In November, voters in Bellingham, Washington, passed a ballot measure banning government use of face recognition technology. It added to a streak of such laws that started with San Francisco in 2019 and now number around two dozen. The spread of such bans has inspired hope from campaigners and policy experts of a turn against an artificial intelligence technology that can lead to invasions of privacy or even wrongful arrest. Such feelings got a boost when Facebook unexpectedly announced on the day of the Bellingham vote that it would shutter its own face recognition system for identifying people in photos and videos, due to "growing societal concerns." Yet a few months earlier and about 100 miles from Bellingham, the commission that runs Seattle-Tacoma International Airport passed its own face recognition restrictions that leave airlines free to use the technology for functions like bag drop and check in, although it promised to provide some oversight and barred the technology's use by port police.

Artificial intelligence (AI) has crossed a threshold. "In the past five years, AI has made the leap from something that mostly happens in research labs or other highly controlled settings to something that's out in society affecting people's lives," says Michael Littman, chair of the One Hundred Year Study on Artificial Intelligence, hosted at Stanford. It's easy to see what he's talking about: The technology's impact can be seen introducing automation, driving efficiency gains and enhancing productivity, creating new jobs, and reducing risks associated with cyber-threats and fraud. During the pandemic, AI enabled more effective testing for Covid-19 and faster vaccine development, and helped manage grocery supply chains and tailor lessons for individual students affected by remote schooling. As AI expands into more and more facets of our lives, there is also more scrutiny on who's developing it.

From self-driving cars to intuitive automatic vacuum cleaners, AI has taken over every industry and government organization around the world. Artificial intelligence is an emerging focus area of policy development in India. Many governments have begun to implement AI across various small-scale pilots. But many are still limited to implementation and experimentation. If implemented effectively, AI tools can generate benefits for both private and public-sector organizations.

Last August, Vince Patton was watching a YouTube video of a Tesla owner who had made a startling observation: Tesla drivers could now play a video game on their car's touch-screen dashboard – while the vehicle is moving. Curious to see for himself, Patton drove his own 2021 Tesla Model 3 to an empty community college parking lot, activated a game called "Sky Force Reloaded" from a menu and did a few loops. "And I was dumbfounded by that. That just seems so inherently dangerous," said Patton, a 59-year-old retired broadcast journalist who lives near Portland, Oregon. He tried Solitaire, too, and was able to activate that game while driving.

Siri, Apple's iconic AI virtual assistant, appeared to not be satisfied with Sen. Ted Cruz's attacks on Big Tech while he sat down with Fox News for an interview. Cruz, R-Texas, who was among several Republican lawmakers who spoke at Turning Point USA's AmericaFest in Phoenix this week, declared Big Tech "the single greatest threat to free speech" and "free and fair elections in America." "Big Tech, they are hard left. They're to the left of the Democratic Party. And they're trying to drive the Democratic Party left," Cruz told Fox News Digital on Monday.

The debate topic was: "This house believes that AI will never be ethical." Not a day passes without a fascinating snippet on the ethical challenges created by "black box" artificial intelligence systems. These use machine learning to figure out patterns within data and make decisions – often without a human giving them any moral basis for how to do it. Classics of the genre are the credit cards accused of awarding bigger loans to men than women, based simply on which gender got the best credit terms in the past. Or the recruitment AIs that discovered the most accurate tool for candidate selection was to find CVs containing the phrase "field hockey" or the first name "Jared". More seriously, former Google CEO Eric Schmidt recently combined with Henry Kissinger to publish The Age of AI: And Our Human Future, a book warning of the dangers of machine-learning AI systems so fast that they could react to hypersonic missiles by firing nuclear weapons before any human got into the decision-making process.

Federated learning, also known as collaborative learning, allows training models at scale on data that remains distributed on the devices where they are generated. Sensitive data remains with the owners of said data, where training is conducted, and a centralized training orchestrator of training only sees the contribution of each client through model updates. Federated learning doesn't guarantee privacy on its own (we'll touch on breaking and repairing privacy in federated learning systems later on), but it does make privacy possible. With the public and policy-makers becoming more aware of the data economy, demand for privacy-preserving machine learning is on the rise. As a result, data practices have been garnering increased scrutiny, and research on privacy-respecting tools like federated learning is increasingly active.

Cyberattacks have reached unparalleled heights. There are numerous reasons for this. The biggest cause is, of course, our growing reliance on computers. The cyberattack surface in today's enterprise environments is enormous, and it's just becoming bigger. As a result, monitoring and strengthening a company's cybersecurity posture requires more than just human interaction. As a result of this unparalleled challenge, artificial intelligence and machine learning-based cybersecurity tools have evolved to assist information security teams in reducing breach risk and improving their security posture quickly and effectively.

The Research Brief is a short take about interesting academic work. A unique material, nickel oxide demonstrates the ability to learn things about its environment in a way that emulates the most basic learning abilities of animals, as my colleagues and I describe in a new paper. For over half a century, neuroscientists have studied sea slugs to understand basic animal learning. Two fundamental concepts of learning are habituation and sensitization. Habituation occurs when an organism's response to a repeated stimulus continuously decreases.

France's foremost privacy regulator has ordered Clearview AI to delete all its data relating to French citizens, as first reported by TechCrunch. In its announcement, the French agency CNIL argued that Clearview had violated the GDPR in collecting the data and violated various other data access rights in its processing and storage. As a result, CNIL is calling on Clearview to purge the data from its systems or face escalating fines as laid out by European privacy law. Clearview rose to prominence in 2020 after a New York Times investigation highlighted the company's massive data collection efforts. In particular, the company offered the unique ability to identify subjects by name, drawing on data scraped from public-facing social networks.