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."

From emotionally cognisant AI friends to experiences that respond to your body language, we're about to go on a tour of some of the most advanced and exciting forms of future human-computer interaction, powered by the emotionally intelligent web. To understand this future, we first have to turn to our distant past. Roughly two million years before the first human, in Africa, we find an early precursor to man: the hominid. At this time, many human-like species were facing extinction. Hominids were under intense evolutionary pressures to survive, competing fiercely with other groups for scarce resources.

Neil Prakash, an Australian recruiter for the Islamic State group (also called ISIS), was arrested somewhere in the Middle East after surviving drone attacks by the FBI, the New York Times reported Thursday. The 25-year-old, who was linked to militant plots in Australia and had appeared in several ISIS propaganda videos, was believed killed in a U.S. airstrike in Iraq in April. According to the Times, which cited an unnamed senior American military official, Prakash was wounded in an airstrike earlier this year but survived. Another senior U.S. military official reportedly said the former Melbourne resident was arrested some time in the last few weeks by an unidentified Middle Eastern government. Prakash, who converted to Islam from Buddhism and took the name Abu Khaled al-Cambodi, left Australia in 2013 and has been recruiting fighters for ISIS since then.

The Artificial Intelligence (AI) market is booming, with nearly every major player in the enterprise space vying for a foothold. IBM, Amazon, GE, Microsoft, Google, Cisco, SAP, HPE, Verizon--you name it, anybody and everybody, even folks who used to sell hardware--are actively working on and/or want to stake a claim in a piece of the AI pie. What encompasses the AI market? Machine learning, natural language processing (NLP), voice recognition and image processing, application and geography are what we're looking at, with mobile devices and cloud being the enablers. And just what will the AI market be?

Banking and financial-services providers have more data than any other industry at their disposal – it's time to make the most of this, for the benefit of customers themselves. Digital transformation is changing the way banks talk to customers, but forward-looking financial institutions in the region are looking at how they can deploy artificial intelligence and automation to transform the customer experience, says Danny Drew, Avaya's Managing Director for South Africa. When was the last time you actually visited your bank branch? For most people, the answer is likely to be somewhere in between the last time you had to do a major financial transaction, such as applying for a loan or a mortgage, and… you just can't remember. The way consumers interact with banks has fundamentally changed over the past few years as trends like mobile and online banking have become increasingly important.

American surveillance drones have been flying over the Tunisia-Libya border to tackle threats by the Islamic State group, also known as ISIS, Tunisian President Beji Caid Essebsi said late Tuesday. He said that the drones will use his country's military bases for Tunisia's benefit. In a local television interview, Essebsi said that the U.S. drones were unarmed and they were flying over the border on Tunisia's request. It remained unclear that whether the aircraft flew across Libyan territory. Last month U.S. government sources told Reuters that American drones have started flying missions into Libya from a Tunisian air base.

Machine Learning is a subfield of computer science by which computers have the ability to learn without being explicitly programmed. Machine learning is a method used to develop complex models and algorithms that lend themselves to prediction. Machine learning is deployed where the system deals with large scale of data. Deployments of machine learning leads to improved speed and accuracy of the functions performed by the system. Machine learning is majorly deployed for solving classification and regression problems.

Wildlife advocates began testing an advanced system this spring to better identify and apprehend poachers. They say the technology has led to dozens of arrests that wouldn't have happened otherwise. Brian Heath, chief executive of the Mara Conservancy in Kenya, believes expanding the use of the technology throughout Africa could significantly improve anti-poaching efforts. "Our rangers now feel completely disadvantaged and blind without it," Heath said. "They get a huge amount of reassurance by having it and the ability to [better] see and identify people and animals." Heath, in partnership with the World Wildlife Fund, relies on a thermal imaging camera that uses artificial intelligence to identify animals and poachers up to a kilometer away.

The wildebeest, hippos, gazelles and warthogs of Southern Kenya have a little less to worry about. Wildlife advocates began testing an advanced system this spring to better identify and apprehend poachers. They say the technology has led to dozens of arrests that wouldn't have happened otherwise. Brian Heath, chief executive of the Mara Conservancy in Kenya, believes expanding the use of the technology throughout Africa could significantly improve anti-poaching efforts. "Our rangers now feel completely disadvantaged and blind without it," Heath said. "They get a huge amount of reassurance by having it and the ability to [better] see and identify people and animals."

Wildlife poachers who stalk endangered animals in East and South Africa have long operated under the cover of night. But lately not even a moonless sky is safe cover for stalking impalas, elephants, and rhinos. Now, the power of increasingly inexpensive infrared cameras, artificial intelligence, and drones are being used to stop illegal poaching. Rangers are rounding up veteran poachers in the middle of the night, says Colby Loucks, World Wildlife Fund's senior director of wildlife crime technology, who ask, dumbfounded, "How are you finding me?'" This spring, the World Wildlife Fund began deploying thermal sensing infrared technology from the imaging company FLIR to combat poaching in Kenya's Maasai Mara Conservancy park--and at another secret location that's home to rhinos, one of the most imperiled creatures on Earth.