For African American boys, the presumption of guilt starts before they have entered a kindergarten classroom, new research shows. In a study presented Wednesday to a meeting of education policy officials, researchers found that pre-K educators who were prompted to expect trouble in a classroom trained their gaze significantly longer on black students, especially boys, than they did on white students. When asked which of four videotaped children -- a boy and girl who were black and a pair who were white -- required their closest attention, educators black and white alike chose the study's African American boy most frequently. The study's white boy came in a distant second and two girls -- one white and one black -- drew the least scrutiny from the teachers. But when subjects in the new study were asked to rate the severity of a child's disruptive behavior and recommend consequences for it, race played a more unexpected role: African American pre-K educators, the study found, judged misbehavior attributed to a black child more harshly than did white educators.

I am a Post-Doctoral Associate in the Computer Science Department at Courant Institute of Mathematical Sciences, New York University. I am working in the Laboratory of prof. Since January 2017 I will be an Assistant Professor in the Department of Electrical and Computer Engineering at NYU Tandon School of Engineering. I received my PhD from the Department of Electical Engineering at Columbia University in the City of New York, where I was also the Fu Foundation School of Engineering and Applied Science Presidential Fellowship holder (in years 2009-2012). I was co-advised by prof.

ARE your hidden biases soon to be revealed? A computer program can unmask them by scrutinising people's body language for signs of prejudice. Algorithms can already accurately read people's emotions from their facial expressions or speech patterns. So a team of researchers in Italy wondered if they could be used to uncover people's hidden racial biases. First, they asked 32 white college students to fill out two questionnaires. One was designed to suss out their explicit biases, while the second, an Implicit Association Test, aimed to uncover their subconscious racial biases.

Ashok Goel is a professor in the School of Interactive Computing. Soon scientists and the public will have the chance to easily test hypotheses about America's ecological challenges with the help of an ensemble of technologies, including artificial intelligence. Researchers at Georgia Institute of Technology will link their technology for systems thinking with IBM Watson and the Encyclopedia of Life at the Smithsonian. Scientists will then be able to use the information to create their own models about the environment and efficiently test them. The project is one of 10 "Big Data Spokes" announced by the National Science Foundation (NSF).

Artificial intelligence for education is a fast growing market the coming years a new report from Technavio shows. Two areas where AI will have a considerable impact is with its adaptive sequencing capabilities as well as its ability to transform pedagogical models. The first means artificial intelligence that is embedded in content that help students learn in a self-directed manner, which improves the learning-process. Both students and teachers will have access to all the data captured, where the artificial intelligence-backed learner solutions personalizing learning pathways. The secondly, transforming and improving traditional pedagogical models, that with AI basically develops online models.

Are the NYU Deep Learning course taken down? I want to re-watch some of the videos, but it seems like they taken down.

I have read a book or some posts on machine learning. I have watched some of the Coursera machine learning course. I still don't know how to get started… How do you get started in machine learning? The most common question I'm asked by developers on my newsletter is: I honestly cannot remember how many times I have answered it. In this post, I lay out all of my very best thinking on this topic. You are a developer and you're interested in getting into machine learning. You read some blog posts. You tried to go deeper but the books are dreadful.

Glancing around school classrooms in 2016, it's easy to miss just how far technology has transformed learning over the last decade. The desks, whiteboards and rows of chairs are the same, but so much else has changed that can't be seen. A third of Britain's schools are asking students to bring their own tablets and laptops into the classroom now, coding has been on the national curriculum for three years, and more and more education is happening outside school through apps and digital services. But these changes are just the start. Artificial intelligence (AI) is the next giant leap in learning and, according to those working in the field of education and technology, we haven't seen anything yet.

IBM's famous supercomputer has accomplished many, many things these past years, from making movie trailers to saving a person's life. Now, it's also helping teachers make lesson plans by powering Teacher Advisor, a program IBM developed with the American Federation of Teachers. If you're thinking "How hard could a grade school lesson plan be?" Well, have you seen Common Core mathematics? It's not the same math from back in the day, and teachers who didn't grow up with it might have a tough time conjuring up a way to make it more understandable.

Did you have a good, relaxing break over the summer? Are you refreshed and re-energised, looking forward to a new start, a new you and brushing up on your data analysis skills? If so, I've thrown together a collection of a few excellent (and free!) statistics eBooks for your Kindle to sharpen up your stats while you're on the long commute to work. Just try not to read them while driving! These books require different levels of existing knowledge, and while some are for early-stage data scientists others are for more hard-core physicists and mathematicians.