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SYDNEY — Researchers in New Zealand say that artificial intelligence, or AI, can help solve problems for patients and doctors.  

A new study from the University of Auckland says that an emerging area is the use of AI during operations using so-called “computer vision.”

The study, published in the journal Nature Medicine, says that artificial intelligence has the potential to identify abnormalities during operations and to unburden overloaded hospitals by enhancing the monitoring of patients to help them recover after surgery at home.

The New Zealand research details how AI “tools are rapidly maturing for medical applications.”  It asserts that “medicine is entering an exciting phase of digital innovation.”

The New Zealand team is investigating computer vision, which describes a machine’s understanding of videos and images. 

Dr. Chris Varghese, a doctoral researcher in the Department of Surgery at the Faculty of Medical and Health Sciences at the University of Auckland, led the AI research team.

He told VOA the technology has great potential.

“The use of AI in surgery is a really emerging field. We are seeing a lot of exciting research looking at what we call computer vision, where AI is trying to learn what surgeons see, what the surgical instruments look like, what the different organs look like, and the potential there is to identify abnormal anatomy or what the safest approach to an operation might be using virtual reality and augmented reality to plan ahead of surgeries, which could be really useful in cutting out cancers and things like that.”

Varghese said doctors in New Zealand are already using AI to help sort through patient backlogs.

“We are using automated algorithms to triage really long waiting lists,” he said. “So, getting people prioritized and into clinics ahead of time, based on need, so the right patients are seen at the right time.”

The researchers said there are limitations to the use of artificial intelligence because of concerns about data privacy and ethics.

The report concludes that “numerous apprehensions remain with regard to the integration of AI into surgical practice, with many clinicians perceiving limited scope in a field dominated by experiential” technology.

The study also says that “autonomous robotic surgeons…. is the most distant of the realizable goals of surgical AI systems.”
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WASHINGTON — U.S. President Joe Biden on Tuesday unveiled a bundle of steep tariff increases on an array of Chinese imports including electric vehicles, computer chips and medical products, risking an election-year standoff with Beijing in a bid to woo voters who give his economic policies low marks.

Biden will keep tariffs put in place by his Republican predecessor Donald Trump while ratcheting up others, including a quadrupling of EV duties to over 100%, the White House said in a statement. It cited “unacceptable risks” to U.S. economic security posed by what it considers unfair Chinese practices that are flooding global markets with cheap goods.

The new measures impact $18 billion in Chinese imported goods including steel and aluminum, semiconductors, batteries, critical minerals, solar cells and cranes, the White House said. The announcement confirmed earlier Reuters reporting.

The United States imported $427 billion in goods from China in 2023 and exported $148 billion to the world’s No. 2 economy, according to the U.S. Census Bureau, a trade gap that has persisted for decades and become an ever more sensitive subject in Washington.

“China’s using the same playbook it has before to power its own growth at the expense of others by continuing to invest, despite excess Chinese capacity and flooding global markets with exports that are underpriced due to unfair practices,” White House National Economic Adviser Lael Brainard told reporters on a conference call.

U.S. Trade Representative Katherine Tai said the revised tariffs were justified because China was continuing to steal U.S. intellectual property and in some cases had become “more aggressive” in cyber intrusions targeting American technology.

She said prior “Section 301” tariffs had minimal impact on U.S. economy-wide prices and employment, but had been effective in reducing U.S. imports of Chinese goods, while increasing imports from other countries.

But Tai recommended tariff exclusions for dozens of industrial machinery import categories from China, including 19 for solar product manufacturing equipment.

Even as Biden’s steps fell in line with Trump’s premise that tougher trade measures are warranted, the Democrat took aim at his opponent in November’s election.

The White House said Trump’s 2020 trade deal with China did not increase American exports or boost American manufacturing jobs, and it said the 10% across-the-board tariffs on goods from all points of origin that Trump has proposed would frustrate U.S. allies and raise prices. Trump has floated tariffs of 60% or higher on all Chinese goods.

Administration officials said their measures are “carefully targeted,” combined with domestic investment, plotted with close allies and unlikely to worsen a bout of inflation that has already angered U.S. voters and imperiled Biden’s re-election bid. They also downplayed the risk of retaliation from Beijing.

Biden has struggled to convince voters of the efficacy of his economic policies despite a backdrop of low unemployment and above-trend economic growth. A Reuters/Ipsos poll last month showed Trump had a 7 percentage-point edge over Biden on the economy.

Analysts have warned that a trade tiff could raise costs for EVs overall, hurting Biden’s climate goals and his aim to create manufacturing jobs.

Biden has said he wants to win this era of competition with China but not to launch a trade war that could hurt the mutually dependent economies. He has worked in recent months to ease tensions in one-on-one talks with Chinese President Xi Jinping.

Both 2024 U.S. presidential candidates have sharply departed from the free-trade consensus that once reigned in Washington, a period capped by China’s joining the World Trade Organization in 2001.

China has said the tariffs are counterproductive and risk inflaming tensions. Trump’s broader imposition of tariffs during his 2017-2021 presidency kicked off a tariff war with China.

As part of the long-awaited tariff update, Biden will increase tariffs this year under Section 301 of the Trade Act of 1974 from 25% to 100% on EVs, bringing total duties to 102.5%, from 7.5% to 25% on lithium-ion EV batteries and other battery parts and from 25% to 50% on photovoltaic cells used to make solar panels. “Certain” critical minerals will have their tariffs raised from nothing to 25%.

The tariffs on ship-to-shore cranes will rise to 25% from zero, those on syringes and needles will rise to 50% from nothing now and some personal protective equipment (PPE) used in medical facilities will rise to 25% from as little as 0% now. Shortages in PPE made largely in China hampered the United States’ COVID-19 response.

More tariffs will follow in 2025 and 2026 on semiconductors, whose tariff rate will double to 50%, as well as lithium-ion batteries that are not used in elective vehicles, graphite and permanent magnets as well as rubber medical and surgical gloves.

A step Biden previously announced to raise tariffs on some steel and aluminum products will take effect this year, the White House said.  

A number of lawmakers have called for massive hikes on Chinese vehicle tariffs. There are relatively few Chinese-made light-duty vehicles being imported now. Senate Banking Committee Chairman Sherrod Brown wants the Biden administration to ban Chinese EVs outright, over concerns they pose risks to Americans’ personal data.

U.S. Treasury Secretary Janet Yellen, who warned China in April that its excess production of EVs and solar products was unacceptable, said that such concerns were widely shared by U.S. allies and the actions were “motivated not by anti-China policy but by a desire to prevent damaging economic dislocation from unfair economic practices.” 
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Seafaring robots are increasingly used for tasks ranging from ocean exploration to rescue missions. Matt Dibble has the latest in this week’s episode of LogOn.
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As generative AI technologies like ChatGPT rapidly gain popularity, they are beginning to change the future of the job market. Some fear mass unemployment, but others see a bright future for human-AI cooperation. Maxim Adams has the story.
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Washington — Two Air Force fighter jets recently squared off in a dogfight in California. One was flown by a pilot. The other wasn’t.

That second jet was piloted by artificial intelligence, with the Air Force’s highest-ranking civilian riding along in the front seat. It was the ultimate display of how far the Air Force has come in developing a technology with its roots in the 1950s. But it’s only a hint of the technology yet to come.

The United States is competing to stay ahead of China on AI and its use in weapon systems. The focus on AI has generated public concern that future wars will be fought by machines that select and strike targets without direct human intervention. Officials say this will never happen, at least not on the U.S. side. But there are questions about what a potential adversary would allow, and the military sees no alternative but to get U.S. capabilities fielded fast.

“Whether you want to call it a race or not, it certainly is,” said Adm. Christopher Grady, vice chairman of the Joint Chiefs of Staff. “Both of us have recognized that this will be a very critical element of the future battlefield. China’s working on it as hard as we are.”

A look at the history of military development of AI, what technologies are on the horizon and how they will be kept under control:

From machine learning to autonomy

AI’s military roots are a hybrid of machine learning and autonomy. Machine learning occurs when a computer analyzes data and rule sets to reach conclusions. Autonomy occurs when those conclusions are applied to act without further human input.

This took an early form in the 1960s and 1970s with the development of the Navy’s Aegis missile defense system. Aegis was trained through a series of human-programmed if/then rule sets to be able to detect and intercept incoming missiles autonomously, and more rapidly than a human could. But the Aegis system was not designed to learn from its decisions and its reactions were limited to the rule set it had.

“If a system uses ‘if/then’ it is probably not machine learning, which is a field of AI that involves creating systems that learn from data,” said Air Force Lt. Col. Christopher Berardi, who is assigned to the Massachusetts Institute of Technology to assist with the Air Force’s AI development.

AI took a major step forward in 2012 when the combination of big data and advanced computing power enabled computers to begin analyzing the information and writing the rule sets themselves. It is what AI experts have called AI’s “big bang.”

The new data created by a computer writing the rules is artificial intelligence. Systems can be programmed to act autonomously from the conclusions reached from machine-written rules, which is a form of AI-enabled autonomy.

Testing an AI alternative to GPS navigation

Air Force Secretary Frank Kendall got a taste of that advanced warfighting this month when he flew on Vista, the first F-16 fighter jet to be controlled by AI, in a dogfighting exercise over California’s Edwards Air Force Base.

While that jet is the most visible sign of the AI work underway, there are hundreds of ongoing AI projects across the Pentagon.

At MIT, service members worked to clear thousands of hours of recorded pilot conversations to create a data set from the flood of messages exchanged between crews and air operations centers during flights, so the AI could learn the difference between critical messages like a runway being closed and mundane cockpit chatter. The goal was to have the AI learn which messages are critical to elevate to ensure controllers see them faster.

In another significant project, the military is working on an AI alternative to GPS satellite-dependent navigation.

In a future war high-value GPS satellites would likely be hit or interfered with. The loss of GPS could blind U.S. communication, navigation and banking systems and make the U.S. military’s fleet of aircraft and warships less able to coordinate a response.

So last year the Air Force flew an AI program — loaded onto a laptop that was strapped to the floor of a C-17 military cargo plane — to work on an alternative solution using the Earth’s magnetic fields.

It has been known that aircraft could navigate by following the Earth’s magnetic fields, but so far that hasn’t been practical because each aircraft generates so much of its own electromagnetic noise that there has been no good way to filter for just the Earth’s emissions.

“Magnetometers are very sensitive,” said Col. Garry Floyd, director for the Department of Air Force-MIT Artificial Intelligence Accelerator program. “If you turn on the strobe lights on a C-17 we would see it.”

The AI learned through the flights and reams of data which signals to ignore and which to follow and the results “were very, very impressive,” Floyd said. “We’re talking tactical airdrop quality.”

“We think we may have added an arrow to the quiver in the things we can do, should we end up operating in a GPS-denied environment. Which we will,” Floyd said.

The AI so far has been tested only on the C-17. Other aircraft will also be tested, and if it works it could give the military another way to operate if GPS goes down.

Safety rails and pilot speak

Vista, the AI-controlled F-16, has considerable safety rails as the Air Force trains it. There are mechanical limits that keep the still-learning AI from executing maneuvers that would put the plane in danger. There is a safety pilot, too, who can take over control from the AI with the push of a button.

The algorithm cannot learn during a flight, so each time up it has only the data and rule sets it has created from previous flights. When a new flight is over, the algorithm is transferred back onto a simulator where it is fed new data gathered in-flight to learn from, create new rule sets and improve its performance.

But the AI is learning fast. Because of the supercomputing speed AI uses to analyze data, and then flying those new rule sets in the simulator, its pace in finding the most efficient way to fly and maneuver has already led it to beat some human pilots in dogfighting exercises.

But safety is still a critical concern, and officials said the most important way to take safety into account is to control what data is reinserted into the simulator for the AI to learn from.
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sacramento, california — California could soon deploy generative artificial intelligence tools to help reduce traffic jams, make roads safer and provide tax guidance, among other things, under new agreements announced Thursday as part of Governor Gavin Newsom’s efforts to harness the power of new technologies for public services. 

The state is partnering with five companies to create generative AI tools using technologies developed by tech giants such as Microsoft-backed OpenAI and Google- and Amazon-backed Anthropic that would ultimately help the state provide better services to the public, administration officials said. 

“It is a very good sign that a lot of these companies are putting their focus on using GenAI for governmental service delivery,” said Amy Tong, secretary of government operations for California. 

The companies will start a six-month internal trial in which state workers test and evaluate the tools. The companies will be paid $1 for their proposals. The state, which faces a significant budget deficit, can then reassess whether any tools could be fully implemented under new contracts. All the tools are considered low risk, meaning they don’t interact with confidential data or personal information, an administration spokesperson said. 

Newsom, a Democrat, touts California as a global hub for AI technology, noting 35 of the world’s top 50 AI companies are located in the state. He signed an executive order last year requiring the state to start exploring responsible ways to incorporate generative AI by this summer, with a goal of positioning California as an AI leader.

In January, the state started asking technology companies to come up with generative AI tools for public services. Last month, California was one of the first states to roll out guidelines on when and how state agencies could buy such tools. 

Generative AI, a branch of AI that can create new content such as text, audio and photos, has significant potential to help government agencies become more efficient, but there’s also an urgent need for safeguards to limit risks, state officials and experts said. In New York City, an AI-powered chatbot created by the city to help small businesses was found to dole out false guidance and advise companies to violate the law. The rapidly growing technology has also raised concerns about job losses, misinformation, privacy and automation bias. 

While state governments are struggling to regulate AI in the private sector, many are exploring how public agencies can leverage the powerful technology for public good. California’s approach, which also requires companies to disclose what large language models they use to develop AI tools, is meant to build public trust, officials said. 

The state’s testing of the tools and collecting of feedback from state workers are some of the best practices to limit potential risks, said Meredith Lee, chief technical adviser for the University of California-Berkeley’s College of Computing, Data Science and Society. The challenge is determining how to assure continued testing and learning about the tools’ potential risks after deployment. 

“This is not something where you just work on testing for some small amount of time and that’s it,” Lee said. “Putting in the structures for people to be able to revisit and better understand the deployments further down the line is really crucial.” 

The California Department of Transportation is looking for tools that would analyze traffic data and come up with solutions to reduce highway traffic and make roads safer. The state’s Department of Tax and Fee Administration, which administers more than 40 programs, wants an AI tool to help its call center cut wait times and call length. The state is also seeking technologies to provide non-English speakers information about health and social services benefits in their languages and to streamline the inspection process for health care facilities. 

The tools are to be designed to assist state workers, not replace them, said Nick Maduros, director of the Department of Tax and Fee Administration. 

Call center workers there took more than 660,000 calls last year. The state envisions the AI technology listening along to those calls and pulling up specific tax code information associated with the problems callers describe. Workers  could decide whether to use the information.

Currently, call center workers have to simultaneously listen to the call and manually look up the code, Maduros said. 

“If it turns out it doesn’t serve the public better, then we’re out $1,” Maduros said. “And I think that’s a pretty good deal for the citizens of California.” 

Tong wouldn’t say when a successfully vetted tool would be deployed, but added that the state was moving as fast as it can. 

“The whole essence of using GenAI is it doesn’t take years,” Tong said. “GenAI doesn’t wait for you.”
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