Artificial intelligence promises to make hiring an unbiased utopia. Employee referrals, a process that tends to leave underrepresented groups out, still make up a bulk of companies' hires. Recruiters and hiring managers also bring their own biases to the process, studies have found, often choosing people with the "right-sounding" names and educational background. Across the pipeline, companies lack racial and gender diversity, with the ranks of underrepresented people thinning at the highest levels of the corporate ladder. Fewer than 5 percent of chief executive officers at Fortune 500 companies are women, and that number will shrink further in October when Pepsi CEO Indra Nooyi steps down.

AI is shaping the world, who will be shaping AI? The future may be uncertain, but one certainty is that today's youth will be central to shaping it. Acorn Aspiration's mission is to empower and assist teens in learning and shaping the future of AI for positive contributions to the world. More than 1500 young people have participated in Acorn's Bootcamps/Hackathons, Accelerator programs, and conferences to date. Acorn's latest initiative, TeensInAI, was launched at the UN AI for Good Summit in May, and followed by a 5-day Bootcamp/ Hackathon.

There are so many online classes available from sites like Coursera, edX, and Udacity that companies don't know what content to offer their employees. And once companies do choose a learning program, it's tough for them to figure out what skills their employees pick up and to what degree they've mastered them. They need an objective metric to evaluate proficiency. A new AI-powered tool developed by Coursera aims to be that metric. The feature lets companies that subscribe to its training programs see which of their employees are earning top scores in Coursera classes; how their employees' skills measure up to their competitors'; and what courses would help fill any knowledge gaps.

Twitter will not suspend Alex Jones or Infowars because they have not broken any rules, its CEO has said. Just about every other major technology company – including Apple, Facebook, YouTube and Spotify – have all acted to either completley ban or punish the controversial conspiracy theorist radio host. But Twitter says that his posts are not in contravention of any rules and so he will stay up. That is despite Jones having used the platform to amplify his beliefs, which include claims that the Sandy Hook school shooting did not actually happen at all and that those mourning murdered loved ones were paid actors. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Stanford University's Machine Learning Course Andrew Ng is the man. The founder of Google Brain and former chief scientist at Baidu, Andrew Ng's course is the clear winner in terms of ratings, reviews, and syllabus fit. Seeing how this course was what practically founded Coursera, that doesn't seem unbelievable. Although it has a smaller scope than the original Stanford class, it covers a large number of algorithms and techniques. The estimated timeline is eleven weeks, which includes two weeks of neural networks and deep learnings.

Here's the conundrum with corporate online learning: there are so many classes available from sites like Coursera, edX, and Udacity that companies don't know what content to offer their employees. And once companies do choose a learning program, it's tough for them to figure out what skills their employees pick up and to what degree they've mastered them. They need an objective metric to evaluate proficiency. A new AI-powered tool developed by Coursera aims to be that metric. The feature, which the Bay Area startup announced today, lets companies that subscribe to its training programs see which of their employees are earning top scores in Coursera classes; how their employees' skills measure up to their competitors'; and what courses would help fill any knowledge gaps.

With the wave of school shootings that have swept the U.S. in recent years, concerns about physical security and safety have overwhelmed parents, teachers and school administrators alike. Facial recognition technology, which would allow schools and law enforcement to quickly identify who is entering their schools and when could give school districts a powerful means to make schools even safer. Last month, RealNetworks, the streaming media company that garnered attention in the '90s and early 2000s for developing the first audio streaming solution, announced it would offer its facial recognition software, SAFR, for free to over 100,000 school districts. "School safety has become one of the top national issues in the United States in 2018," said Rob Glaser, chairman and CEO of RealNetworks in a press release. "We are proud to give our leading-edge SAFR for K-12 technology solution to every elementary, middle, and high school in America and Canada. We hope this will help make schools safer."

Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science. This can be daunting if you're new to data science, but keep in mind that different roles and companies will emphasize some skills over others, so you don't have to be an expert at everything. Pro tip: "Data scientist" is often used as a blanket title to describe jobs that are drastically different! One important piece of advice for your job search is to read data science job descriptions carefully. This will enable you to apply to jobs you're already qualified for, or develop specific data skill sets to match the roles you want to pursue.

Do you believe Artificial Intelligence is the future game-changer? Artificial Intelligence (AI) is not the FUTURE, it is ALREADY HERE. According to Wikipedia, "Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals". In a post by Josh Bersin, Founder and Principal at Bersin by Deloitte, it is mentioned that "AI is all about a wide range of machine learning tools and algorithms that quickly provide data, identify and predict patterns for informed decision making. It is possible for the systems to understand speech, identify photos, and use pattern matching to pick up signals about mood, honesty, and even personality. These algorithms are not "intuitive" like human beings, but they are fast, so they can analyze millions of pieces of information in seconds and quickly correlate them against patterns."

Stories of how students and developers get started in applied machine learning are an inspiration. In this post, you will hear about Álvaro Lemos story and his transition from student to getting a machine learning internship. I'm from Salvador, Bahia (Brazil), but currently, I live in Belo Horizonte, Minas Gerais (also in Brazil). I am studying Electrical Engineering at the Federal University of Minas Gerais and since the beginning of my undergraduation course, I've been involved with software development in some way. On my first week as a freshman, I joined a research group called LabCOM to help a colleague on his master's degree project.