NYU Data Science newsletter – September 16, 2015

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As guards were going so far as to check inside NFL fans’ wallets as part of routine security measures before a recent preseason game at Levi’s Stadium, a different form of surveillance was taking place on the inside of the San Francisco 49ers’ 1-year-old, $1.3 billion home here in Silicon Valley.

We’re not talking about facial recognition devices, police body cams, or other security measures likely zeroing in on fans. Instead, employees from San Jose-based Zebra Technologies had recently finished scanning the NFL uniforms of the 49ers and of their opponents—the Dallas Cowboys. All of a sudden, an on-the-field de facto surveillance society was instantly created when Zebra techies activated nickel-sized Radio Frequency Identification Device (RFID) chips that were fastened inside players’ shoulder pads. Every movement of every player now could be monitored within an accuracy level of all but a few inches.

Integrating vision and language has long been a dream in work on artificial intelligence (AI). In the past two years, we have witnessed an explosion of work that brings together vision and language from images to videos and beyond. The available corpora have played a crucial role in advancing this area of research. In this paper we propose a set of quality metrics for evaluating and analyzing the vision-&-language datasets and classify them accordingly. Our analyses show that the most recent datasets have been using more complex language.

How is your data being used? Who is it being shared with? Data privacy is a major ethical issue facing data scientists. Access to and analysis of data can be a great benefit—personalized treatment is a remarkable convenience (like Netflix recommendations) and potential societal benefit (such as analyzing health records to develop cutting-edge medical techniques)—but it also carries a heavy responsibility. Most people might not be terribly worried if their Netflix history were made public (save for a bit of shame over a binge-watching habit), but they would take great issue if their medical or GPS records along with personally identifying information were released.

This issue came to a head in August when a group of hackers released a 9.7 gigabyte data dump of illegally-obtained private data from the website Ashley Madison.

In a world first, an artificial intelligence machine plays chess by evaluating the board rather than using brute force to work out every possible move.

Eric Horvitz, director of Microsoft’s research lab in Seattle, tells Simon Jack the robots of the future will remind us what it means to be human, rather than threaten humanity itself.

Federal drug regulators are exploring ways to search Facebook and Twitter messages for information about drug side effects but acknowledge that the data may have limited uses.

Regulators want to examine public social media sites for messages about drugs and medical devices, Henry Francis, director of data mining at the FDA’s Center for Drug Evaluation, said recently. The agency hopes the information gleaned from social media sites will improve its surveillance of approved drugs, he said.

… It’s pretty much a no-brainer that the military is also taking advantage of big data, but exactly what data is it using, and how? It turns out the military is using pretty much any kind of big dataset you can imagine, for everything from the most basic daily tasks to the most complicated long-term planning.

“Large data sets have already existed for a long time, it’s just that they have gotten larger and we have the computing power and technology to process it now,” said Vicki Barbur, chief technical officer at Concurrent Technologies Corporation, a nonprofit applied research and development organization that helps clients (including the military) find the right data analysis tools. She said big data in defense planning starts with very basic information.

“The kind of info we all have access to on a day to day basis is information defense groups would be interested in: GPS, climate, environment, traffic, vegetation growth,” Barbur told me in a phone interview.

The evolution of infrastructure networks such as roads and streets are of utmost importance to understand the evolution of urban systems. However, datasets describing these spatial objects are rare and sparse. The database presented here represents the road network at the french national level described in the historical map of Cassini in the 18th century. The digitization of this historical map is based on a collaborative methodology that we describe in detail. This dataset can be used for a variety of interdisciplinary studies, covering multiple spatial resolutions and ranging from history, geography, urban economics to network science.

The ideology of American lawyers has been a persistent source of discussion and debate. Two obstacles, however, have prevented this topic from being systematically studied: the sheer number of attorneys in the United States and the need for a methodology that makes comparing the ideology of specific individuals possible. In this paper, we present a comprehensive mapping of lawyers’ ideologies that has overcome these hurdles. We use a new dataset that links the largest database of political ideology with the largest database of lawyers’ identities to complete the most extensive analysis of the political ideology of American lawyers ever conducted.

Peer review is often claimed to be the guarantor of the trustworthiness of scientific papers, but it is a troubled process. Preprints offer a way out.

The University of Chicago announced Sept. 14 that the National Science Foundation has awarded a $3.1 million grant to support the development of Array of Things, an urban sensing instrument that will serve as a fitness tracker for the city. Starting next year, 500 Array of Things nodes will measure data on Chicago’s environment, infrastructure and activity to scientifically investigate solutions to urban challenges ranging from air quality to urban flooding. The ultimate goal of this innovative community technology platform is to help make cities cleaner, healthier and more livable.

… Enrollment is surging, and schools have too few resources to meet demand. Dealing with the enrollment surge was a big topic at the ACM Education Council last month. Based on what I heard at last year’s meeting of the Ed Council, I predicted that the enrollment surge would like lead to less diversity in CS (see blog post here). This year, I came away with the sense that most attendees believe it’s quite likely. The issue now is measuring the impact and seeing what resources can be marshaled once there’s evidence that there has been damage to diversity.

There’s no doubt that smartphones make our lives easier. As smartphone technology becomes more sophisticated with each passing year, however, it’s worthwhile to ask: are these helping devices truly serving the needs of every person who requires assistance in their daily lives? Could mobile technology be reaching more people who truly need it? Aipoly is a smartphone app that acts as an intelligent assistant to the non-sighted user

Students at Singularity University—a Silicon Valley-based benefit corporation, educational program, and startup accelerator that researches emerging technology to develop unique solutions to the challenges that modern communities face—asked the above questions, and their answer could change the way that the 285 million visually impaired people worldwide experience their lives.

Data Services tutorials are typically 1-2 hour sessions that focus on the essential components of our supported software packages. To see the full list of Library classes please visit the Library’s classes page. If you are an instructor and would like to request a tutorial for your class, you may do so via this form.

A calendar of Data Services and HPC scheduled tutorials and clinics can be found at the link. The calendar is updated on a monthly basis.