A paper coauthored by over 112 researchers across 160 data and social science teams found that AI and statistical models, when used to predict six life outcomes for children, parents, and households, weren't very accurate even when trained on 13,000 data points from over 4,000 families. They assert that the work is a cautionary tale on the use of predictive modeling, especially in the criminal justice system and social support programs. "Here's a setting where we have hundreds of participants and a rich data set, and even the best AI results are still not accurate," said study co-lead author Matt Salganik, a professor of sociology at Princeton and interim director of the Center for Information Technology Policy at the Woodrow Wilson School of Public and International Affairs. "These results show us that machine learning isn't magic; there are clearly other factors at play when it comes to predicting the life course." The study, which was published this week in the journal Proceedings of the National Academy of Sciences, is the fruit of the Fragile Families Challenge, a multi-year collaboration that sought to recruit researchers to complete a predictive task by predicting the same outcomes using the same data.
Researchers at the University of California, San Francisco have recently created an AI system that can produce text by analyzing a person's brain activity, essentially translating their thoughts into text. The AI takes neural signals from a user and decodes them, and it can decipher up to 250 words in real-time based on a set of between 30 to 50 sentences. As reported by the Independent, the AI model was trained on neural signals collected from four women. The participants in the experiment had electrodes implanted in their brains to monitor for the occurrence of epileptic seizures. The participants were instructed to read sentences aloud, and their neural signals were fed to the AI model.
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Autonomous technology continues to make an impact on the supply chain. The autonomous supply chain, applies to moving goods without human intervention (to some degree at least) or aiding in achieving inventory accuracy. One of the more interesting examples is the Belgian brewery De Halve Maan, which in an effort to reduce congestion on the city streets, built a beer pipeline under the streets. The pipeline is capable of carrying 1,500 gallons of beer an hour at 12 mph to a bottling facility two miles away. Autonomous technology is seen in warehouses and stores, on highways and in mines, and in last mile deliveries.
Like many agencies, the Census Bureau looks for reductions in expenses and workloads when it makes decisions about machine learning. But the agency has discovered another advantage in the technology: It can find data that employees never knew they needed. More than 100 different surveys are handled by siloed programs within the Census Bureau, and the capture, instrumentation, processing and summation of the resulting data is "really hard to manage," said Zachary Whitman, chief data officer, at an AFCEA Bethesda event Wednesday, The bureau's dissemination branch exports data in a consolidated system where discovery and preparation is "difficult" for employees, Whitman said. So the agency is piloting ML that flags valuable information employees may not have even been searching for originally. "How do you get people to translate into information they might not know about but would be very valuable to them?" Whitman said.
IBM will make its Watson artificial intelligence software available for free, so government agencies, businesses, universities and healthcare institutions can use intelligent bots to answer citizens' queries about the unfolding COVID-19 crisis. The software will be available for free for at least 90 days, meaning organisations can use it to create chatbots to alleviate demand and waiting times on customer service phone numbers. IBM's Watson AI software will be free for organisations to create customer service bots, which can talk to people about their COVID-19 queries. The free service is already being used by organisations in the US and across Europe and the company said it could be added into existing mobile phone apps, or online apps such as the newly released Australian government's, to provide information and advice about the pandemic. In a statement IBM's general manager of data and AI Rob Thomas said it was putting years of experience in helping businesses use natural language processing, out into the market for use.
A few years ago, when researchers successfully demonstrated the use of augmented reality (AR) to treat PTSD by examining which parts of the brain it impacted, no one would have thought that scientists would be able to able to use artificial intelligence (AI) to turn brain activity to text. According to The Guardian, scientists at the University of California (UC) have been able to do so using electrode arrays implanted in the brain. Although the results are not too revolutionary, and AI commits mistakes more often than not, the fact that this is now possible is an achievement in itself. While, in the AR experiment, scientists were looking at which part of the brain gets impacted by certain images and videos to decode neural response, in the UC experiment, AI converted brain activity to numbers related to aspects of speech. The AI, with great difficulty, could only do this for the 50 sentences in which it was trained.
Chances are you've already encountered, more than a few times, truly frightening predictions about artificial intelligence and its implications for the future of humankind. The machines are coming and they want your job, at a minimum. Scary stories are easy to find in all the erudite places where the tech visionaries of Silicon Valley and Seattle, the cosmopolitan elite of New York City, and the policy wonks of Washington, DC, converge--TED talks, Davos, ideas festivals, Vanity Fair, the New Yorker, The New York Times, Hollywood films, South by Southwest, Burning Man. The brilliant innovator Elon Musk and the genius theoretical physicist Stephen Hawking have been two of the most quotable and influential purveyors of these AI predictions. AI poses "an existential threat" to civilization, Elon Musk warned a gathering of governors in Rhode Island one summer's day.
WASHINGTON: The National Geospatial-Intelligence Agency (NGA) will announce plans in May to contract with commercial companies to for analyze satellite and other imagery data of military targets, says David Gauthier, head of NGA's new(ish) Commercial and Business Operations Group. While the first contracts will be small, the move is a big step toward the spy agency's goal of creating a "hybrid" pool of data that combines commercial imagery with low-resolution but high re-revisit rates with traditional high-resolution that is less timely Intelligence Community imagery provided by the National Reconnaissance Office (NRO) and others. "We do foresee in the future a hybrid architecture, where we definitely require both national systems for their capabilities, and commercial systems for their capabilities," he said. While Gauthier wouldn't provide a budget for the new effort, he told me earlier this week that the plan is to evaluate the capabilities of a number of commercial companies to meet NGA's needs. "I don't want to discuss numbers at this time, but we are still operating at small scale and plan on contracting with multiple vendors to compare and contrast their capabilities," he said.
AI is transforming the practice of medicine. It's helping doctors diagnose patients more accurately, make predictions about patients' future health, and recommend better treatments. To help make this transformation possible worldwide, you need to gain practical experience applying machine learning to concrete problems in medicine. We've gathered experts in the AI and medicine field to share their career advice and what they're working on. We'll also be celebrating the launch of our new AI For Medicine Specialization!