Suppose you go shopping for mangoes one day. The vendor has laid out a cart full of mangoes. You can handpick the mangoes, the vendor will weigh them, and you pay according to a fixed Rs per Kg rate (typical story in India). Obviously, you want to pick the sweetest, most ripe mangoes for yourself (since you are paying by weight and not by quality). How do you choose the mangoes?

At the meeting, HuiyiHuiying and Intel jointly launched the "Artificial Intelligence Breast Cancer Full Cycle Health Management System" to help screening and diagnosis through artificial intelligence technology. Saying Huo, Wei Sun, Xuejuan Luo and Jiaqi Li were present as representatives of this year's charity star and were awarded the "Pink Ambassador" award. According to the statistics, breast cancer is the second leading cause of death in women and in fact, one in eight women will be diagnosed with breast cancer. The incidence rate has ranked first among female malignant tumors and has become the first killer threatening women's health. "Early screening, Early detection, Early treatment" is essential for women to prevent breast cancer.

In this episode of the Data Show, I spoke with Sharad Goel, assistant professor at Stanford, and his student Sam Corbett-Davies. They recently wrote a survey paper, "A Critical Review of Fair Machine Learning," where they carefully examined the standard statistical tools used to check for fairness in machine learning models. It turns out that each of the standard approaches (anti-classification, classification parity, and calibration) has limitations, and their paper is a must-read tour through recent research in designing fair algorithms. We talked about their key findings, and, most importantly, I pressed them to list a few best practices that analysts and industrial data scientists might want to consider. Sam Corbett-Davies: The problem with many of the standard metrics is that they fail to take into account how different groups might have different distributions of risk.

The first novel by YouTube star Hank Green, An Absolutely Remarkable Thing, is about a young woman named April who becomes an internet celebrity after posting video of a mysterious alien robot. She quickly discovers that being famous has a lot of downsides--something Green and his friends have learned the hard way. "I started to have notoriety in my late 20s or early 30s--like the first time someone recognized me in public was probably when I was 29 years old," Green says in Episode 328 of the Geek's Guide to the Galaxy podcast. "Whereas for a lot of my friends, this happened in their teens or early 20s, and it was sort of their first job, being a famous person, without any of the infrastructure of normal famous-person life, because this was all so new, and that was difficult." April soon draws the ire of Peter Petrawicki, a professional troll who accuses her of being in league with the alien invaders.

Do security analysts trust analytics that are powered by Machine Learning (ML)? In my opinion, it seems as if the vast majority do not. Given this skepticism, the obvious next question is "why not?" To answer that, we need to step back quite a bit. To really come up with a good answer, I believe it's worth taking a moment to understand some fundamentals around analytics and Machine Learning.

In this interview, Tamim Saleh cuts through the hype around artificial intelligence with guidance for executives about where and how to employ AI in their businesses. In this episode of our Inside the Strategy Room podcast, senior partner Tamim Saleh cuts through the hype around artificial intelligence (AI) and offers clear guidance for executives looking to make precise strategic decisions about where and how to employ AI in their businesses. Tamim shares insights on the impact of machine vision on AI, the future of voice recognition, and the latest developments in advanced analytics, virtual assistants, and robotics. He outlines the challenges companies face when adopting AI and the steps CEOs can take to overcome them. Tamim is a senior partner in our London office, and he is with me at our Global CFO Forum, where he's speaking about AI and machine learning. Tamim, one of the things you've talked about is the notion of five different developments of AI. Tamim Saleh: Machine learning and AI are limited by the fact that when we input data as humans, first of all we are slow, and we make mistakes. One of the fastest-growing technologies is capturing data through image analytics and cameras. And the beauty of this is, cameras don't make the same mistakes we do, because they capture things the way they are, and they don't see the world the same way that we do. In fact, the spectrum is much wider than what we see. It includes infrared, et cetera.

A former employee of Google has warned of the web giant's'disturbing' plans for a search engine in China which could help Beijing monitor its citizens online. Jack Poulson wrote in a letter to the US Senate's commerce committee that the proposed Dragonfly website was'tailored to the censorship and surveillance demands of the Chinese government'. In his letter he also claimed that discussion of the plans among Google employees had been'increasingly stifled'. Mr Poulson was a senior research scientist at Google until he resigned last month in protest at the Dragonfly proposals. A former employee of Google has warned of the web giant's'disturbing' plans for a search engine in China which could help Beijing monitor its citizens online While China is home to the world's largest number of internet users, a 2015 report by US think tank Freedom House found that the country had the most restrictive online use policies of 65 nations it studied, ranking below Iran and Syria.

Starting with its acquisition of Kiva Systems for $775 million back in 2012, Amazon has been steadily investing in a robotic future. From delivery drones to a rumored home robot to a robotics picking challenge, Amazon definitely wants useful, practical robots to happen. We're not always sure that they're going about it the right way, but we are always in favor of companies with as much clout as Amazon has recognizing that robotics is worth focusing on, especially with an understanding that some problems are going to take years of work to solve. Brad Porter is the vice president of robotics at Amazon. He joined the company over a decade ago, initially working on Amazon's web operations and e-commerce architecture.

Two years ago, it started being possible. Today, it's a certainty: Canada is well on its way to becoming a global hub for artificial intelligence, or "AI." We are steadily attracting some of the brightest students and talented scientists to study and conduct research here. The challenge, however, is expanding the number of AI companies, spaces, and institutes to increase job availability and retain these talented individuals. If we can expand the pool of available jobs for our AI researchers and graduates, we stand a chance of retaining them to pursue their AI careers here, instead of losing them to Silicon Valley and giant companies like Google, Microsoft, Apple, and Amazon.

In March 2004, when René Koiter was 19, his twin brother Michel came down with a fever. René and Michel were students in the Netherlands--Michel at the Utrecht School of the Arts, René at the University of Utrecht--and they were doing freelance design work for Blizzard Entertainment, a video game developer about to launch its marquee franchise: World of Warcraft. Michel's fever wasn't supposed to be fatal. Michel was young and healthy--he and René were regulars at their local Taekwondo center. But a few days later, Michel's heart started failing, and René and their father rushed to the hospital to save him.