Regulators who want to get a grip on an emerging generation of artificially intelligent killing machines may not have much time left to do so, governments were warned on Monday. As autonomous weapons systems rapidly proliferate, including across battlefields in Ukraine and Gaza, algorithms and unmanned aerial vehicles are already helping military planners decide whether or not to hit targets. Soon, that decision could be outsourced entirely to the machines. "This is the Oppenheimer Moment of our generation," said Austrian Foreign Minister Alexander Schallenberg, referencing J. Robert Oppenheimer, who helped invent the atomic bomb in 1945 before going on to advocate for controls over the spread of nuclear arms.

It sounds like a scenario straight out of a Ridley Scott film: technology that not only sounds more "real" than actual humans, but looks more convincing, too. Yet it seems that moment has already arrived. A new study has found people are more likely to think pictures of white faces generated by AI are human than photographs of real individuals. "Remarkably, white AI faces can convincingly pass as more real than human faces – and people do not realise they are being fooled," the researchers report. The team, which includes researchers from Australia, the UK and the Netherlands, said their findings had important implications in the real world, including in identity theft, with the possibility that people could end up being duped by digital impostors.

Artificial intelligence (AI) is now so sophisticated that we can't tell the difference between fake faces and snaps of real people, a new study warns. In experiments with US citizens, more people thought AI-generated faces were human than the faces of real people. Experts are concerned that'hyper-realistic' imagery could be fueling misinformation and identity theft online by creating authentic-looking profiles of people. In the study, the researchers compared five AI faces with five human faces. So, can you tell which of these people are real?

And with it, so are the digital labor platforms used by many AI companies to employ human gig workers. Those people perform the vital but often unseen labor of generating or labeling the masses of data that AI systems heavily rely on--often as part of efforts to make AIs more reliable and less biased. Even as these workers take on the vital task of making modern AI safer, the companies that employ them are uniformly failing to meet even a basic threshold of labor rights standards, according to a new report from the University of Oxford's Internet Institute, shared exclusively with TIME. Researchers assessed 15 digital work platforms--among them Amazon Mechanical Turk, Scale AI and Appen--and found that all of them were "still far from safeguarding basic standards of fair work," according to the report. "While the run for AI deployments gets public hype and momentum, workers behind the design, building and testing of these technological solutions, unfortunately, still face enormous challenges and experience unfair working conditions," the report says.

The whole internet is blown up by ChatGPT, but what is it? ChatGPT is a powerful artificial intelligence tool that can generate human-like text. It uses state-of-the-art natural language processing (NLP) technology to understand and respond to human input. With ChatGPT, you can create engaging and realistic conversations with chatbots and other conversational systems. This opens up exciting possibilities for personalized and dynamic interactions with your audience.

BUT, you might ask yourself, how do we know this actually works? And that's where it gets fun. We need an AI facial recognition "before and after". Of course, we'll be using some of the most useful AI on the market: NicOrNot.com "Surely you can't be serious!"

As an activist, Nandini Jammi has become accustomed to getting harassed online, often by faceless social media accounts. But this time was different: a menacing tweet was sent her way from an account with a profile picture of a woman with blonde hair and a beaming smile. The woman went only by a first name, "Jessica," and her short Twitter biography read: "If you are a bully I will fight you." In her tweet sent to Jammi last July, she said: "why haven't you cleaned your info from Adult Friend Finder? It's only been three years."

More and more, federal agencies are looking to integrate artificial intelligence and automation into their day-to-day workplace functions, particularly to implement internal controls and compliance measures to counteract fraud and improve efficiency. At a Sept. 18 Association of Government Accountants (AGA) event, experts in AI and robotic process automation from public- and private-sector organizations stressed that automating lower-level functions, such as data processing claims, would free up employees to work on higher functions that require more analytical skills and mission-specific duties. "Artificial intelligence operates in real time to enable personalized experiences," said Dan Chenok, executive director of IBM's Center for the Business of Government and a former government official. Comparing AI to the chat boxes that often accompany internet users when they're shopping online, Chenok pointed out that such technologies are constantly building upon themselves to improve users' experiences and stamp out common problems that users may encounter when using a government website. AI and RPA also allow workers to identify patterns of potential fraud or other misuse, according to Jennifer Main, the chief operating officer for the Center for Medicare and Medicaid Services.

Artificial intelligence has a hype problem. The technology earns attention for its rapid developments and unique applications, but there is still a major gap when it comes to real-world implementations. In fact, Gartner data shows that while nearly half of CIOs plan to use AI, only 4 percent have actually started to implement the technology. AI faces big barriers when it comes to enterprise adoption due to return-on-investment (ROI) concerns and workforce fears that companies design the technology to replace their jobs. These challenges are a result of poor planning strategies when it comes to AI implementation and a misguided understanding of what is required to truly leverage the technology for the betterment of the whole organization. When implementing any type of technology, one of the biggest hurdles businesses face is clearly articulating both long-term and short-term expected ROI.

Microsoft today announced several improvements to its pre-built AI tools for companies, with a focus on improving facial recognition, custom image classification, and understanding important entities. The updates are included in the company's suite of Cognitive Services -- APIs that help developers deliver intelligent capabilities even if they don't have a great deal of AI expertise. The three updated services -- Microsoft's Custom Vision Service, Face API, and Bing Entity Search -- are designed to make AI easier for companies that can't keep a professional data scientist on staff. That's important, given the limited number of AI experts currently available, how much they cost to hire, and how complicated the task of rolling your own AI capabilities can be. The Custom Vision Service is now in paid public beta.