CA Technologies, a global software firm, has made a gift of $300,000 to the University of Vermont to establish and fund doctoral fellowships in complex systems and data science. The fellowships will provide a competitive tuition and stipend package for up to two Ph.D. students per year for a minimum of three years.
The gift coincides with the launch, in fall 2018, of a new Ph.D. program in Complex Systems and Data Science at the university.
Thousands of jails and prisons across the United States use a company called Securus Technologies to provide and monitor calls to inmates. But the former sheriff of Mississippi County, Mo., used a lesser-known Securus service to track people’s cellphones, including those of other officers, without court orders, according to charges filed against him in state and federal court.
The service can find the whereabouts of almost any cellphone in the country within seconds. It does this by going through a system typically used by marketers and other companies to get location data from major cellphone carriers, including AT&T, Sprint, T-Mobile and Verizon, documents show.
Between 2014 and 2017, the sheriff, Cory Hutcheson, used the service at least 11 times, prosecutors said. His alleged targets included a judge and members of the State Highway Patrol. Mr. Hutcheson, who was dismissed last year in an unrelated matter, has pleaded not guilty in the surveillance cases.
As location tracking has become more accurate, and as more people carry their phones at every waking moment, the ability of law enforcement officers and companies like Securus to get that data has become an ever greater privacy concern.
Yale Fox’s business doesn’t work unless everyone thinks its fair. His startup, Rentlogic, relies on an algorithm to score New York City landlords on how well they take care of their properties. It’s an easy way for tenants to avoid bedbugs and mold, and for landlords to signal they take good care of their properties. But it isn’t enough for Rentlogic’s score to just exist; Fox needs landlords and tenants to believe in it.
This was on his mind last fall when he heard Cathy O’Neil speak. O’Neil, a former Wall Street quant with a Harvard PhD in mathematics, wrote a book in 2016 to sound the siren of algorithmic injustice. That book, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, argued that poorly rendered algorithms reinforce discrimination and widen inequality.
It’s a common argument, but most critics offer few solutions for fixing this bias. But O’Neil has come up with a novel idea: an auditing process that asks companies to open up their technology for evaluation. After the lecture, Fox asked to meet with her. By the end of their coffee, he’d signed on as her first client for an external algorithmic audit.
Google Cloud Chief Scientist Fei-Fei Li is one of the most popular and influential AI figures today. The woman behind the large-scale image dataset ImageNet is a visionary and an authority on AI’s development. And so it came as no surprise that Li’s panel session today at the Google Developer Conference I/O was packed to capacity.
Li was joined by Google Principal Scientist Greg Corrado and Google Cloud CEO Diane Greene on the “Building the future of artificial intelligence for everyone” panel. The trio shared their views on the future of AI from a scientist’s perspective.
Speaking on artificial general intelligence (AGI) — the long-range, human-intelligence-level target of contemporary AI technology — Li stressed that “humans have a tendency to overestimate the short-term promise while underestimating long-term promise.”
Li gave the example of her two-year-old daughter figuring out how to safely climb out of her crib, a task that state-of-the-art AI would have a tough time with. “Even a cat has things it can do that AI cannot,” said Li.
Bloomberg Government, Robert Levinson & Chris Cornillie
The Central Intelligence Agency is looking to team up with industry experts to run a series of open-source intelligence projects using its Amazon cloud.
The agency released a revised acquisition schedule on May 7 for a project known as Mesa Verde that will test the frontiers of big data and open-source intelligence. The project calls for using the CIA’s C2S cloud, built by Amazon Web Services LLC, to pore through thousands of terabytes of data, including data publicly available on the Web, and apply tools such as natural language processing, sentiment analysis, and data visualization to draw conclusions others might have missed.
Uber Technologies Inc. has responded to concerns about its safety processes by hiring the former head of the U.S. National Transportation Safety Board to advise it on safety after an internal investigation found that a software error caused the fatal crash involving one of their self-driving vehicles in March.
Christopher Hart was first acting chairman of the NTSB in August 2014 and then chairman between February 2015 and August 2017. He joins Uber at the same time The Information reported that Uber has found that a software fault, specifically how the software decides how the car should react to objects it detects, was to blame for the death of Arizona pedestrian Elaine Herzberg in March.
Initially it was believed that the pedestrian was at fault — particularly given that video footage (see below) showed the woman crossing a very dark stretch of road. But the investigation found that its autonomous vehicle software had been set in a way that caused it to ignore the pedestrian.
Sherlock Holmes famously solved a case by listening for the dog that didn’t bark. So it has been fascinating to listen to the utter silence from the D.C. police department as the Facebook privacy scandal has unfolded—especially as it’s unfolded around Palantir, a defense contractor cum cop spying agency founded by Peter Thiel, Donald Trump’s favorite Silicon Valley baron.
Palantir’s role in the Facebook scandal—scraping Facebook data for Cambridge Analytica—has raised all sorts of embarrassing questions for police chiefs around the country. Palantir has been aggressive at selling its wares to local cops and has won contracts in Los Angeles, New York, the suburbs of Chicago, and with the Virginia State Police and dozens of departments in Utah. Even before the latest Facebook scandal, Palantir was radioactive: The company was chased out of New Orleans in February when it emerged that the cops didn’t tell anybody in City Hall that Palantir was spying on their citizens.
D.C., then, has been a bit of mongrel among big-city police departments in that it hasn’t made use of Palantir’s snooping technology, which includes using cop cameras, social media profiles, and all sorts of advanced analytics to come up with “crime maps.” But it turns out that it’s not for lack of trying: Records obtained by City Paper show that D.C. officials did their level best to bring Palantir to town. It may be that the District’s long history of contracting incompetence and corruption saved it from the latest unpleasantness.
Survey results included in the report suggest that very few people in Los Angeles bear the brunt of most police interactions: 2 percent of residents who responded to the survey reported being stopped by police between 11 and 30 times a week or more, while 76 percent of respondents reported never being stopped at all. The 300 survey respondents were distributed across geography, race, age, and gender. In focus groups, people who lived in areas heavily targeted by police described a state of constant surveillance. Asking “how often do I see police in my area is like asking me how many times do I see a bird in the day,” said one resident.
What’s more, the LAPD has been using technology from the data-mining firm Palantir that may amplify that concentration, as part of a predictive policing program that targets and surveils specific individuals within select neighborhoods based off their recent history with the criminal justice system.
Officers and analysts who work on Operation LASER, or Los Angeles Strategic Extraction and Restoration, are tasked with maintaining an ongoing list of community residents to monitor, by creating “Chronic Offender Bulletins” for so-called persons of interest. Each of the 16 department divisions that currently use the program is required to maintain a minimum of a dozen of these “bulletins,” which are intended to help officers “identify the most active violent chronic offenders” in a given geographical area.
By now, New York City commuters are familiar with the wait. We descend from the bitter cold or the stifling heat to find subway platforms teeming with other bodies trying to make it to work on time. Delays ripple through the system, so there’s barely room to squeeze into the next train that arrives.
For years, the Metropolitan Transportation Authority told us that rising ridership and overcrowding were to blame. Yet ridership actually stayed mostly flat from 2013 to 2018 as delays rose, and the authority recently acknowledged that overcrowding was not at fault.
Instead, two decisions made by the M.T.A. years ago — one to slow down trains and another that tried to improve worker safety — appear to have pushed the subway system into its current crisis. And there’s no easy fix.
3.1. Four in ten Americans say they have personally experienced the effects of global warming.
Four in ten Americans (41%) say they have personally experienced the effects of global warming, while about six in ten (59%) say they have not.
The percentage of Americans who say they have personally experienced the effects of global warming decreased by three percentage points from its all-time high in October 2017, but has increased by 10 percentage points since our March 2015 survey.
arXiv, Statistics > Machine Learning; Miguel A. Hernán, John Hsu, Brian Healy
Causal inference from observational data is the goal of many health and social scientists. However, academic statistics has often frowned upon data analyses with a causal objective. The advent of data science provides a historical opportunity to redefine data analysis in such a way that it naturally accommodates causal inference from observational data. We argue that the scientific contributions of data science can be organized into three classes of tasks: description, prediction, and causal inference. An explicit classification of data science tasks is necessary to describe the role of subject-matter expert knowledge in data analysis. We discuss the implications of this classification for the use of data to guide decision making in the real world.
Recognizing that tropical cyclones are among the most destructive and costly natural hazards on Earth, and they always develop over the ocean, a new special issue of JGR: Oceans aimed to address the oceanic responses and feedbacks to tropical cyclones. Indeed, improving our understanding, simulation, and forecasts of tropical cyclones is both a scientific and societal imperative.
The special collection received more than 70 submissions from the international scientific community. Papers cover a broad range of topics including the physical mechanisms for ocean-tropical cyclone interactions, ocean-tropical cyclone interactions in the context of climate change, cutting edge techniques in data assimilation forecasting using coupled models, and other related interdisciplinary studies such as coastal environments, biochemical and geological processes.
Berkeley, CA July 16-19. “UC Berkeley’s Division of Data Sciences, in partnership with the National Science Foundation and the Microsoft Corporation will be holding a workshop on undergraduate data science pedagogy.” Application deadline is May 21.
“The GVG-AI Competition explores the problem of creating controllers for general video game playing. How would you create a single agent that is able to play any game it is given? Could you program an agent that is able to play a wide variety of games, without knowing which games are to be played? Can you create an automatic level generation that designs levels for any game is given?” Deadlines for submissions begin on June 8.
Montreal, Quebec, Canada August 28. “The Montreal AI Symposium aims at gathering experts and professionals interested in fundamental advances and applications of artificial intelligence, with an emphasis on machine learning, deep learning and related approaches.” Deadline for submissions is early-July.
HIMSS Innovator in Residence Adam Culbertson and Brent Hicks, senior director of clinical solutions at the Cleveland Clinic, discuss the opportunities and challenges to tying EHR data with new applications.