Aircraft fuel is without a doubt the biggest cost for any airline and often receives widespread attention, especially when airlines hedge their bets the wrong way. Cathay Pacific reported a HK$4.49 billion fuel-hedging loss in the first half of 2016, which has hurt the airline's profitability. The second biggest expense for an airline is human capital, and researchers from Hong Kong Polytechnic University and University of Nottingham Ningbo China Business School may have found a solution to ease some of Cathays financial woes through an unlikely source – Machine Learning and Data Science. The researchers say that a "poorly designed airline crew schedule can result in unreliable flight schedules, significantly jeopardizing airline operations and profitability if insufficient crew members are available or other glitches occur. For that reason, managing airline crew scheduling and costs are one of the most crucial topics for airlines because it yields enormous economic benefits and ranks as the second highest expenditure after fuel costs."

Facebook and Google are two of Silicon Valley's leaders in artificial intelligence. They have both invested heavily in AI, hiring loads of top researchers to develop projects like the Facebook Messenger "smart" assistant M, or Google's in-the-works AI-powered chatbot. While Facebook and Google are duking it out in international competitions, the two companies are far from alone in their efforts to dominate the space. As for the rest of Silicon Valley, research firm CB Insights recently published a report on the AI investments the tech industry is making.

A year ago, a researcher tested Samsung's S Voice digital assistant by telling it he was depressed. "Maybe it's time for you to take a break and get a change of scenery." Researchers found Apple's Siri and Microsoft's Cortana couldn't understand queries involving abuse or sexual assault, according to a study published in March in JAMA Internal Medicine. Next week's Consumer Electronics Show will show off digital assistants' abilities to make our lives a little easier by adding more voice-powered smarts into our lights, appliances and door locks. While these smart-home ideas are likely to gain plenty of attention at CES, the JAMA study highlights the need to improve digital helpers' responses to more critical health and wellness issues, as well.

From car accidents to bridge collapses, 1.25 million road fatalities occur across the world annually. Another 20 to 50 million people suffer road injuries per year, some resulting in lifetime disabilities. Road incidents are also the source of economic damage to the victims, their families and nations themselves as they generate medical treatment expenses and repair costs as well as reduce productivity. There's fear that without noticeable action, roads will become the seventh leading cause of death across the world by 2030. However, there's hope that with the help of emerging technologies such as artificial intelligence and Internet of Things, we can make our roads and bridges much more safer, save hundreds of thousands of lives, and spare billions of dollars in maintenance and repairs costs.

A technology incubator in the company, called Jigsaw--formerly known as Google Ideas--says it intends to spot and remove digital harassment with an automated program called Conversation AI. So if Conversation AI or similar tools make it easier and more efficient to exercise such control, it's a reminder that "solving" the abuse problem, whether through human or automated means, requires moving away from maximal inclusivity as the highest ideal online. The Wild West nature of those sites will become only more apparent if tools like Conversation AI make moderated sites function even better. While Jigsaw efforts like Project Shield aim to provide defenses for politically sensitive websites, Conversation AI makes it easier to filter out unwanted speech--but the question is, unwanted by whom?

Length of Stay (LOS) is a critical factor in managing hospital quality & economic outcomes in Healthcare. The metric is calculated by summing the total number of days for all discharges & dividing it by the total number of discharges. Insurance programs such as Medicare are moving to a model where they are compensating Hospitals the same amount for a specific surgery (e.g. Joint replacement) regardless of the number of days spent in the hospital. Therefore, hospitals & the overall healthcare ecosystem are motivated to reduce LOS.

The White House has issued a sequel to its October report on how the U.S. should approach artificial intelligence and its effects on various groups and institutions. Today's report focuses on the potential economic effects of AI, and while it's far from a dark outlook, it does warn that with improper handling, automation could drive further inequality in this already deeply divided country. "You look at the last couple decades, we have seen an increase in inequality," said Jason Furman, Chairman of the Council of Economic Advisers, on a press call discussing the paper. "In part that increase has been because of a technological fact: that technological innovation, more recently, has helped complement people with higher skills. So we now have a few decades of experience with technology helping to contribute to inequality."

Meet YoloData, one of the latest DMV-area data analytics startups promising to make sense of millennials for businesses. The Ashburn, Va.-based startup provides data scientists and business developers with an aggregated data platform focused on how millennials might respond to a business. Co-founder and CEO Bryan Short said the platform collects financial and health data, mostly, from public government sources and a few private partnerships, but it also lets customers import their own private data for individual analysis. In January, the nine-month-old company will close its first round of $500,000 backed mostly by local angel investors who have previously invested in Short's previous ventures, including a few mobile apps. This raise will be used to prep YoloData's technology for beta testing in the spring.

On Tuesday, the US government continued a national conversation on the impact of artificial intelligence on the workforce. The new White House report, Artificial Intelligence, Automation, and the Economy, serves as a follow-up to its October report, Preparing for the Future of Artificial Intelligence, which looked at the role of government in the development and implementation of artificial intelligence. It's an effort by the US government to address the huge impact automation is currently having on jobs--which promises to be felt more deeply as artificial intelligence advances. The report explores the history and impact of automation on the economy, and looks at jobs that could be lost or gained from artificial intelligence. It also outlines three policy strategies meant to help prevent automation from taking jobs away from humans.

Why is it important to democratize machine learning? Why is it important to democratize machine learning? For two reasons: first, because machine learning and artificial intelligence have tremendous potential for value creation, and we should not let any of that potential go to waste. People with the drive and intelligence required to advance the field of ML or to use AI to create great things can come from anywhere, and we have a responsibility to make sure that these people can readily access the knowledge and tools they will need to realize their full potential. What's more, we should do our best to inspire capable people the world over so that they will want to dedicate their talents to value creation through AI.