What I saw didn't look very much like the future -- or at least the automated one you might imagine. The offices could have been call centers or payment processing centers. One was a timeworn former apartment building in the middle of a low-income residential neighborhood in western Kolkata that teemed with pedestrians, auto rickshaws and street vendors. In facilities like the one I visited in Bhubaneswar and in other cities in India, China, Nepal, the Philippines, East Africa and the United States, tens of thousands of office workers are punching a clock while they teach the machines. Tens of thousands more workers, independent contractors usually working in their homes, also annotate data through crowdsourcing services like Amazon Mechanical Turk, which lets anyone distribute digital tasks to independent workers in the United States and other countries.
On paper, it's a great time to be on a dating app. In the seven years since Tinder's entrance on to the dating scene in 2012, it has gone from fringe novelty to romantic ubiquity; within two years of launching, it was seeing 1bn swipes a day. Other apps have similarly impressive stats: in 2018, Bumble's global brand director revealed it had more than 26 million users and a confirmed 20,000 marriages. It's a far cry from the considerably less optimistic response Tinder received when it launched. Many hailed it as the end of romance itself.
The 9th Circuit U.S. Court of Appeals said Thursday that Facebook users in Illinois can sue the company over its use of facial recognition technology. The 9th Circuit U.S. Court of Appeals said Thursday that Facebook users in Illinois can sue the company over its use of facial recognition technology. A U.S. court has ruled that Facebook users in Illinois can sue the company over face recognition technology, meaning a class action can move forward. The 9th Circuit U.S. Court of Appeals issued its ruling on Thursday. According to the American Civil Liberties Union, it's the first decision by a U.S. appellate court to directly address privacy concerns posed by facial recognition technology.
Somewhat unceremoniously, Facebook this week provided an update on its brain-computer interface project, preliminary plans for which it unveiled at its F8 developer conference in 2017. In a paper published in the journal Nature Communications, a team of scientists at the University of California, San Francisco backed by Facebook Reality Labs -- Facebook's Pittsburgh-based division devoted to augmented reality and virtual reality R&D -- described a prototypical system capable of reading and decoding study subjects' brain activity while they speak. It's impressive no matter how you slice it: The researchers managed to make out full, spoken words and phrases in real time. Study participants (who were prepping for epilepsy surgery) had a patch of electrodes placed on the surface of their brains, which employed a technique called electrocorticography (ECoG) -- the direct recording of electrical potentials associated with activity from the cerebral cortex -- to derive rich insights. A set of machine learning algorithms equipped with phonological speech models learned to decode specific speech sounds from the data and to distinguish between questions and responses.
With a new feature, Tinder says it wants to make the swiping experience safer for its LGBTQ users traveling and living in certain countries. On Wednesday, the dating app introduced a new safety update dubbed "Traveler Alert" that will warn users who have identified themselves as lesbian, gay, bisexual, transgender and/or queer when they enter a country that could criminalize them for being out. The app plans to use the locations from users' devices to determine if there is a threat to the user's safety, where users can opt to have their profile hidden during their stay or make their profile public again. The caveat being that if a user decides to have their profile public, their sexual preference or gender identity will no longer be disclosed on the app until they return to a location where the user is deemed safer to disclose their identity. In the statement, Tinder says they developed the feature so that users "can take extra caution and do not unknowingly place themselves in danger for simply being themselves."
Dozens of databases of people's faces are being compiled without their knowledge by companies and researchers, with many of the images then being shared around the world, in what has become a vast ecosystem fueling the spread of facial recognition technology. The databases are pulled together with images from social networks, photo websites, dating services like OkCupid and cameras placed in restaurants and on college quads. While there is no precise count of the data sets, privacy activists have pinpointed repositories that were built by Microsoft, Stanford University and others, with one holding over 10 million images while another had more than two million. The face compilations are being driven by the race to create leading-edge facial recognition systems. This technology learns how to identify people by analyzing as many digital pictures as possible using "neural networks," which are complex mathematical systems that require vast amounts of data to build pattern recognition.
What do Russian trolls, Facebook, and US elections have to do with machine learning? Recommendation engines are at the heart of the central feedback loop of social networks and the user-generated content (UGC) they create. Users join the network and are recommended users and content with which to engage. Recommendation engines can be gamed because they amplify the effects of thought bubbles. The 2016 US presidential election showed how important it is to understand how recommendation engines work and the limitations and strengths they offer.
Summer romance is in the air and the special someone you just met at an online dating site or on social media seems too good to be true. The sad truth is the person just might turn out to be. In fact, your would-be dreamboat could be a "catfisher." Some states have a higher risk than others, it seems. HighSpeedInternet.com has issued a new report "When Love Bites," in which the internet service provider comparison website identified the states where you are most likely to fall prey to these scammers.
Twitter has just announced it has picked up London-based Fabula AI. The deep learning startup has been developing technology to try to identify online disinformation by looking at patterns in how fake stuff vs genuine news spreads online -- making it an obvious fit for the rumor-riled social network. Social media giants remain under increasing political pressure to get a handle on online disinformation to ensure that manipulative messages don't, for example, get a free pass to fiddle with democratic processes. Twitter says the acquisition of Fabula will help it build out its internal machine learning capabilities -- writing that the UK startup's "world-class team of machine learning researchers" will feed an internal research group it's building out, led by Sandeep Pandey, its head of ML/AI engineering. This research group will focus on "a few key strategic areas such as natural language processing, reinforcement learning, ML ethics, recommendation systems, and graph deep learning" -- now with Fabula co-founder and chief scientist, Michael Bronstein, as a leading light within it.
Walt Disney World recently showed the Associated Press what it takes to put their shows together. It's a shift for a resort that hasn't allowed many peeks behind the curtains of the fantasy it creates. Maybe romantic Disney fairy tales come true after all. Data from the popular global online dating site Plenty of Fish reveals that singles who have expressed an interest in Disney are 3.6 times more likely to leave the app in a relationship compared to singles who more generally list interests in music and movies. That was certainly true for Disney fan Abby Schiller.