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Ukraine Starts Using Facial Recognition To Identify Dead Russians And Tell Their Relatives – Forbes

Ukraine’s deputy prime minister says the tech will help provide transparency about how many Russian soldiers are dying in the war. Critics say the use of facial recognition in war zones is a disaster in the making.
Ukraine is using Clearview AI facial recognition to identify dead Russian soldiers as part of a campaign to combat Kremlin disinformation on the number of dead from the war.
Find a photo of a dead Russian soldier on social media. Upload it to facial recognition software. Get an identity match from a database of billions of social media images. Identify the deceased’s family and friends. Show them what happened to the victim of Putin’s war and Ukraine’s defense.
This is one of Ukraine’s strategies in trying to inform Russians, who have limited access to non-state-controlled media and information, about the death being wrought by their president’s invasion. On Wednesday, deputy prime minister and head of the Digital Transformation Ministry in Ukraine, Mykhailo Fedorov, confirmed on his Telegram profile that surveillance technology was being used in this way, a matter of weeks after Clearview AI, the New York-based facial recognition provider, started offering its services to Ukraine for those same purposes. Fedorov didn’t say what brand of artificial intelligence was being used in this way, but his department later confirmed to Forbes that it was Clearview AI, which is providing its software for free. They’ll have a good chance of getting some matches: In an interview with Reuters earlier this month, Clearview CEO Hoan Ton-That said the company had a store of 10 billion users’ faces scraped from social media, including 2 billion from Russian Facebook alternative Vkontakte. Fedorov wrote in a Telegram post that the ultimate aim was to “dispel the myth of a ‘special operation’ in which there are ‘no conscripts’ and ‘no one dies.’”
Just a month ago, Clearview AI and facial recognition were the subject of strong criticism. U.S. lawmakers decried its use by the federal government, saying the technology disproportionately targeted Black, Brown and Asian ethnicities and falsely matched them more often when compared to white individuals. They also made clear the existential threat to privacy the software posed. Civil rights organizations like the American Civil Liberties Union don’t believe the technology should be used in any setting, calling for outright bans.
The use case in Ukraine, of course, is vastly different from the ones typically seen in the U.S., which try to identify criminal suspects. Identifying dead Russian soldiers might be more acceptable, if the ultimate aim is to let people know their loved ones have died as a result of their leader’s warmongering. Not to mention that the dead don’t have a right to privacy—not according to U.S. law, anyway. It’s one reason why police are allowed to unlock iPhones or other smart devices of the deceased by holding it up to their face (even if they may not have much success, due to liveness detection). But should privacy advocates worry about the use of facial recognition in wartime, when it might legitimize the tech for use in other scenarios where the living’s privacy is under threat?
For Ukraine, it believes there is a need to identify dead Russian soldiers, as there’s much contention over the numbers of deceased military personnel. Last week, a Russian newspaper published and subsequently deleted a report claiming nearly 10,000 Russian soldiers had died since the invasion began, far more than had been previously reported. Later the tabloid claimed it had been hacked and the figures were not correct. Ukraine believes Russia is lying to its citizens about the number of the dead.
But Albert Fox Cahn, founder of the Surveillance Technology Oversight Project, said the introduction of facial recognition into the war could be disastrous, even if Ukraine is using it to tell the truth to Russian citizens. “This is a human rights catastrophe in the making. When facial recognition makes mistakes in peacetime, people are wrongly arrested. When facial recognition makes mistakes in a war zone, innocent people get shot,” he told Forbes.
“I’m terrified to think how many refugees will be wrongly stopped and shot at checkpoints because of facial recognition error. We should be supporting the Ukrainian people with the air defenses and military equipment they ask for, not by turning this heartbreaking war into a place for product promotion.”
Facial recognition has also been shown to be fallible, falsely matching images of people’s faces to the wrong identity. In the U.S., this has happened at least three times to Black individuals, who were wrongly arrested because their face erroneously matched with footage from surveillance cameras.
As Cahn noted, “When facial recognition inevitably misidentifies the dead, it will mean heartbreak for the living.”
When asked about those concerns or the use of its technology, Hoan Ton-That, CEO of Clearview AI, said, “War zones can be dangerous when there is no way to tell enemy combatants apart from civilians. Facial recognition technology can help reduce uncertainty and increase safety in these situations.”
He said that U.S.-government funded tests had shown that Clearview “can pick the correct face out of a lineup of over 12 million photos at an accuracy rate of 99.85%.” That accuracy “will prevent misidentifications from happening in the field.”
“The Ukrainian officials who have received access to Clearview AI have expressed their enthusiasm, and we await to hear more from them. We are ensuring each person with access to the tool is trained on how to use it safely and responsibly,” he added.
Whatever the morals at play, the use of facial recognition in this war is remarkable in its use as a tool in the propaganda war. Or as Ukraine would put it, the war for truth. Even Fedorov didn’t think he’d be using the technology for this before the invasion, writing in his Telegram post, “We have all changed. We started doing things we couldn’t even imagine a month ago.”
Money
Meet the cheapest US states to buy a house

A new study analyzing Zillow data has found that the monthly median sale price of a house last year was more than $500,000 in Utah, California and Colorado — and more than a staggering $800,000 in Hawaii.
The study, conducted by Studio City realtors, found that Hawaii clocked in as the most expensive state in the U.S. for homebuyers. On the island, the average home price was $805,775 — hundreds of thousands of dollars more than the cheapest state on the list.
Studio City realtor Tony Mariotti noted that market turbulence contributed to a “significant increase” in house prices across the U.S.
Home prices went up nationwide in February after months of declines amid low inventory and a small uptick in demand — and experts have said they expect affordability will continue to be a problem for prospective homebuyers in the months ahead.
Here are the priciest and cheapest U.S. states to buy a home:
The most expensive states to buy a home
Eight states and Washington, D.C., saw a monthly median sale price of a house last year of $400,000 or higher, with Oregon sitting at that exact figure.
Washington state, Nevada, Montana and Washington, D.C., came in between $402,900 and $487,500.
California, Colorado and Hawaii were the top three most expensive, at $537,000, $537,125 and $805,775 in monthly median sale prices last year, respectively.
Costs differed in different areas within states: for example, the median monthly sale price of a house last year in California’s cheapest city of Red Bluff was $320,000 — while the ticket in its most expensive city of San Jose was $1,370,000.
Money
Don’t just hug a tree this Arbor Day — plant one, too

Nearly five years ago, Hurricane Michael became the first Category 5 storm to hit the United States in 25 years. It left a trail of destruction in its wake, and my community of Panama City — located in the Florida Panhandle — was hit especially hard. Since then, working together as neighbors and citizens, we’ve made significant progress in key recovery areas, including rebuilding key and vital infrastructure, enhancing quality of life, developing our downtown, and attracting new businesses across a mix of industries. However, one of our most important recovery efforts lies within our tree canopy restoration — an often overlooked but vital area of disaster recovery and prevention.
When Hurricane Michael uprooted nearly 80 percent of Panama City’s trees — approximately a million trees, generating 5.7 million cubic yards of debris within the city — it created serious challenges. Not only did we lose the beautiful canopy from 100-year-old oak trees, but the vital function of the trees was lost, the first of which was the absorption of groundwater. The loss of so many trees significantly increased the risk of flooding in our community,
where we now experience flooding in areas that haven’t typically flooded in the 114-year history of the city. The second function lost from the lack of trees is shade.
Trees serve to mitigate the urban heat island effect, where an entire city is warmed by concrete being heated by the sun. These increased temperatures not only result in uncomfortably hot weather but can also lead to other extreme weather events like wildfires. Since the storm, Panama City has experienced increased flooding whenever thunderstorms roll through, in addition to wildfires that consumed over 40,000 acres last year – both due in part to the damaged tree canopy and loss of trees.
Money
The problems facing VA modernization are bigger than its software systems

The list of criticisms of the new Veterans Affairs (VA) electronic health record system, Oracle Cerner, is long.
Thousands of doctors’ orders went missing, putting patient safety at risk. Its downtime has been high compared to the old system, though it has improved. The new system is expensive: $16 billion so far, up from the $10 billion originally estimated. And, so far, it has been rolled out at just five of the VA’s 171 sites.
One of the problems is that the old record system, VistA, has its own lengthy list of reasons why it cannot continue to serve as the main software for VA hospitals. VistA was coded in Mumps, a computer language so old that few programmers are available to work on it. This old system is also not cloud-based, and cloud-based systems are now standard. And each VA location has customized VistA for its own particular needs, which means that each system is, in its way, unique, and interoperability is not-at-all simple.
Even those who still love VistA concede that sticking with the old software is not a long-term solution. And even in the short-term, VistA is expensive to maintain, costing $900 million for this purpose just last year. So VA has been sinking money into two different electronic health record systems, each one broken in its own way.
As of last Friday, VA has called for a complete reset of the modernization program and a halt to any further Oracle Cerner rollouts.
How did this implementation go so wrong? And what should be done now?
Electronic health record (EHR) implementations often take a long time and go over budget. And while the VA implementation of its new EHR software has been challenging for a number of reasons, all of these reasons could be, and indeed were, anticipated.
VA is unique in its geographical breadth — most EHR rollouts occur in a single health care system that is physically situated in one state, not across 50. Most EHRs, including the new Oracle Cerner system, are designed around billing, which is not a focus for providers in VA hospitals. The VA patient population is also different than the general public, with different frequencies of disease (more PTSD and missing limbs; less pregnancy and pediatric care), and it requires management of referrals and care outside the VA system.
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