London-based CUBE, was founded in 2011 and claims to offer a RegTech platform that can help businesses cut regulatory costs and minimize risk of non-compliance. The 94-employee company claims their platform can assist in predicting compliance risk, automating AML, Know Your Customer (KYC) and Cyber/information security processes. CUBE states that the platform uses machine learning to help enterprises to automatically keep track of global regulatory data and prompt alerts by detecting regulatory changes that pose a compliance risk. The company claims it has created a regulatory'data lake' that covers the regulations for financial services organizations across the globe. We, however, could find no evidence of how extensive their database is.

They eat in Google's cafeterias, ride its commuter shuttles and work alongside its celebrated geeks. They aren't entitled to stock and can't enter certain offices. Many don't have health insurance. Before each weekly Google all-hands meeting, trays of hors d'oeuvres and, sometimes, kegs of beer are carted into an auditorium and satellite offices around the globe for employees, who wear white badges. Those without white badges are asked to return to their desks. Google's Alphabet Inc. employs hordes of these red-badged contract workers in addition to its full-fledged staff. They serve meals and clean offices.

Face recognition technology sold by Amazon incorrectly matched 28 politicians with people arrested for a crime, an investigation by the American Civil Liberties Union has found. The findings raise further concerns about the use of similar technology by police departments in the US and beyond. Amazon's Rekognition is an image analysis service that offers the ability to automatically comb huge quantities of still pictures and video. It can detect objects and sensitive content, extract on-screen text, and compare faces to a reference image.

In a report published Thursday, the American Civil Liberties Union found that Amazon's facial recognition software mistakenly matched 28 U.S. Congresspeople to photos from a mugshot database. The software--which is already in use by some police departments--was disproportionately inaccurate in identifying people of color. In the test, the ACLU used Amazon's Rekognition software to compare photos of the 535 members of the House and Senate to a database of 25,000 mugshots, for an overall inaccuracy rate of 5%. But while only 20% of the members of Congress are non-white, about 40% of the falsely ID'd legislators were men and women of color. The potential outcomes of such misidentifications in life-or-death police encounters are terrifying to consider.

Working late, falling asleep on trains due to exhaustion and getting drunk to release tension from work might still be the typical image of the "salaryman." This country is notorious for a culture of overwork. Employees who stay late are still praised for hard work while others are frowned upon for leaving before their bosses do. Many even feel guilty about taking paid holidays. Karōshi, death from overwork, is a word now known worldwide.

Amazon defended the law enforcement use cases for its facial recognition technology Friday in an effort to throw water on fears raised by civil rights activists. Matt Wood, a leader on the Amazon Web Services machine learning team, published a blog post in response to criticism from the American Civil Liberties Union and other advocacy groups, which have been demanding the company stop selling its Rekognition software to police. In the post, Wood cautions that we "should not throw away the oven because the temperature could be set wrong and burn the pizza." Wood expressed skepticism about an experiment the ACLU conducted using Rekognition to compare headshots of the members of Congress with a database of 25,000 mugshots. The test set Rekognition to make matches with an 80 percent confidence rating, according to Amazon.

President Donald Trump's July 19 executive order establishing the President's National Council for the American Worker is directed at preparing Americans for the workplace of the future. Although short on specifics, the order sends a powerful message about the need for revitalizing educational opportunities if Americans are to thrive in the era of big data, robots and artificial intelligence. The president's intent is to lay the groundwork for tackling a national "skills crisis." His order accepts that Americans need additional skills to fill the current 6.7 million job vacancies. In fact, the executive order gives official imprimatur to what many in industry and academia have feared for some time: "The economy is changing at a rapid pace because of the technology, automation, and artificial intelligence," and existing programs have "prepared Americans for the economy of the past."

Dozens of members of Congress joined forces to request Amazon CEO Jeff Bezos explain the recent "Rekognition" facial recognition flap that misidentified 28 members of Congress as suspected criminals. Bezos does have some questions to answer. It's the least he can do after his artificial intelligence software mistook the faces of more than two dozen lawmakers for mugshots in police files. The American Civil Liberties Union first found the discrepancy; Reps. John Lewis and Tom Garrett, contacted by The Washington Times for response, put out a bipartisan statement, along with Rep. Jimmy Gomez, criticizing the technology. Several other affected members of Congress contacted for comment by The Washington Times failed to respond.

A quiet revolution is taking place. In contrast to much of the press coverage of artificial intelligence, this revolution is not about the ascendance of a sentient android army. Rather, it is characterized by a steady increase in the automation of traditionally human-based decision processes throughout organizations all over the country. While advancements like AlphaGo Zero make for catchy headlines, it is fairly conventional machine learning and statistical techniques -- ordinary least squares, logistic regression, decision trees -- that are adding real value to the bottom line of many organizations. Real-world applications range from medical diagnoses and judicial sentencing to professional recruiting and resource allocation in public agencies. Is this revolution a good thing?

Not content with its impressive(ly creepy) Duplex demo, Google promises it's not wanting to replace call centers with its latest AI demonstration. During the Google Cloud Next 18 conference, Google Chief AI Scientist Dr. Fei-Fei Li demonstrated a new AI system called Google Contact Center AI which – much like Duplex – sounded incredibly natural in its responses to human queries. Google seems to have learned its lesson from its Duplex demonstration and wanted to iterate that it's not designed to replace human operators. Instead, the system could be used to replace the current dreaded automated messages you often hear when dialling a call center. "Press 1 for… press 2 for…" just writing it makes me shudder.