We have a crisis of work. The secure, well-paid jobs of the past -- many of them in manufacturing -- are disappearing. What is replacing them is insecurity and uncertainty. The "gig economy", where people are paid performance by performance -- or piece by piece. "Piecework", we used to call it.

Svetlana Alexievich, winner of the 2015 Nobel Prize in literature, called the nuclear catastrophes at Chernobyl and Fukushima events that people cannot yet fully fathom and warned against the hubris that humans have the power to conquer nature. The 68-year-old Belarusian writer was in Tokyo at the invitation of researchers at the University of Tokyo, where she gave a lecture on Friday. More than 200 people attended. The Nobel laureate, who writes in Russian, is known for addressing dramatic and tragic events involving the former Soviet Union – World War II, the Soviet war in Afghanistan, the 1986 Chernobyl nuclear disaster and the 1991 collapse of the communist state. Her style is distinctive in that she presents the testimonies of ordinary people going through traumatic experiences as they speak, without intruding on their narratives.

Last week I attended IBM (IBM) World of Watson as both a speaker and an attendee, and today as I sit in my neighborhood Starbucks (SBUX) thinking about everything, all I can say is WOW! This was one of the most interesting, inspiring and amazing events I have ever attended. And we are still in the very early stages of Watson, Cognitive and AI. I invite you to follow me as I learn more and write more about the wonderful world of Watson, all the companies that work with it and how it will change our industries, our businesses and our lives. As a wireless analyst and columnist, I come at this world of Watson from the wireless, telecom, internet and television angle.

The fields of artificial intelligence and machine learning are moving so quickly that any notion of ethics is lagging decades behind, or left to works of science fiction. This might explain a new study out of Shanghai Jiao Tong University, which says computers can tell whether you will be a criminal based on nothing more than your facial features. The bankrupt attempt to infer moral qualities from physiology was a popular pursuit for millennia, particularly among those who wanted to justify the supremacy of one racial group over another. But phrenology, which involved studying the cranium to determine someone's character and intelligence, was debunked around the time of the Industrial Revolution, and few outside of the pseudo-scientific fringe would still claim that the shape of your mouth or size of your eyelids might predict whether you'll become a rapist or thief. Not so in the modern age of Artificial Intelligence, apparently: In a paper titled "Automated Inference on Criminality using Face Images," two Shanghai Jiao Tong University researchers say they fed "facial images of 1,856 real persons" into computers and found "some discriminating structural features for predicting criminality, such as lip curvature, eye inner corner distance, and the so-called nose-mouth angle."

Artificial Intelligence company Soul Machines was officially launched this week after it attracted US $7.5 million in its initial financing round from Hong Kong-based venture capital firm Horizons Ventures, making it the University's biggest Series A fund raising deal to date. The company is developing a completely new user interface between humans and their machines, based on technology created by Dr Mark Sagar and his team at the Auckland Bioengineering Institute (ABI) at the University of Auckland. Dr Sagar won two academy awards for his work on the Avatar blockbuster. He becomes the CEO of Soul Machines. He also heads the Bioengineering Institute's Lab for Animate Technologies.

For most people, it is not easy to picture the buying and selling of cognitive capabilities that have traditionally been embedded in humans – things like judgment and decision-making. Yet, thanks to recent advances in machine learning, we face the very real possibility of precisely such a'market for intelligence'. Given the potential of this market to transform the entire global economy, we must all begin preparing – now – for its emergence. To be clear, machine intelligence is still in its infancy, and while some of the current applications are remarkable, none are transformational. For example, the recommendation engines employed by companies such as Amazon and Netflix – which learn our preferences and recommend which books we should buy or which movies we should watch – are a common application of machine learning.

Besides your passport, what really defines your nationality these days? Is it where you were live? If it is, then despite an increase in "nationalism" (i.e., Brexit), we may see the idea of "nationality" quickly dissolve in the decades ahead… Or at least become an option you choose versus assume as a default. Residency, currency and language are rapidly being disrupted and dematerialized by technology. Increasingly, technological developments will allow us to live and work almost anywhere on the planet (and even beyond).

It's already one of the most technologically advanced countries in the world, what with its robotic hotels and its typhoon-powered wind turbines, and now, Japan is looking to further cement its position at the forefront of digital innovation. And it's all contingent upon a new supercomputer that aims to be the fastest in the world. The goal, Reuters reports, is to create a machine that will help the country's scientists create or improve upon technologies like driverless cars, robotics, and medicine. The lofty challenge won't come cheap. Reports note that the Ministry of Economy, Trade and Industry will invest around $173 million on the project as Japan attempts to differentiate itself from fellow Asian technology superpowers China and South Korea.

IoT is rapidly changing the way enterprises are using data to improve business decision-making. In order to derive business value, organizations must unlock insights from the data gathered and then act on these. In their session at @ThingsExpo, Eric Hoffman, Vice President at EastBanc Technologies, and Peter Shashkin, Head of Development Department at EastBanc Technologies, discussed how one organization leveraged IoT, cloud technology and data analysis to improve customer experiences and efficiencies. They shared the lessons learned, why they believe IoT works better with the cloud, and the four steps organizations should follow to ensure they are able to achieve big business intelligence with IoT. Speaker Bios Peter Shashkin is Head of Development Department at EastBanc Technologies.

From gender to education, the words used on social media carry impressions to others. Using publicly available tweets, social psychologists and computer scientists from the University of Pennsylvania Positive Psychology Center, Germany, and Australia are helping us to parse out the stereotypes formed by word choices on the social media channel Twitter. Utilizing natural language processing (NLP), a form of artificial intelligence, the researchers show where stereotyping goes from "plausible" to wrong. The research appears in Social Psychological and Personality Science. In a series of studies, participants were asked to categorize the authors of tweets based solely on the content of their social media posts.