Irina Raicu is the director of the Internet Ethics program at the Markkula Center for Applied Ethics at Santa Clara University. Over in Santa Clara University's Leavey School of Business, professor Sanjiv Das teaches machine learning to graduate students enrolled in the MS of Information Systems program. As the Spring 2017 quarter was about to start, Subramaniam (Subbu) Vincent (the Tech Lead for the center's Trust Project, and an engineer-journalist with experience in data science) suggested that the two of them might collaborate in an effort to introduce the students to some key questions in data analytics: what do fairness and bias look like in the context of machine learning? And, if bias is detected in a dataset or an algorithm, are there ways to minimize or correct for it? In his hands-on, skill-building course, professor Das asked the students to work in small groups as they practiced predictive modeling on data sets--and proposed the fairness questions as one project option. Five of the groups took him up on the offer.

In April, the Chinese AI business SenseTime became the world's most valuable Artificial Intelligence startup, with a valuation of more than $3bn. The company, founded in 2014, is backed by many of the big names in Chinese tech – including Alibaba, who reportedly sought the biggest stake in the business with a $230m investment. Whilst this growth is music to the ears of SenseTime investors, it is also part of a wider drive by in China to become world leaders in AI. With both private business and the government firmly behind this ambition, China is the perfect breeding ground for pushing the boundaries of AI technology. Enduring cultural attitudes towards women, however, give this technological success story a sting in its tail.

Over the past year, there's been a lot of buzz regarding the impact of artificial intelligence on the practice of law. Some maintain it's a lot of hype over nothing, but those very same people likely said the same thing about social media and cloud computing, two technologies that have undeniably shaped our culture and, in turn, the practice of law. Rest assured, the naysayers are once again wrong; artificial intelligence tools will undoubtedly leave their mark on the legal landscape. But don't take my word for it -- there's a new report that backs me up. ALM recently released the report, and it confirms that even though law firms may not be ready, AI is here and it's going to change the way that legal services are delivered.

Amazon's online facial recognition system incorrectly matched pictures of US Congress members to mugshots of suspected criminals in a study by the American Civil Liberties Union. The ACLU, a nonprofit headquartered in New York, has called for Congress to ban cops and Feds from using any sort of computer-powered facial recognition technology due to the fact that, well, it sucks. Amazon's AI-powered Rekognition service was previously criticized by the ACLU when it revealed the web giant was aggressively marketing its face-matching tech to police in Washington County, Oregon, and Orlando, Florida. Rekognition is touted by the Bezos Bunch as, among other applications, a way to identify people in real time from surveillance camera footage or from officers' body cameras. The results from the ACLU's latest probing showed that Rekognition mistook images of 28 members of Congress for mugshots of cuffed people suspected of crimes.

Sky is ditching the humble remote control thanks to an experimental new feature that will see Sky Q owners able to control their television using only their voice. The firm is developing technology that allows viewers to bark orders to switch channels, record live TV and even look-up shows featuring their favourite actors. Sky has confirmed plans to start trialling the experimental feature, which it describes as'hands-free TV', later this year. It is not yet clear whether the technology will come loaded onto a new set-top box, or as a downloadable update to existing hardware. Sky is asking viewers to ditch the TV remote.

Amazon's facial recognition technology falsely identified 28 members of Congress as people who have been arrested for crimes, according to the American Civil Liberties Union (ACLU). The ACLU of Northern California's test of Amazon's controversial Rekognition software also found that people of color were disproportionately misidentified in a mugshot database, raising new concerns about racial bias and the potential for abuse by law enforcement. The report followed revelations in May that Amazon has been marketing and selling the Rekognition technology to police agencies, leading privacy advocates to urge CEO Jeff Bezos to stop providing the product to the government. "Our test reinforces that face surveillance is not safe for government use," Jacob Snow, a technology and civil liberties attorney at the ACLU Foundation of Northern California, said in a statement. "Face surveillance will be used to power discriminatory surveillance and policing that targets communities of color, immigrants, and activists. Once unleashed, that damage can't be undone."

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. The ACLU released a report on Thursday revealing that Rekognition, Amazon's facial recognition tool, had falsely matched 28 members of Congress to mug shots. Members of the ACLU purchased the version of Rekognition that Amazon offers to the general public and ran public photos of every member of the House and Senate against a database of 25,000 arrest photos. The entire experiment costed $12.33, which, as ACLU attorney Jake Snow writes in a blogpost, is "less than a large pizza." Almost 40 percent of the representatives that Rekognition falsely matched were people of color, even though they make up only 20 percent of Congress.

Jack Shepherd had a polished seduction routine. He would take women out for expensive meals and thrilling rides on his speedboat. But one night his fixation on trying to impress went horribly wrong when he killed his date, Charlotte Brown. Shepherd met Charlotte - or Charli, as she was known - for the first time on a December night in 2015. Before that, they'd got to know each other online through the dating website OkCupid.

The ACLU put Amazon's Rekognition facial scanning software to the test and the results were more than a little troubling. Comparing "every current member of the House and Senate" against a database of 25,000 publicly available mugshots, Amazon's software identified 28 lawmakers as folks who'd been arrested for a crime. Given what we've seen about facial recognition's shortcomings, especially in regards to people of color, the following might not be all that surprising: The false matches included six members of the Congressional Black Caucus. "Nearly 40 percent of Rekognition's false matches were of people of color, even though they make up only 20 percent of Congress," according to the ACLU. We've already seen how the public has reacted to Amazon's face-scanning tech.

Amazon's facial recognition tool, Rekognition, wrongly identified 28 members of Congress as police suspects during a test conducted by the American Civil Liberties Union, the organization said Thursday. Amazon issued a statement saying the company objects to the level of accuracy settings used in its face ID tool during the test. ACLU officials maintain that the findings still highlight the risks that individuals could face if police use the technology in certain ways to catch criminals. Since May, the ACLU and other civil rights groups have pressured Amazon to stop selling governments access to the powerful image ID software, which was unveiled in 2016 by the company's cloud-computing division and has since been marketed to web developers. The groups cited use of Rekognition by law enforcement in Oregon and Florida and warned that the tool could be used to target immigrants and people of color unfairly.