A team of University of Illinois researchers estimated the mortality costs associated with air pollution in the U.S. by developing and applying a novel machine learning-based method to estimate the life-years lost and cost associated with air pollution exposure. Scholars from the Gies College of Business at Illinois studied the causal effects of acute fine particulate matter exposure on mortality, health care use and medical costs among older Americans through Medicare data and a unique way of measuring air pollution via changes in local wind direction. The researchers - Tatyana Deryugina, Nolan Miller, David Molitor and Julian Reif - calculated that the reduction in particulate matter experienced between 1999-2013 resulted in elderly mortality reductions worth $24 billion annually by the end of that period. Garth Heutel of Georgia State University and the National Bureau of Economic Research was a co-author of the paper. "Our goal with this paper was to quantify the costs of air pollution on mortality in a particularly vulnerable population: the elderly," said Deryugina, a professor of finance who studies the health effects and distributional impact of air pollution.
Under the new law, companies must explain how the technology works and how the tools evaluate a candidate. Employers must obtain consent from applicants before using A.I. to assess their videos. The legislation also prohibits businesses from sharing submitted videos except with "persons whose expertise or technology" are required to screen applicants. Job applicants can ask to have submitted videos destroyed, and companies, including any individual with copies, must comply within 30 days.
The most well-funded US artificial intelligence startup is Nuro, with just over $1B in disclosed equity funding, including a $940M Series B from SoftBank in February 2019. The California-based startup is developing autonomous vehicles, with a focus on last-mile delivery. Nuro is followed by New York's UiPath ($1B in disclosed equity funding) and Illinois' Avant ($655M). There are 9 unicorn startups on our map: robotic process automation vendor UiPath ($7.1B valuation), autonomous vehicles software provider Argo AI ($7B), agtech startup Indigo Agriculture ($3.5B), Nuro ($2.7B), alternative lending startup Avant ($1.9B), AI-powered predictive sales platform InsideSales.com The startup with the least funding on the list is Rhode Island's The Innovation Scout, a SaaS platform that connects enterprises with startups, accelerators, and more.
Data science consultant Cathy O'Neil helps companies audit their algorithms for a living. And when it comes to how algorithms and artificial intelligence can enable bias in the job hiring process, she said the biggest issue isn't even with the employers themselves. A new Illinois law that aims to help job seekers understand how AI tools are used to evaluate them in video interviews recently resurfaced the debate over AI's role in recruiting. But O'Neil believes the law tries to tackle bias too late in the process. "The problem actually lies before the application comes in. The problem lies in the pipeline to match job seekers with jobs," said O'Neil, founder and CEO of O'Neil Risk Consulting & Algorithmic Auditing.
Citadel is a global investment firm built around world-class talent, sound risk management, and innovative leading-edge technology. For a quarter of a century, Citadel's hedge funds have delivered meaningful and measurable results to top-tier investors around the world, including sovereign wealth funds, public institutions, corporate pensions, endowments and foundations. With an unparalleled ability to identify and execute on great ideas, Citadel's team of more than 675 investment professionals, operating from offices including Chicago, New York, San Francisco, London, Hong Kong and Shanghai, deploy capital across all major asset classes, in all major financial markets.
Artificial intelligence can diagnose breast cancer more accurately than trained doctors, a study suggests. The research on almost 30,000 women who underwent screening found a computer programme could reduce the number of cases missed by more than two thirds. Researchers said the algorithmdeveloped by Imperial College London, Northwestern University in Chicago and Google Health was a "huge advance" in early detection of cancers. Breast cancer is the most common type of cancer in the UK, affecting around one in eight women - with 55,000 diagnoses annually and 11,000 deaths. Experts said the breakthrough could save thousands of lives, by finding deadly tumours that would otherwise go undetected.
In this paper, we introduce STREETS, a novel traffic flow dataset from publicly available web cameras in the suburbs of Chicago, IL. We seek to address the limitations of existing datasets in this area. Many such datasets lack a coherent traffic network graph to describe the relationship between sensors. The datasets that do provide a graph depict traffic flow in urban population centers or highway systems and use costly sensors like induction loops. These contexts differ from that of a suburban traffic body.
Position: Data Scientist Location: Chicago, IL/ SFO, CA Long term contract Client is looking for an advanced data science thinker, team leader, doer and expert who loves to dive into new and different problems, push the boundaries of innovation, and rapidly design, build and help implement machine learning and knowledge discovery solutions. Ideal candidate enjoys learning new contexts and areas of applications to help clients across industries and functions build ROI positive solutions. Creative thinking, problem solving and on-your-feet dot-connecting is very important. All your information will be kept confidential according to EEO guidelines.
PlaceIQ is a powerful, location-based audience and insights platform that organizes a wide variety of consumer activity data around a precise location base map at massive scale. PlaceIQ uses its detailed understanding of location and consumer activity to reach a targeted audience, and also to derive powerful insights about consumer behavior to inform market and business strategies for national brands. The company is headquartered in New York City and has offices in Palo Alto, Chicago, and Detroit. Data Scientists analyze PlaceIQ hyperlocal data sources to develop accurate predictions of audience and behavior. A mixture of analytical approaches are employed including raw data mining, data visualization, application of rules and heuristics and supervised / unsupervised machine learning techniques.
CHICAGO--An artificial intelligence machine-learning program has demonstrated the ability to accurately forecast which head and neck cancer patients are likely to experience severe weight loss, necessitating the use of a feeding tube, researchers at MD Anderson Cancer Center in Houston told attendees at the 2019 ASTRO Annual Meeting (Abstract 141). It marks the first time that such a sophisticated "self-teaching" computer algorithm has accurately identified patients likely to develop problems eating, said Jay Reddy, MD, PhD, Assistant Professor of Radiation Oncology and lead author of the study. "With head and neck radiation, a lot of toxicity occurs; however it's not always clear which patients will experience serious side effects," he told a press conference. Reddy and his colleagues used machine learning models to analyze large datasets from three sources--electronic health records, an internal web-based patient charting tool, and the hospital's records and verification system--in an effort to discern and eventually predict patients with weight loss exceeding 10 percent of total body weight, the need for a feeding tube, and/or any unplanned hospitalization within 3 months of radiation. Machine learning is a relatively powerful application of artificial intelligence (AI)–think facial recognition software--by which a computer program can automatically learn and improve itself by analyzing large quantities of data.