Among those who do enter the criminal justice system, a disproportionately high number are people of color. In 2010, the BJS found that for every 100,000 Americans, 380 inmates are white, while 2.5 times that many (966) are Latino. A whopping 2,207 are black -- nearly six times as many black Americans are incarcerated as their Caucasian counterparts. Is it any wonder, then, that America's minority communities express such little faith in the fairness of US legal institutions? In a nation that incorporated structural racism into its social system for nearly a century -- after hundreds of years of slavery -- are you really surprised that people of color have historically distrusted the legal system?

Last year at the DARPA Robotics Challenge Finals, NASA announced a new challenge for humanoid robots: the Space Robotics Challenge (SRC), which will "prepare robots for the journey to Mars." Just like the DRC, the first stage of the SRC will consist of a virtual challenge, run in the Gazebo simulator, followed up by a physical challenge using NASA's R5 Valkyrie robots. As of yesterday, NASA has opened registration for the SRC, and we'll take a look at the format of the competition, the challenges that teams will need to complete, and what they can take home for winning. The Space Robotics Challenge focuses on developing software to increase the autonomy of dexterous mobile robots--particularly those of humanoid format--so they can complete specific tasks during space travel or after landing on other planets (such as Mars), as well as on Earth. In the not too distant future, R5 has arrived on Mars along with supplies ahead of a human mission.

Machine learning, a subset of artificial intelligence (AI) that is sometimes called cognitive computing, refers to the technology that allows machines to "learn" and "decide" like humans. The process is a complex one, centering on the development of programs that can grow with new data--all sans human intervention. A powerful new wave of technology, machine learning has the potential to change how enterprise companies do business. Machine learning is not just science fiction anymore. While machine learning is still in the earliest stages of development and has not yet reached full-scale adoption, some influential companies have already started experimenting with these technologies and have released open-sourced versions of their software.

From Siri to Alexa, voice interfaces are becoming increasingly common, but for all their recent advances, they often struggle with one of the most basic characteristics of human speech: accents. The problem is so prevalent that computer scientists have identified the existence of a "machine voice," a standardized way of speaking that individuals with accents adopt in the hope of being understood. Researchers even warn about the existence of a "speech divide" that ostracizes individuals whose accents differ from those the machines have been trained on. As is often the case with technology built on large data sets, the problem begins with the input. If you only train your interface using a narrow selection of voices, then it won't know how to respond to accents that fall outside of its frame of reference.

Over the course of a week in March, Lee Sedol, the world's best player of Go, played a series of five games against a computer program. The series, which the program AlphaGo won 4-1, took place in Seoul, while tens of millions watched live on internet feeds. Go, usually considered the most intellectually demanding of board games, originated in China but developed into its current form in Japan, enjoying a long golden age from the 17th to the 19th century. Famous contests from the period include the Blood Vomiting game, in which three moves of great subtlety were allegedly revealed to Honinbo Jowa by ghosts, enabling him to defeat his young protégé Intetsu Akaboshi, who after four days of continuous play collapsed and coughed up blood, dying of TB shortly afterwards. Another, the Ear Reddening game, turned on a move of such strength that it caused a discernible flow of blood to the ears of the master Inoue Genan Inseki. That move was, until 13 March this year, probably the most talked about move in the history of Go. That accolade probably now belongs to move 78 in the fourth game between Sedol and AlphaGo, a moment of apparently inexplicable intuition which gave Sedol his only victory in the series. The move, quickly named the Touch of God, has captured the attention not just of fans of Go but of anyone with an interest in what differentiates human from artificial intelligence. DeepMind, the London-based company behind AlphaGo, was acquired by Google in January 2014.

It has been four months since we launched the Kik Bot Shop and Facebook opened its bot platform for Messenger. It's been about the same time since the hype around bots was at its peak, with Microsoft CEO Satya Nadella predicting that bots would be as big as apps. Since then, the hype has cooled, with some people now wondering why bots suck and politely asking not to be exposed to them. At Kik, we remain bullish on bots, but we've noticed the same thing everyone else has: so far, there has been no killer bot. This is not yet the world that the early hype promised.

"It doesn't matter whether you are a lion or a gazelle. When the sun comes up, you better start running." In my previous article, I discussed how AI has become a ground reality and is already touching our lives and businesses. As its use cases expand and the contagion spreads, it is important for businesses to not only watch it closely but to take certain steps to prepare themselves in the race for survival. As during any technology revolution, it is going to be a tough transition.

If you ask kids today why phrases like "hang up" the phone or "roll down" the window exist, chances are they'll have no idea. Fast-forward to the near future and "search the web" may also cause a few head scratches. "We're evolving, but remain electronic'hunters and gatherers,'" explained Ralph Lucci, cofounder and user experience director at Behavior Design. But that's about to change thanks to today's quickly emerging artificial intelligence (AI) technology for practically every industry, including education. "The day will soon come when we'll sardonically ask ourselves: 'Remember when we had to visit a website and look around for what we needed?' Now the data comes to us."

For enterprises at the forefront of digital transformation, it's hard to underestimate the value that cognitive technologies bring to data-driven business processes. More than just automation, cognitive computing kicks things up to the next level by attempting to mimic human thought, both in terms of perception and the ability to make informed, even intuitive, decisions. There are many forms of cognitive computing--some of them familiar, some bordering on the esoteric. Machine learning is probably the most common form today, powering much of the search and e-commerce services available on the web. But more advanced forms of artificial intelligence are well along the development path, and these are already uniting with speech recognition software and other technologies to produce in ways that can revolutionize business throughout the next few years.