JERUSALEM – The Israeli military said Tuesday the militant group Hezbollah and Iran have built a precision-missile factory in neighboring Lebanon's Bekaa Valley. The army issued a statement saying that "in fear of strikes" by Israel, Hezbollah had moved key equipment from the site to "civilian locations in Beirut." It didn't specify when this happened. The military said the factory was of "superior importance" to Hezbollah. An official, speaking anonymously under military rules, said the factory is operational but missing major components.

Michael Niedermayer used to fly drones for the U.S. Army and the Central Intelligence Agency, gathering real-time, life-and-death intelligence on battlefields in Iraq. Now he pilots delivery robots for a San Francisco Bay Area startup that wants to disrupt burrito delivery. Postmates, which in mid-August received a permit to operate its Serve delivery robot in San Francisco and is already testing it for food delivery in Los Angeles, employs a growing team of "pilots" to remotely oversee, and at times steer, these four-wheeled food ferries. "We will probably see a drastic increase in our workforce over the next five years," says Postmates Chief Executive Bastian Lehmann. Across industries, engineers are building atop work done a generation ago by designers of military drones.

A pair of researchers associated with the U.S. Air Force want to give nuclear codes to an artificial intelligence. Air Force Institute of Technology associate dean Curtis McGiffin and Louisiana Tech Research Institute researcher Adam Lowther, also affiliated with the Air Force, co-wrote an article -- with the ominous title "America Needs a'Dead Hand'" -- arguing that the United States needs to develop "an automated strategic response system based on artificial intelligence." In other words, they want to give an AI the nuclear codes. And yes, as the authors admit, it sure sounds a lot like the "Doomsday Machine" from Stanley Kubrick's 1964 satire "Dr. The "Dead Hand" referenced in the title refers to the Soviet Union's semiautomated system that would have launched nuclear weapons if certain conditions were met, including the death of the Union's leader. This time, though, the AI-powered system suggested by Lowther and McGiffin wouldn't even wait for a first strike against the U.S. to occur -- it would know what to do ahead of time. "[I]t may be necessary to develop a system based on artificial intelligence, with predetermined response decisions, that detects, decides, and directs strategic forces with such speed that the attack-time compression challenge does not place the United States in an impossible position," they wrote. The attack-time compression is the phenomenon that modern technologies, including highly sensitive radar and near instantaneous communication, drastically reduced the time between detection and decision time. The challenge: modern weapon technologies, particularly hypersonic cruise missiles and vehicles, cut the window even further. "These new technologies are shrinking America's senior-leader decision time to such a narrow window that it may soon be impossible to effectively detect, decide, and direct nuclear force in time," Lowther and McGiffin argue. The idea is to use an AI-powered solution to negate any surprise capabilities or advantages of retaliatory strikes of the enemy. It would replace what Lowther and McGiffin describe as a "system of systems, processes and people" that "must inevitably be capable of detecting launches anywhere in the world and have the ability to launch a nuclear strike against an adversary." Not surprisingly, points out Bulletin of the Atomic Scientists editor Matt Field, handing over the nuclear codes to an AI could have plenty of negative side effects. One of them is automation bias, as Field points out in his piece. People tend to blindly trust what machines are telling them, even favoring automated decision-making over human decision-making. And then there's the simple fact that the AI doesn't have much data to run on, Field argues. That means that most of the data fed to the AI would be simulated data. Strangelove" is anything to go by, as long as all major world powers are made aware of the automated system, it could keep them from attacking the United States.

One of the biggest legal problems protecting AI users in the coming years will be accountability – dealing with the opacity of the black box and explaining decisions made by machine thinking. Understanding the logic behind an AI finding is not an issue where AI is assisting in spotting real-world risks that affect individuals – such as the current use of AI in radiology, where failure to use AI radiology analysis may soon be considered malpractice. As long as the AI is accurate and productive in showing where cancer may exist, we don't care how the machine picked that specific spot on the x-ray, we are just happy to have another tool that helps save lives. But where the AI proposes treatments or outcomes, your clients – healthcare and otherwise – will need to be ready to defend those decisions. This means an entirely different baseline organization and feature set for than the AI currently envisioned or in use.

These robotic partners were hailed as'the future of work', particularly in the manufacturing sector, but concerns about widespread robotic implementation are rife. Figures released by the Office for National Statistics (ONS) in March claim that 1.5 million people in England alone are at risk of losing their jobs to automation, suggesting that these fears are justified. However, automation can actually help manufacturers thrive and survive many of the workforce challenges they currently face. These include the'crippling skills shortage', which continues to blight the industry, and is putting workforces under increased pressure. At the same time, tougher immigration rules, associated with the UK's imminent departure from the EU, means that working in the UK will become less attractive or accessible for foreign nationals.

Ed. note: This is the first article in a two-part series about AI, its potential impact on how organizations approach security, and the accompanying considerations around implementation, efficacy, and compliance. Is Artificial Intelligence (AI) on track to help the world streamline and solve against tasks that are better left to a machine? One might think so, given everything we've seen and heard about the impact of AI on our society -- from our phones telling us the best way to drive home, to chatbots on e-commerce sites answering product questions, to devices as small as a thermostat or as large as an electric vehicle removing friction from everyday life. Now AI is entering the space of cybersecurity, promising to bring greater speed and accuracy in detecting and responding to breaches, user behavior analysis, or predicting new strains of malware. AI and machine learning technologies can help protect organizations from a continuously evolving threat landscape -- but AI is not just for sophisticated attacks, AI can also help protect against classic attack scenarios.

File photo - U.S. Army soldiers take part in a U.S.-South Korea joint live-fire military exercise at a training field in Pocheon, south of the demilitarized zone separating the two Koreas, March 25, 2015. The age is fast emerging wherein forward-operating soldier sensors, weapons and networking technologies will all rely upon secure computing to perform most advanced combat tasks. While many elements of this scenario already exist in various forms, technology is progressing quickly to the point where virtually all combat systems will be cyber-reliant. Soldier-worn computers will instantly connect target information, drone feeds and enemy tracking data - among other things. Computers and sensors are already being woven into soldier uniforms and being ergonomically engineered to accompany forces in battle for this specific purpose.

Around a year ago, amidst numerous desktop browsers, a LinkedIn notification blinked expectantly. The freshly minted digital magazine of Forbes unleashing its 30 Under 30's. Intrigued, I hastily found the social entrepreneurship section. This was definitely very special. But it would take more than half a year since connecting with Emily on LinkedIn, to find the guts to actually reach out and hear more…because in reality, other than the recent Sciences Po course I took on algorithmic governance, I had underestimated how much potential AI had within law enforcement and justice.

The government is actively pursuing a strategy which places the UK at the'forefront of the artificial intelligence and data revolution', however, the £45 million to be allocated for 200 extra PhDs in AI and related disciplines will barely make a dent in this omnipresent issue. In order to progress towards an AI future, we need to value the human role in this process and ensure the right skills are in place to develop the best tech. By better preparing a shift towards data skills, companies can build an army of citizen data scientists' capable of better reacting and leading in a data-led world. Through empowering every member of the business to use and leverage analytics to amplify their abilities companies can develop existing talent to understand the data in a business context without investing in consultants to do relatively easy data tasks. Without the right workforce, organisations simply cannot proceed to tackle the technical challenges existing in a data-driven industry.