In this talk, Prof. Iiyoshi goes head to head with an AI questioning the fate of education and lifelong learning! Toru Iiyoshi was previously a senior scholar and Director of the Knowledge Media Laboratory at the Carnegie Foundation for the Advancement of Teaching (1999-2008), and Senior Strategist in the Office of Educational Innovation and Technology at Massachusetts Institute of Technology (2009-2011). He is the co-editor of the Carnegie Foundation book, "Opening Up Education: The Collective Advancement of Education through Open Technology, Open Content, and Open Knowledge" (MIT Press, 2008) and co-author of three books including "The Art of Multimedia: Design and Development of The Multimedia Human Body" and numerous academic and commercial articles. He received the Outstanding Practice Award in Instructional Development and the Robert M. Gagne Award for Research in Instructional Design from the Association for Educational Communications and Technology. Currently, he is the director and a professor of the Center for the Promotion of Excellence in Higher Education (CPEHE) at Kyoto University.

In my last post I discussed how machine learning could be used to detect phishing-based account compromise attacks using a real-world use case from the recent Verizon Data Breach Digest. This time I'll examine how to detect insider threats using similar techniques. The example I've chosen involves an organization in the middle of a buyout that was using retention contracts to prevent employee attrition. To find out what other employees were being offered, a middle manager acquired IT administrator credentials from a colleague and friend. He used these credentials to access the company's onsite spam filter and spy on the CEO's incoming email. The same credentials were also used to browse sensitive file shares and conduct other unauthorized actions.

Last month I examined how machine learning could be used to detect low and slow insider threats. In this, the final installment of my trilogy on real-world use cases from the recent Verizon Data Breach Digest, I'll discuss how remote access threats can be exposed with the machine learning techniques I've covered in my two previous blogs. In this example, a manufacturing company experienced a breach of a shared engineering work station in its R&D department. A phishing email resulted in a Remote Access Trojan (RAT) backdoor being downloaded onto the system, which enabled the threat actors to escalate privileges and capture user credentials for everyone who had used the system. By the time the breach was discovered, a significant amount of information had been leaked out via FTP to a foreign IP address.

Growing artificial intelligence systems are unearthing previously unknown wrongdoing in organisations, but they should be matched by human oversight. It all started as a normal day for David and John (not their real names). Out of the blue, the Audit and Compliance team called them, seeking clarifications about some of their recent trades. Shortly afterward, David and John realised they had just become more victims of the rise of the machines. Both traders had engaged in inappropriate behaviours. David had favoured a single counterparty at the expense of his employer but this had been cloaked by a complex trading pattern.

Text, sentiment, and social analytics help you tune in, at scale, to the voice of the customer, patient, public, and market. The technologies are currently being applied in an array of industries ranging from healthcare to finance, media, and consumer markets. It's useful stuff, insight extracted from text, audio, images, and connections. The state of analytics is pretty good at the moment, although uptake in certain areas -- digital analytics and market research, for example -- has lagged behind. This is true for both technical innovation and for more-of-the-same uptake.

Have anything in mind that you think is awesome and would fit in this list? Feel free to send a pull request.

Are we set to enter an era where robots brew beer and artificial intelligence takes over from brewers? BeverageDaily talks to IntelligentX Brewing Co, which has launched the'world's first beer brewed by artificial intelligence.' The London-based company has created a premium beer that uses complex machine learning algorithms to improve future batches. It does this by taking reviews from consumers, and feeding these back to the AI where information is used by the brewing algorithm. For many brewers – and indeed consumers – creating beer is about the craftsmanship behind the brew.

A very, very small quadcopter, one inch in diameter can carry a one- or two-gram shaped charge. You can order them from a drone manufacturer in China. You can program the code to say: "Here are thousands of photographs of the kinds of things I want to target." A one-gram shaped charge can punch a hole in nine millimeters of steel, so presumably you can also punch a hole in someone's head. You can fit about three million of those in a semi-tractor-trailer. You can drive up I-95 with three trucks and have 10 million weapons attacking New York City. They don't have to be very effective, only 5 or 10% of them have to find the target. There will be manufacturers producing millions of these weapons that people will be able to buy just like you can buy guns now, except millions of guns don't matter unless you have a million soldiers. You need only three guys to write the program and launch them. So you can just imagine that in many parts of the world humans will be hunted. They will be cowering underground in shelters and devising techniques so that they don't get detected. This is the ever-present cloud of lethal autonomous weapons. Mary Wareham laughs a lot. It usually sounds the same regardless of the circumstance -- like a mirthful giggle the blonde New Zealander can't suppress -- but it bubbles up at the most varied moments. Wareham laughs when things are funny, she laughs when things are awkward, she laughs when she disagrees with you. And she laughs when things are truly unpleasant, like when you're talking to her about how humanity might soon be annihilated by killer robots and the world is doing nothing to stop it. One afternoon this spring at the United Nations in Geneva, I sat behind Wareham in a large wood-paneled, beige-carpeted assembly room that hosted the Convention on Certain Conventional Weapons (CCW), a group of 121 countries that have signed the agreement to restrict weapons that "are considered to cause unnecessary or unjustifiable suffering to combatants or to affect civilians indiscriminately"-- in other words, weapons humanity deems too cruel to use in war. The UN moves at a glacial pace, but the CCW is even worse.

Cooperation is one of the hallmarks of being human. We are extremely social compared to other species. On a regular basis, we all enter into helping others in small but important ways, whether it be letting someone out in traffic or giving a tip for good service. We do this without any guarantee of payback. Donations are made at a small personal cost but with a bigger benefit to the recipient. This form of cooperation, or donation to others, is called indirect reciprocity and helps human society to thrive.

Earlier this year, the union representing U.S. airport security agents called for hiring 6,000 additional screeners to reduce long waits and help handle the rise in summer travelers. Government positions -- especially those at an agency like the Transportation Security Administration -- require a rigorous screening process in which officials might consider 100 employees for every one hire made. Airport security is clearly an area that could benefit from automation. Through a process known as organizational change management, TSA could automate some entry-level IT jobs that were previously handled by tech employees and repurpose those employees to ease the demand for additional security screeners. Automation allows employees to focus on more complex tasks, and artificial intelligence-based technology can handle knowledge work in a fraction of the time and with no errors -- a level of performance humans can't match.