NYU Data Science newsletter – September 22, 2015

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More and more, scientists are seeing tech seep into their work. From data collection to team management, various tools exist to make your lives easier. But, where to start? Python is growing in popularity in scientific circles, due to its simple syntax and seemingly endless libraries. This free ebook gets you started on the path to a more streamlined process. With a collection of chapters from our top scientific books, you’ll learn about the various options that await you as you strengthen your computational thinking.

Keeping people from gaining access to your personal information online is a nearly impossible task in the modern world. What you can do however is ensure that the information which is out there is as well protected as possible. Doing this is a multi-step process for us, the members of the general public.

links to .html articles from the conference

You really want to avoid going back to school just to work on projects that will be your portfolio. You are busy. Interviewing is hard. Data Science is new and means different things to different people. And most of all, you’re worried that since you are learning skills on your own time at home, you may not be learning the right things. So when you construct your data science portfolio, it may be all wrong.

A few months ago, social psychologist Benjamin Crosier was building an app to look for links between social-media activity and ills like drug addiction.

Then, he was stopped in his tracks after Facebook Inc. limited outsiders’ access to information about its roughly 1.5 billion users. Dr. Crosier, a postdoctoral fellow at Dartmouth College, is petitioning the company to get some of that data back.

His experience highlights how Facebook’s restrictions on its user data, which were announced last year and put into effect in May, are rippling through academia, business and presidential politics.

The Allen Institute for Artificial Intelligence (AI2) today announced a significant breakthrough in AI research in the form of GeoS, a new AI system that is capable of solving SAT geometry problems as well as the average American 11th grade student through a combination of visual processing and textual analysis. The creation of GeoS was led by AI2, in collaboration with UW faculty and students with expertise in artificial intelligence, natural language processing and computer vision at the University of Washington. AI2 – established by investor, philanthropist, and technologist Paul G. Allen in 2004 to advance artificial intelligence research for the public good – is led by former UW CSE professor Oren Etzioni.

Steve Chambers and Cynthia Breazeal provide several exciting updates on the Jibo program and Jibo’s delivery. Our early adopter developers will gain access to the Jibo SDK this Fall, and we look forward to providing more progress reports on the official Jibo blog.

You can think of John Hegeman as Facebook’s chief economist. He spends his days thinking about the economics of Facebook advertising.

That’s an enormous thing. Facebook pulled in $4.04 billion in the second quarter of this year. And the overall economy of Facebook advertising, as Hegeman describes it, is far larger. Advertising, you see, is very much a part of everything else on the world’s largest social network. Hegeman doesn’t just think about ads. He thinks about how ads fit with the rest of Facebook.

“The automation of labour is inevitable,” says New York designer Lucien Ng. “Before the end of this century, 70% of today’s occupations will likely be replaced by automation.” With that sobering thought in mind, Ng created “Artificium”, a project that posits a world where it has already happened.

The short video presents as an advertisement for the artificial intelligence designer Artificium, promising to improve corporate profits by removing humans from the design process. “Because designers cost time and money,” the ad states, “The elimination of the designer…can bring good to the world.”

Text has long been an important, but difficult to use, source of data for social scientists. Back when I wrote my Ph.D. thesis, for example, I sat for weeks with abstracts from the New York Times — finding newspaper articles relating to past presidential campaigns, and content-analyzing those articles to determine whether they had substantive or “horse-race” information in them. Back in the day, most scholars analyzed text like this manually, and despite the fact that vast amounts of text were available for study, very little of that information became data that was amenable to sophisticated quantitative analysis.

How the world has changed! Because of vast improvements in computational capabilities (both in terms of data accessibility, storage, and analytic power), tools and methods for the automated analysis of text have proliferated. Some of the most innovative new tools and methods are being developed by social scientists, and in recent years we have seen many important papers on the analysis of text published in Political Analysis.

… Pope Francis, in fact, made news for endorsing both the big-bang theory and evolution. He said they don’t contradict the existence of a higher power.

“As a man of science I think he’s shown a great deal of respect for the role of science in society,” NYU physics professor Kyle Cranmer said.