Open up the photo app on your phone and search "dog," and all the pictures you have of dogs will come up. This was no easy feat. Your phone knows what a dog "looks" like. This and other modern-day marvels are the result of machine learning. These are programs that comb through millions of pieces of data and start making correlations and predictions about the world. The appeal of these programs is immense: These machines can use cold, hard data to make decisions that are sometimes more accurate than a human's.

There is a stretch of highway through the Ozark Mountains where being data-driven is a hazard. Jason Tashea (@justicecodes), a writer and technologist based in Baltimore, is the founder of Justice Codes, a criminal justice and technology consultancy. Heading from Springfield, Missouri, to Clarksville, Arkansas, navigation apps recommend the Arkansas 43. While this can be the fastest route, the GPS's algorithm does not concern itself with factors important to truckers carrying a heavy load, such as the 43's 1,300-foot elevation drop over four miles with two sharp turns. The road once hosted few 18-wheelers, but the last two and half years have seen a noticeable increase in truck traffic--and wrecks.

He enrolled in the NYC Data Science Academy 17-week remote bootcamp program, taking place from January to April 2017. This post is based on his third class project focusing on web scraping in Python. The original article can be found here. Clean technology continues to undergo significant advancements spanning technology, sustainability, financial, and policy issues. Given the field's large scope, there is no shortage of news outlets covering the action.

AI is buzzing in the legal industry. It's time to separate hype from reality. I was recently invited to speak on artificial intelligence in law at the annual LMA conference along with an outstanding panel of industry experts (read my summary here). During my talk I offered a simplified view of the AI landscape of vendors and technologies in play and received great feedback and many requests for further detail. This feedback is consistent with many conversations I've had regarding legal AI over the past few years: it's hard to distinguish fact from reality, and practical examples of AI in this industry are hard to come by.

We live in a world that's increasingly being shaped by complex algorithms and interactive artificial intelligence assistants who help us plot out our days and get from point A to point B. According to a new Princeton study, though, the engineers responsible for teaching these AI programs things about humans are also teaching them how to be racist, sexist assholes. The study, published in today's edition of Science magazine by Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan, focuses on machine learning, the process by which AI programs begin to think by making associations based on patterns observed in mass quantities of data. In a completely neutral vacuum, this would mean that AI would learn to provide responses based solely on objective, data-driven facts. But because the data sets fed to the AI are selected and influenced by humans, there's a degree to which certain biases become a part of the AI's diet. To demonstrate this, Caliskan and her team created a modified version of an Implicit Association Test, an exercise that tasks participants to quickly associate concrete ideas like people of color and women with abstract concepts like goodness and evil.

One thing that's certain in our increasingly automated future is that artificial intelligence will play a increasingly central role in our lives. But while we think of these machines as robotic and logical, they can actually acquire cultural biases around race and gender. Researchers from the University of Washington found that a machine learning tool called "word embedding" can absorb biases hidden in language patterns. This tool helps computers make sense of language, and is used in web search and language translation, using a statistical approach to build up a mathematical representation of language and the meaning of words. The study, published in the journal Science, involved the machine pairing word concepts together.

In late February, the UN-Secretary General held a press conference, highlighting the risk of starvation in East Africa and the necessity to raise funds to address the emergency situations in Somalia and South Sudan. Drought has been back in these countries and their neighbours since 2016, leading to a huge current food crisis. While governments are trying to handle the situation, how could technology innovations help prevent starvation and improve agriculture management in the future? We met with Laurent Rivière, a French 30 years-old entrepreneur, who shared with us his view on the subject with a combination of engineer pragmatism and changemaker idealism . Founder and CEO at Sunbirds for two years, he explained to us how his "bird of the sun," his solar drone, is addressing the agriculture challenges of the 21st century.

Maajid Nawaz highlights the scary reality of artificial intelligence - also known as AI - today. Maajid Nawaz highlights the scary reality of artificial intelligence - also known as AI - today. Standing in for James O'Brien, Maajid Nawaz tackled the subject of artificial intelligence after a new study found that the technology is becoming racist and sexist. Here Maajid Nawaz highlights just some of the prejudices AI has already picked up - and it's not pretty. Maajid said: "An algorithm declared that 18 of the 23 most captivating women in the world were white. "We're going to carry on.

A state economic development board on Thursday approved an $8 million tax credit for General Motors as the company looks to expand its autonomous vehicle division with more than 1,100 hires in California. The GM tax credit was among more than $91 million in California Competes incentives for 114 companies approved at a board meeting in Sacramento of Gov. Jerry Brown's GO-Biz agency. The credits range from GM's $8 million to $20,000 for MinowCPA Corp., an accounting firm that plans to hire eight people in Newport Beach and Santa Ana. GM promises to hire 1,163 workers at an average salary of $116,000. San Francisco is the hub for GM's autonomous vehicle research and development since the company acquired Cruise Automation last year, said Kevin Kelly, a GM spokesman.

Computers can now tell you if the profile picture you use on social media sites or your online dating profile is making the right first impression. Scientists have developed an algorithm that uses artificial intelligence to predict what kind of first impression you will make on other people based on your photograph. The technology could prove useful for ensuring your appearance sends the right signal to prospective employers when going for an interview or what message your Facebook profile picture sends about you. The AI showed that Benedict Cumberbatch was a good choice to play Julian Assange in the Fifth Estate (top). Similarly Joseph Gordon Levitt was rated as a good match to play Edward Snowdon in the film Snowden (bottom).