[ aw-ton-uh-wosh-ing ] verb. The practice of making unverified or misleading claims which misrepresent the appropriate level of human...

What is the environmental footprint of AI, the consequential ethical implications, and the social cost borne by those who don't necessarily reap the benefits…

🔥 Are you developing AI? Investing in AI? Interested in AI? Listen to what Dr. Ann Cavoukian - the inventor of privacy by design - said about AI &… | 12 comments on LinkedIn

The human gig workers behind AI are often subjected to "unfair" working conditions, a new Oxford report says

Margaret Atwood, Viet Thanh Nguyen and 8,000 others have signed an open letter asking that permission is obtained and compensation given when a writer’s work is used by AI

A wave of advanced machines is coming to the company's facilities thanks to better AI and robots smart enough to work with—and without—humans.