"The algorithm behind what3words took six months to write. Sheldrick worked on it with two friends he had grown up with. Mohan Ganesalingham, a maths fellow at Trinity College, Cambridge, and Jack Waley-Cohen, a full-time quiz obsessive and question-setter for Only Connect. After the initial mapping was complete, they incorporated an error-correction algorithm, which places similar-sounding combinations a very long way apart."
"Flooding involves deluging the citizen with a torrent of information - some accurate, some phoney, some biased - with the aim of making people overwhelmed. In a digital world, flooding is child's play: it's cheap, effective and won't generate backlash. (En passant, it's what Russia - and Trump - do.)
In her book, Roberts provides abundant evidence of how the Chinese authorities deploy these three techniques."
"In October 2016, algorithms reacted to negative news headlines about Brexit negotiations by sending the pound down 6% against the dollar in under two minutes, before recovering almost immediately. Knowing which particular headline, or which particular algorithm, caused the crash is next to impossible. When one haywire algorithm started placing and cancelling orders that ate up 4% of all traffic in US stocks in October 2012, one commentator was moved to comment wryly that "the motive of the algorithm is still unclear"."
"The animal matchmaking program isn't just for gorillas, and it takes some things into consideration that probably aren't on Tinder's radar. It scores every animal on a variety of traits (and when we say "every" animal, we mean there's an entry for each flamingo in each American zoo), including social skills, age, experience, family history, and interpersonal relationships. Oh, and genetic diversity. Animals with rare genes are more valuable to breeding programs because their offspring will introduce more genetic diversity into the dating pool."
"Hangzhou Zhongheng Electric is just one example of the large-scale application of brain surveillance devices to monitor people's emotions and other mental activities in the workplace, according to scientists and companies involved in the government-backed projects.
Concealed in regular safety helmets or uniform hats, these lightweight, wireless sensors constantly monitor the wearer's brainwaves and stream the data to computers that use artificial intelligence algorithms to detect emotional spikes such as depression, anxiety or rage."
"Neural networks can find telltale patterns in a person's gait that can be used to recognize and identify them with almost perfect accuracy, according to new research published in IEEE Transactions on Pattern Analysis and Machine Intelligence. The new system, called SfootBD, is nearly 380 times more accurate than previous methods, and it doesn't require a person to go barefoot in order to work. It's less invasive than other behavioral biometric verification systems, such as retinal scanners or fingerprinting, but its passive nature could make it a bigger privacy concern, since it could be used covertly."
"The system is called as"Intelligent Classroom Behavior Management System" and it is being used at Hangzhou No. 11 High School. With scanning facial expressions the system has the ability to even analysis six types of behaviors by the students such as standing up, reading, writing, hand raising, listening to the teacher, and leaning on the desk."
" If your consumption of content is tailored by near limitless observations harvested about people like you, how could your universe not collapse into the partial depiction of reality that people like you also enjoy? How could empathy and respect for difference thrive in this environment? Where's the incentive to stamp out fake accounts, fake news, paid troll armies, dyspeptic bots?"
"It is also self-improving. The 10-year-old grading software leverages deep learning algorithms to "compare notes" with human teachers' scores, suggestions, and comments. An engineer involved in the project compared its capabilities to those of AlphaGo, the record-breaking AI Go player developed by Google subsidiary DeepMind."
"Cellebrite, the Israeli-founded and now Japanese-owned company behind some of the software, claims a wider rollout would solve problems over failures to disclose crucial digital evidence that have led to the collapse of a series of rape trials and other prosecutions in the past year. However, the move by police has prompted concerns over privacy and the potential for software to introduce bias into processing of criminal evidence."
""The disproportionally high arrest rates for members of the black community make the use of facial recognition technology by law enforcement problematic," the letter reads, "because it could serve to reinforce this trend."
""The person on the other line said, 'unplug your Alexa devices right now,'" Danielle told KIRO. "'You're being hacked.'" The couple had reportedly placed Amazon devices in every room of their house to control the heat, lights, and security system. All of the gadgets were pulled out after their colleague proved they had received the unauthorized recording."
"An algorithm has no tastebuds; a neural net never gets the munchies. So can a robot brain really tell us what we'll want to eat? The question is whether AI systems will be able to excel in the sensual, creative work of tasting and developing new foods - and what we stand to gain or lose by inventing foods that really have our number."
"MIT researcher's at CSAIL have developed a lane-changing algorithm for self-driving cars. the algorithm allows for aggressive lane changes much like the kind only real drivers would be capable of.
it works by computing 'buffer zones' around autonomous vehicles and reassessing them on the fly. MIT uses a mathematically efficient approach which calculates new buffer zones if the default buffer zones lead to performance that's far worse than a human's driver."
"The revelation that encrypted email is vulnerable to a variety of devastating attacks (collectively known as "Efail") has set off a round of soul-searching by internet security researchers and other technical people -- can we save email?
One way to think about Efail is that it was caused by a lack of central coordination and control over email-reading programs -- the underlying protocols are strong and robust, but they can be implemented in ways that create real problems. In particular, the ability to show HTML inside a message makes email very hard to secure:"
"More than just a poetic metaphor, the butterfly effect says that there are some things that even the most advanced science can never predict. Well, that list of things just got a lot shorter. Scientists from the University of Maryland have used machine learning to predict chaos."
"The vast majority of emails flooding inboxes across Europe from companies asking for consent to keep recipients on their mailing list are unnecessary and some may be illegal, privacy experts have said, as new rules over data privacy come into force at the end of this week."
"This Digital Expiry Date offers companies the benefits of getting your data, personalizing results and still making profits, while putting some control in the user's hands. You will not have to worry about governments or companies in the future mishandling years' worth of information - which would limit the damage they could do. A Digital Expiry Date would maintain online innovation and profitability, while helping to prevent any future privacy disasters."
"Xiao Long, or "Little Dragon", is not your typical employee - she's a robot at China's first fully automated, human-free bank branch.
As guardian of the bank, she talks to customers, takes bank cards and checks accounts (she comes complete with a PIN pad) and can answer basic questions. After a quick initial chat with Xiao Long, customers pass through electronic gates where their faces and ID cards are scanned. On future visits, facial recognition alone is enough to open the gates and call up customer information."
" The machine's doing the prediction, making the distinct role of judgment in decision making clearer. So as the value of human prediction falls, the value of human judgment goes up because AI doesn't do judgment-it can only make predictions and then hand them off to a human to use his or her judgment to determine what to do with those predictions."
