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COLOGNE, Germany NATO officials are kicking around a new set of questions for member states on artificial intelligence in defense applications, as the alliance seeks common ground ahead of a strategy document planned for this summer.

The move comes amid a grand effort to sharpen NATOs edge in what officials call emerging and disruptive technologies, or EDT. Autonomous and artificial intelligence-enabled weaponry is a key element in that push, aimed at ensuring tech leadership on a global scale.

Exactly where the alliance falls on the spectrum between permitting AI-powered defense technology in some applications and disavowing it in others is expected to be a hotly debated topic in the run-up to the June 14 NATO summit.

We have agreed that we need principles of responsible use, but were also in the process of delineating specific technologies, David van Weel, the alliances assistant secretary-general for emerging security challenges, said at a web event earlier this month organized by the Estonian Defence Ministry.

Different rules could apply to different systems depending on their intended use and the level of autonomy involved, he said. For example, an algorithm sifting through data as part of a back-office operation at NATO headquarters in Brussels would be subjected to a different level of scrutiny than an autonomous weapon.

In addition, rules are in the works for industry to understand the requirements involved in making systems adhere to a future NATO policy on artificial intelligence. The idea is to present a menu of quantifiable principles for companies to determine what their products can live up to, van Weel said.

For now, alliance officials are teeing up questions to guide the upcoming discussion, he added.

Those range from basic introspections about whether AI-enabled systems fall under NATOs legal mandates, van Weel explained, to whether a given system is free of bias, meaning if its decision-making tilts in a particular direction.

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Accountability and transparency are two more buzzwords expected to loom large in the debate. Accidents with autonomous vehicles, for example, will the raise the question of who is responsible manufacturers or operators.

The level of visibility into of how systems make decisions also will be crucial, according to van Weel. Can you explain to me as an operator what your autonomous vehicle does, and why it does certain things? And if it does things that we didnt expect, can we then turn it off? he asked.

NATOs effort to hammer out common ground on artificial intelligence follows a push by the European Union to do the same, albeit without considering military applications. In addition, the United Nations has long been a forum for discussing the implications of weaponizing AI.

Some of those organizations have essentially reinvented the wheel every time, according to Frank Sauer, a researcher at the Bundeswehr University in Munich.

Regulators tend to focus too much on slicing and dicing through various definitions of autonomy and pairing them with potential use cases, he said.

You have to think about this in a technology-agnostic way, Sauer argued, suggesting that officials place greater emphasis on the precise mechanics of human control. Lets just assume the machine can do everything it wants what role are humans supposed to play?

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NATO tees up negotiations on artificial intelligence in weapons - C4ISRNet

As artificial intelligence (AI) and machine learning tools become more widely adopted in various products and industries, the NRC has begun studying what roles these technologies can play in commercial nuclear power operations. On April 21, as part of its study, the NRCs Office of Nuclear Regulatory Research requested public comments on the role of these technologies in the various phases of nuclear power generation operational experience and plant management. The NRC requests feedback on the state of practice, benefits, and future trends related to [these technologies] computational tools and techniques in predictive reliability and predictive safety assessments in the commercial nuclear power industry. These technologies are emerging, analytical tools, which, if used properly, show promise in their ability to improve reactor safety, yet offer economic savings. Comments are due by May 21, 2021.

The NRC intends to use the comments to enhance its understanding of the benefits of AI and machine learning as well as the potential pitfalls and challenges associated with their application.

The NRC has requested comments on the following questions:

The NRC is in the early stages of its review, and the agency does not promise to use the information collected in any formal regulatory action. Morgan Lewis will continue to follow the NRCs regulatory initiatives.

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NRC Exploring Potential Role of Artificial Intelligence in Commercial Nuclear Power Operations - JD Supra

"We are thrilled to have Andrey's leadership and experience and believe he will be instrumental in continuing to expand the use of systems and technology within the company," said Ajai Nair, CIO. "His extensive background in application development and business robotic automation software brings a wealth of knowledge to the team that is necessary to accelerate a successful digital transformation, allowing us to faster determine measurable business benefits and better serve our customers."

Andrey joins the JG Wentworth team from UiPath where he served as Director on their Competitive and Market Intelligence team. During his tenure at UiPath he utilized data mining techniques to analyze the marketplaces, enable sales and predict cashflows.

"I am excited to join a market leader focused on helping customers improve their financial health. I look forward to this unique opportunity to be part of the evolution of JG Wentworth by leveraging AI and automation to positively impact our customers' lives," said Andrey.

Andrey earned his Bachelor of Science in both Information & Systems Engineering and Analytical Finance from the Lehigh University and holds a Master of Science from The George Washington University and a Master of Business Administration from New York University, Leonard N. Stern School of Business.

About JG WentworthJG Wentworth is a financial services company that focuses on helping customers who are experiencing financial hardship or need to quickly access cash. Its services include debt relief, structured settlement payment purchasing, annuity payment purchasing, lottery and casino payment purchasing. J.G. Wentworth was founded in 1991 and currently has offices in Chesterbrook, Pennsylvania, Radnor, Pennsylvania and Rockville, Maryland. For more information about J.G. Wentworth visit http://www.jgwentworth.com or use the information provided below.

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JG Wentworth Welcomes Andrey Zelenovsky as their Vice President of Artificial Intelligence and Machine Learning - PRNewswire

SAN FRANCISCO, April 26, 2021 /PRNewswire/ --Lilt, the modern language service and technology provider, today announced that it has been named to the 2021 Forbes AI 50 for the third consecutive year. The Forbes AI 50 recognizes the most promising privately-held companies using artificial intelligence to build business applications and services to transform industries. Lilt is one of only seven companies that have been included every year since the list's inception in 2019.

"Our artificial intelligence and machine learning technologies enable our customers to provide exceptional global experiences to their customers around the world," said Lilt CEO Spence Green. "We're proud to be recognized by Forbes for the third year in a row alongside other leading companies developing AI-powered solutions."

Lilt's translation services are powered by the Lilt Platform, the world's most advanced translation technology that uses AI and automation to make every step of the localization process faster, more accurate, and simpler. Lilt's community of over 60,000 skilled human translators uses its AI-powered translation technology to translate content quickly, efficiently, and at higher quality than ever before. With Lilt, companies go-to-market faster, grow global revenues, and provide a personalized global experience to their customers in their language of choice.

Forbes partnered with Sequoia Capital and Meritech Capital to evaluate hundreds of promising, privately-held North American companies that are using AI in ways that are fundamental to their operations. The list, which nearly 400 companies qualified for, focused on companies utilizing machine learning, natural language processing, or computer vision technologies. Of the qualifying companies, 100 were selected based on their qualitative score created by Forbes' data partners, followed by evaluation by a panel of expert AI judges to narrow the list down to 50.

Along with the Forbes AI 50 list, Lilt was recently named to the CB Insights AI 100 list, showcasing the 100 most promising private artificial intelligence companies in the world, and was included in Gartner's recent Market Guide for AI-Enabled Translation Services.

About LiltHeadquartered in San Francisco, Lilt is the modern language service and technology provider enabling localized customer experiences. Lilt's mission is to make the world's information accessible to everyone regardless of where they were born or which language they speak. Lilt brings human-powered, technology-assisted translations to global enterprises, empowering product, marketing, support, e-commerce, and localization teams to deliver exceptional customer experiences to global audiences. Lilt gives industry-leading organizations like Intel, ASICS, WalkMe, DigitalOcean, and Canva everything they need to scale their localization programs and go-to-market faster. Lilt has additional global offices in Dublin, Berlin, Washington, D.C. and Indianapolis. Visit us online at http://www.lilt.com or contact us at [emailprotected].

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Forbes Recognizes Lilt As One of the Top Artificial Intelligence Companies For Third Straight Year - PRNewswire

Students newly accepted by colleges and universities this spring are being deluged by emails and texts in the hope that they will put down their deposits and enroll. If they have questions about deadlines, financial aid and even where to eat on campus, they can get instant answers.

The messages are friendly and informative. But many of them arent from humans.

Artificial intelligence, or AI, is being used to shoot off these seemingly personal appeals and deliver pre-written information through chatbots and text personas meant to mimic human banter. It can help a university or college by boosting early deposit rates while cutting down on expensive and time-consuming calls to stretched admissions staffs.

AI has long been quietly embedding itself into higher education in ways like these, often to save money a need thats been heightened by pandemic-related budget squeezes.

Now, simple AI-driven tools like these chatbots, plagiarism-detecting software and apps to check spelling and grammar are being joined by new, more powerful and controversial applications that answer academic questions, grade assignments, recommend classes and even teach.

The newest can evaluate and score applicants personality traits and perceived motivation, and colleges increasing are using these tools to make admissions and financial aid decisions.

As the presence of this technology on campus grows, so do concerns about it. In at least one case, a seemingly promising use of AI in admissions decisions was halted because, by using algorithms to score applicants based on historical precedence, it perpetuated bias.

Much of the AI-powered software used by colleges and universities remains confined to fairly mundane tasks such as improving back-office workflow, said Eric Wang, senior director of AI at Turnitin, a service many institutions use to check for plagiarism.

Where you start seeing things that get a bit more worrying, he said, is when AI gets into higher-stakes types of decisions.

Among those are predicting how well students might do if admitted and assessing their financial need.

Hundreds of colleges subscribe to private platforms that do intensive data analysis about past classes and use it to score applicants for admission on factors such as the likelihood they will enroll, the amount of financial aid theyll need, the probability theyll graduate and how likely they are to be engaged alumni.

Some universities use AI to rate applicants potential for success based on how they interact with a schools website and respond to its messages, which the provider of the service says is 20 times more predictive than relying on demographics alone.

Humans always make the final calls, these colleges and the AI companies say, but AI can help them narrow the field.

Baylor, Boston and Wake Forest universities are among those that have used the Canadian company Kira Talent, which offers a review system that can score an applicants personality traits and soft skills based on a recorded, AI-reviewed video the student submits. A company presentation shows students being scored on a five-point scale in areas such as openness, motivation, agreeableness and neuroticism.

Related: Subscribing to college and other visions of higher educations future

New York University, Southeast Missouri State University and other schools have used a service called Element451, which rates prospects potential for success based on how they interact with a schools website and respond to its messages.

The result is 20 times more predictive than relying on demographics alone, the company says.

Once admitted, many students now get messages from companies like AdmitHub, which advertises a customizable chatbot and text message platform that the company calls conversational AI to nudge accepted applicants into putting down deposits. The company says its reached more than 3 million students this way on behalf of hundreds of university and college clients.

Georgia State University, which pioneered the use of these chatbots, says its version, named Pounce, has delivered hundreds of thousands of answers to questions from potential students since it launched in 2016 and reduced summer melt the incidence of students enrolling in the spring but failing to show up in the fall by 20 percent.

Georgia State was also among the first to develop inexpensive, always-on AI teaching assistants, ready to answer student questions about course material. Theirs is called Jill Watson, and studies found that some students couldnt tell they were engaging with AI and not a human teaching assistant.

AI grading does it better, more quickly and probably making fewer errors than humans.

Staffordshire University in England offers students a digital friend, an AI teaching assistant named Beacon that can recommend reading resources and connect students with tutors. Australias Deakin University has an AI assistant named Genie that knows whether a student asking a question has engaged with specific online course materials and can check students locations and activities to determine if theyve visited the library or tell them when theyve spent too long in the dining hall and prompt them to move along.

Related: PROOF POINTS New wave of research shows nudging students by text is not as promising as hoped

Many colleges increasingly use AI to grade students, as online classes grow too large for instructors to manage this well.

The pandemic has hastened the shift to those kinds of classes. Even before that, however, Southern New Hampshire University with 97 percent of its nearly 150,000 students exclusively online was working on ways that AI could be used to grade large numbers of students quickly, said Faby Gagne, executive director of its research and development arm.

SNHU is also starting to AI not just to grade students but to teach them. Gagne has been experimenting with having AI monitor such things as speech or movement or the speed with which a student responds to video lessons and use that information to score achievement.

Turnitin, best known for checking for plagiarism, also sells AI language comprehension products to assess subjective written work. One tool can sort written assignments into batches, allowing a teacher to correct a mistake or give guidance just once instead of highlighting, commenting on and grading the same mistake again and again. The company says instructors check to verify that the machine made the correct assessment, and that eliminating repetitive work gives them more time to teach.

AI tools are also being sold to colleges to make decisions once made by faculty. ElevateU, for example, uses AI to analyze student data and deliver individualized learning content to students based on how they answered questions. If the program determines that a particular student will do better with a video lesson as opposed to a written one, thats what he or she gets.

Where you start seeing things that get a bit more worrying is when AI gets into higher-stakes types of decisions.

But some research suggests that AI tools can be wrong, or even gamed. A team at MIT used a computer to create an essentially meaningless essay that nonetheless included all the prompts an AI essay reader searches for. The AI gave the gibberish a high score.

In Spain, an AI bot named Lola answered more than 38,700 student questions with a 91.7 percent accuracy rate meaning it gave out at least 3,200 wrong or incomplete answers.

AI alone is not a good judge of human behavior or intention, said Jarrod Morgan, the founder and chief strategy officer at ProctorU, which schools hire to manage and observe the tests students take online. We found that people are better at this than machines are, pretty much across the board.

Related: Coronavirus accelerates higher educations trend toward distance learning

The University of St. Thomas in Minnesota said it tested, but did not deploy, an AI system that can scan and analyze students facial expressions to determine whether theyre engaged or understand the material. The system would immediately tell professors or others which students were becoming bored or which points in a lecture required repeating or punching up.

And researchers at the University of California, Santa Barbara, studied whether students got more emotional reinforcement from animated than from real-life instructors and found that, while students recognized emotion in both human and animated teachers, they had stronger, more accurate perceptions of emotions such as happy and frustrated when the instructors were human.

Many people think AI is smarter than people, said Wang, of Turnitin. But the AI is us. Its a mirror that reflects us to us, and sometimes in very exaggerated ways. Those ways, Wang said, underscore that the data AI often uses is a record of what people have done in the past. Thats an issue because we are more prone to accept recommendations that reinforce who we are.

AI alone is not a good judge of human behavior or intention. We found that people are better at this than machines are, pretty much across the board.

Thats what happened with GRADE, the GRaduate ADmissions Evaluator, an AI evaluation system built and used by the graduate program in computer science at the University of Texas at Austin. GRADE reviewed applications and assigned scores based on the likelihood of admission by a review committee. The goal was to reduce human time spent reviewing the increasing pile of applications, which GRADE did, cutting review time by 74 percent.

But the university dropped GRADE last year, agreeing that it had the potential to replicate superficial biases in the scoring scoring up some applications not because they were good, but because they looked like the kinds of applications that had been approved in the past.

These types of reinforcing bias that can surface in AI can be tested initially and frequently, said Kirsten Martin, a professor of technology ethics at the University of Notre Dame. But universities would be makinga mistake if they thought that automating decisions somehow relieved them of theirethical and legal obligations.

This story about artificial intelligence in higher education was produced byThe Hechinger Report, a nonprofit, independent news organization focused oninequality and innovation in education. Sign upforourhigher education newsletter.

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Artificial intelligence is infiltrating higher ed, from admissions to grading - The Hechinger Report