"Data is the new oil." Although the expression has found widespread use, it has not been accepted by all as relevant for several reasons. One of these is the fact that while oil is a natural resource destined to run out, the quantity and availability of data is going in the opposite direction, that is, it is constantly increasing. Another is the fact that extrapolating facts is not the same as gaining insights on which to base informed decisions. Ronald Schmelzer talked about this in his article for Forbes [2], where he dismantled Humby's saying through precise reasoning.

When researchers design machine learning systems, their goal is typically to automate certain functions. Instead of being fully autonomous, however, most of these systems work together with humans. In order to be truly helpful, they need to understand what goals people have. Researchers at the Finnish Center for Artificial Intelligence (FCAI) have now taken important steps towards designing AI that understands people. At first, the researchers taught the AI to build a model of its user--human or machine.

When researchers design machine learning systems, their goal is typically to automate certain functions. Instead of being fully autonomous, however, most of these systems work together with humans. In order to be truly helpful, they need to understand what goals people have. Researchers at the Finnish Center for Artificial Intelligence (FCAI) have now taken important steps towards designing AI that understands people. At first, the researchers taught the AI to build a model of its user--human or machine.

It's a bright April day in Boston, and Gabi Zijderveld, a pioneer in the field of emotional artificial intelligence, is trying to explain why teaching robots to feel is as important as teaching them to think. "We live in a world surrounded by all these super-advanced technologies, hyper-connected devices, AI systems with super cognitive abilities -- or, as I like to say, lots of IQ but absolutely no EQ," says Zijderveld, chief marketing officer of Affectiva, the startup that spun out of the MIT Media Lab 10 years ago to build emotionally intelligent machines. "Just like humans that are successful in business and in life -- they have high emotional intelligence and social skills -- we should expect the same with technology, especially for these technologies that are designed to interact with humans." Giving machines a soul has been a dream of scientists, and sci-fi writers, for decades. But until recently, the idea of robots with heart was the stuff of moviemaking.

The past decade of machine learning has given us self-driving cars, practical speech recognition, video game playing robots, effective web search, and revolutionary drug treatments. While Artificial Intelligence has been impressive in achieving these specific tasks, this does not always correspond to the broader goal of cultivating human well-being. This winter, Stanford is launching a unique class that aims to bridge the gap between technology and societal objectives: How do we design AI to promote human flourishing? We will draw on behavioral research to discuss what makes humans thrive. Behavioral research shows that for people to flourish, they need meaning, which involves an ability to understand and value others, a sense of belonging, and knowledge that they are making a contribution bigger than themselves.

The point is, there are too many people asking what AI will transform, and not enough asking how. There may be no greater example than in medicine. AI has remarkable promise for the industry. Done right, even basic machine learning could transform how doctors work, making them smarter, more efficient, and less error-prone. Yet doctors themselves, while eager to try out the newest procedure or medicine, typically remain dead set against a machine telling them what to do.

Michael Krigsman: Artificial intelligence is one of the great buzzwords of our time, but there's substance behind it in some quarters. Today we're talking with somebody who is actually designing AI systems. We are on Episode #257 of CxOTalk. Before we dive in, I want to thank Livestream for providing our video streaming infrastructure. If you go to Livestream.com/CxOTalk, they'll actually give you a discount on their plans.

Here, she focuses on how AI can provide real value for end users. In the first article in this three-part series, I outlined reasons why designing artificial intelligence (AI) for humans is a strategic imperative. In this second article, we'll discuss how to create AI experiences that go beyond technology buzz and provide real value for end users. I've identified eight strategic pillars to serve as a consumer focused foundation for any ideation, design and development process. We'll begin with the first four of these pillars: The more we emphasize the end user of a potential AI experience, the more likely we are to create something that truly adds value to both our businesses and our lives.