Group items matching

in title, tags, annotations or url

"The school will teach cyber skills to some of the UK's most gifted 16- to 19-year-olds. It will select on talent alone, looking in particular for exceptional problem solvers and logic fiends, regardless of wealth or family background, according to Alastair MacWillson, a driving force behind the initiative. "The cyber threat is the real threat facing the UK, and the problem it's causing the UK government and companies is growing exponentially," said MacWillson, chair of Qufaro, a not-for-profit organisation created by a consortium of cybersecurity experts for the purposes of education."

"In terms of safety, a 2013 Navigant Research report noted "the potential for greatly reduced accident rates." Such potential rests on the basic logic of driving: Good driving relies on physics calculations; bad driving happens thanks to human physical limitations like intoxication and sleepiness."

"Atlas is a semi-autonomous system. The operator tells the robot where to be and what position to take, such as where to put its hands on a vacuum cleaner, and then the robot comes up with a plan of how to do that. For some chores Atlas's actions are logical and human-like. Others require re-thinking of how to get the job done in a way that its quite different to the way a person would perform the action."

"THE DIGITAL DIVIDE The fear of losing control aside, many hawkers also have to deal with another major challenge: Digital technology, which entails some basic competence in logic and literacy - much to the horror of those who only received some primary school education, typical of the older generation of hawkers."

"Humming does not sit easily with the way we imagine technology, but it highlights a crucial truth about how humans navigate the world of work, in offices, online or anywhere else: even if we think we are rational, logical creatures, we make decisions in social groups by absorbing a wide range of signals. And perhaps the best way to understand this is to employ an idea popularised by anthropologists working at companies such as Xerox during the late 20th century, and since used by Beunza and others on Wall Street: "Sense-making"."

"Let's say you have an IoT device that is well protected with functions that can be accessed through a well-defined API; even if you can control the device through the API, you probably can't do too much harm. Firmware, the programming inside the device has logical constraints that don't allow you, for example, to close garage doors while someone is in the way of them or overheat a device so that it combusts.  We used to trust that hardware, such as a common kitchen appliance, could be trusted and could not be easily altered without physically dismounting the device. But with today's "smart" appliances, this is no longer the case."

"First of all, in the short term I agree with arguments that comparative advantage will continue to keep humans relevant and in fact increase their productivity, and may even in some ways level the playing field between humans. As long as AI is only better at 90% of a given job, the other 10% will cause humans to become highly leveraged, increasing compensation and in fact creating a bunch of new human jobs complementing and amplifying what AI is good at, such that the "10%" expands to continue to employ almost everyone. In fact, even if AI can do 100% of things better than humans, but it remains inefficient or expensive at some tasks, or if the resource inputs to humans and AI's are meaningfully different, then the logic of comparative advantage continues to apply. One area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach "a country of geniuses in a datacenter"."

"That's why the best systems may come from a combination of AI and human work; we can play to the machine's strengths, Ilievski says. But when we want to compare AI and the human mind, it's important to remember "there is no conclusive research providing evidence that humans and machines approach puzzles in a similar vein", he says. In other words, understanding AI may not give us any direct insight into the mind, or vice versa."