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Lawmakers in the United States and the United Kingdom are calling on Facebook chief executive Mark Zuckerberg to explain how the names, preferences and other information from tens of millions of users ended up in the hands of the Cambridge Analytica data analysis firm.

After Facebook cited data privacy policies violations and announced that it was suspending the Cambridge Analytica data analytics firm also tied to the Trump campaign, new revelations have emerged. On Saturday, reports revealed that Cambridge Analytica, used a feature once available to Facebook app developers to collect information on some 270,000 people. In the process, the company, which was, at the time, handling U.S. President Donald Trump’s presidential campaign, gained access to data on tens of millions of their Facebook “friends” and that it wasn’t clear at all if any of these people had given explicit permission for this kind of sharing. Facebook’s Deputy General Counsel Paul Grewal said in a statement, “We will take legal action if necessary to hold them responsible and accountable for any unlawful behavior.”

The social media giant also added that it was continuing to investigate the claims. According to reports, Cambridge Analytica worked for the failed presidential campaign of U.S. Senator Ted Cruz and then for the presidential campaign of Donald Trump. Federal Election Commission records reportedly show that Trump’s campaign hired Cambridge Analytica in June 2016 and paid it more than $6.2 million. On its website, the company says that it “provided the Donald J. Trump for President campaign with the expertise and insights that helped win the White House.” Cambridge Analytica also mentions that it uses “behavioral microtargeting,” or combining analysis of people’s personalities with demographics, to predict and influence mass behavior.  According to the company, it has data on 220 million Americans, two thirds of the U.S. population. Cambridge Analytica says it has worked on other campaigns in the United States and other countries, and it is funded by Robert Mercer, a prominent supporter of politically conservative groups.

Imagine if someone could scan every image on Facebook, Twitter, and Instagram, then instantly determine where each was taken. The ability to combine this location data with information about who appears in those photos—and any social media contacts tied to them—would make it possible for government agencies to quickly track terrorist groups posting propaganda photos. (And, really, just about anyone else.) That's precisely the goal of Finder, a research program of the Intelligence Advanced Research Projects Agency (IARPA), the Office of the Director of National Intelligence's dedicated research organization. For many photos taken with smartphones (and with some consumer cameras), geolocation information is saved with the image by default. The location is stored in the Exif (Exchangable Image File Format) data of the photo itself unless geolocation services are turned off. If you have used Apple's iCloud photo store or Google Photos, you've probably created a rich map of your pattern of life through geotagged metadata. However, this location data is pruned off for privacy reasons when images are uploaded to some social media services, and privacy-conscious photographers (particularly those concerned about potential drone strikes) will purposely disable geotagging on their devices and social media accounts.

“We are truly fucked.” That was Motherboard’s spot-on reaction to deep fake sex videos (realistic-looking videos that swap a person’s face into sex scenes actually involving other people). And that sleazy application is just the tip of the iceberg. As Julian Sanchez tweeted, “The prospect of any Internet rando being able to swap anyone’s face into porn is incredibly creepy. But my first thought is that we have not even scratched the surface of how bad ‘fake news’ is going to get.” Indeed. Recent events amply demonstrate that false claims—even preposterous ones—can be peddled with unprecedented success today thanks to a combination of social media ubiquity and virality, cognitive biases, filter bubbles, and group polarization. The resulting harms are significant for individuals, businesses, and democracy. Belated recognition of the problem has spurred a variety of efforts to address this most recent illustration of truth decay, and at first blush there seems to be reason for optimism. Alas, the problem may soon take a significant turn for the worse thanks to deep fakes. Get used to hearing that phrase. It refers to digital manipulation of sound, images, or video to impersonate someone or make it appear that a person did something—and to do so in a manner that is increasingly realistic, to the point that the unaided observer cannot detect the fake. Think of it as a destructive variation of the Turing test: imitation designed to mislead and deceive rather than to emulate and iterate.

Fueled by artificial intelligence, digital impersonation is on the rise. Machine-learning algorithms (often neural networks) combined with facial-mapping software enable the cheap and easy fabrication of content that hijacks one’s identity—voice, face, body. Deep fake technology inserts individuals’ faces into videos without their permission. The result is “believable videos of people doing and saying things they never did.” Not surprisingly, this concept has been quickly leveraged to sleazy ends. The latest craze is fake sex videos featuring celebrities like Gal Gadot and Emma Watson. Although the sex scenes look realistic, they are not consensual cyber porn. Conscripting individuals (more often women) into fake porn undermines their agency, reduces them to sexual objects, engenders feeling of embarrassment and shame, and inflicts reputational harm that can devastate careers (especially for everyday people). Regrettably, cyber stalkers are sure to use fake sex videos to torment victims. What comes next? We can expect to see deep fakes used in other abusive, individually-targeted ways, such as undermining a rival’s relationship with fake evidence of an affair or an enemy’s career with fake evidence of a racist comment.

What they are doing could be seen as the online world’s equivalent of punk rock: a scattered revolt against an industry that many now think has grown greedy, intrusive and arrogant – as well as governments whose surveillance programmes have fuelled the same anxieties. As concerns grow about an online realm dominated by a few huge corporations, everyone involved shares one common goal: a comprehensively decentralised internet.

In the last few months, they have started working with people in the Belgian city of Ghent – or, in Flemish, Gent – where the authorities own their own internet domain, complete with .gent web addresses. Using the blueprint of Heartbeat, they want to create a new kind of internet they call the indienet – in which people control their data, are not tracked and each own an equal space online. This would be a radical alternative to what we have now: giant “supernodes” that have made a few men in northern California unimaginable amounts of money thanks to the ocean of lucrative personal information billions of people hand over in exchange for their services.

His alternative is what he calls the Safe network: the acronym stands for “Safe Access for Everyone”. In this model, rather than being stored on distant servers, people’s data – files, documents, social-media interactions – will be broken into fragments, encrypted and scattered around other people’s computers and smartphones, meaning that hacking and data theft will become impossible. Thanks to a system of self-authentication in which a Safe user’s encrypted information would only be put back together and unlocked on their own devices, there will be no centrally held passwords. No one will leave data trails, so there will be nothing for big online companies to harvest. The financial lubricant, Irvine says, will be a cryptocurrency called Safecoin: users will pay to store data on the network, and also be rewarded for storing other people’s (encrypted) information on their devices. Software developers, meanwhile, will be rewarded with Safecoin according to the popularity of their apps. There is a community of around 7,000 interested people already working on services that will work on the Safe network, including alternatives to platforms such as Facebook and YouTube.

These and other classified documents provided by former NSA contractor Edward Snowden reveal that the NSA has developed technology not just to record and transcribe private conversations but to automatically identify the speakers. Americans most regularly encounter this technology, known as speaker recognition, or speaker identification, when they wake up Amazon’s Alexa or call their bank. But a decade before voice commands like “Hello Siri” and “OK Google” became common household phrases, the NSA was using speaker recognition to monitor terrorists, politicians, drug lords, spies, and even agency employees. The technology works by analyzing the physical and behavioral features that make each person’s voice distinctive, such as the pitch, shape of the mouth, and length of the larynx. An algorithm then creates a dynamic computer model of the individual’s vocal characteristics. This is what’s popularly referred to as a “voiceprint.” The entire process — capturing a few spoken words, turning those words into a voiceprint, and comparing that representation to other “voiceprints” already stored in the database — can happen almost instantaneously. Although the NSA is known to rely on finger and face prints to identify targets, voiceprints, according to a 2008 agency document, are “where NSA reigns supreme.” It’s not difficult to see why. By intercepting and recording millions of overseas telephone conversations, video teleconferences, and internet calls — in addition to capturing, with or without warrants, the domestic conversations of Americans — the NSA has built an unrivaled collection of distinct voices. Documents from the Snowden archive reveal that analysts fed some of these recordings to speaker recognition algorithms that could connect individuals to their past utterances, even when they had used unknown phone numbers, secret code words, or multiple languages.

The classified documents, dating from 2004 to 2012, show the NSA refining increasingly sophisticated iterations of its speaker recognition technology. They confirm the uses of speaker recognition in counterterrorism operations and overseas drug busts. And they suggest that the agency planned to deploy the technology not just to retroactively identify spies like Pelton but to prevent whistleblowers like Snowden.

One of the few positive things in the ill-named USA FREEDOM Act, enacted in 2015 after the Snowden revelations on NSA domestic spying, is that it required the Director of National Intelligence to regularly report on its domestic surveillance activities. On Friday, the latest report was released on just how much our own government is spying on us. The news is not good at all if you value freedom over tyranny.According to the annual report, named the Statistical Transparency Report Regarding Use of National Security Authorities, the US government intercepted and stored information from more than a half-billion of our telephone calls and text messages in 2017. That is a 300 percent increase from 2016. All of these intercepts were “legal” under the Foreign Intelligence Surveillance Act (FISA), which is ironic because FISA was enacted to curtail the Nixon-era abuse of surveillance on American citizens.Has the US government intercepted your phone calls and/or text messages? You don’t know, which is why the surveillance state is so evil. Instead of assuming your privacy is protected by the US Constitution, you must assume that the US government is listening in to your communications. The difference between these is the difference between freedom and tyranny. The ultimate triumph of totalitarian states was not to punish citizens for opposing its tyranny, but to successfully cause them to censor themselves before even expressing “subversive” thoughts.

Mark Zuckerberg faces allegations that he developed a “malicious and fraudulent scheme” to exploit vast amounts of private data to earn Facebook billions and force rivals out of business. A company suing Facebook in a California court claims the social network’s chief executive “weaponised” the ability to access data from any user’s network of friends – the feature at the heart of the Cambridge Analytica scandal. A legal motion filed last week in the superior court of San Mateo draws upon extensive confidential emails and messages between Facebook senior executives including Mark Zuckerberg. He is named individually in the case and, it is claimed, had personal oversight of the scheme. Facebook rejects all claims, and has made a motion to have the case dismissed using a free speech defence.

It claims the first amendment protects its right to make “editorial decisions” as it sees fit. Zuckerberg and other senior executives have asserted that Facebook is a platform not a publisher, most recently in testimony to Congress.

Heather Whitney, a legal scholar who has written about social media companies for the Knight First Amendment Institute at Columbia University, said, in her opinion, this exposed a potential tension for Facebook. “Facebook’s claims in court that it is an editor for first amendment purposes and thus free to censor and alter the content available on its site is in tension with their, especially recent, claims before the public and US Congress to be neutral platforms.” The company that has filed the case, a former startup called Six4Three, is now trying to stop Facebook from having the case thrown out and has submitted legal arguments that draw on thousands of emails, the details of which are currently redacted. Facebook has until next Tuesday to file a motion requesting that the evidence remains sealed, otherwise the documents will be made public.

Today we are releasing the implementation guide for EFF’s Do Not Track (DNT) policy. For years users have been able to set a Do Not Track signal in their browser, but there has been little guidance for websites as to how to honor that request. EFF’s DNT policy sets out a meaningful response for servers to follow, and this guide provides details about how to apply it in practice. At its core, DNT protects user privacy by excluding the use of unique identifiers for cross-site tracking, and by limiting the retention period of log data to ten days. This short retention period gives sites the time they need for debugging and security purposes, and to generate aggregate statistical data. From this baseline, the policy then allows exceptions when the user's interactions with the site—e.g., to post comments, make a purchase, or click on an ad—necessitates collecting more information. The site is then free to retain any data necessary to complete the transaction. We believe this approach balances users’ privacy expectations with the ability of websites to deliver the functionality users want. Websites often integrate third-party content and rely on third-party services (like content delivery networks or analytics), and this creates the potential for user data to be leaked despite the best intentions of the site operator. The guide identifies potential pitfalls and catalogs providers of compliant services. It is common, for example, to embed media from platforms like You Tube, Sound Cloud, and Twitter, all of which track users whenever their widgets are loaded. Fortunately, Embedly, which offers control over the appearance of embeds, also supports DNT via its API, displaying a poster instead and loading the widget only if the user clicks on it knowingly.

Knowledge makes the difference between willing tracking and non-consensual tracking. Users should be able to choose whether they want to give up their privacy in exchange for using a site or a  particular feature. This means sites need to be transparent about their practices. A great example of this is our biggest adopter, Medium, which does not track DNT users who browse the site and gives clear information about tracking to users when they choose to log in. This is their previous log-in panel, the DNT language is currently being added to their new interface.

A judge has approved a settlement valued at $650 million from Facebook to end a privacy lawsuit, one which alleged the social network used facial recognition technology on user photos stored on its iPhone app without permission. The lawsuit, which started in April 2015, alleged Facebook did not gain consent from users to use its facial tagging features on their photographs. Originally filed by Chicago attorney Jay Edelson on behalf of plaintiff Carlo Licata, the complaint claimed the consent-less tagging was not allowed under privacy laws in Illinois. The case originated in Cook County Circuit Court before moving to Chicago federal court then California, reports the Chicago Tribune. On reaching California, the lawsuit attained class-action status. The class in question constitutes approximately 6.9 million Facebook users in Illinois that Facebook created and stored a face template for after June 7, 2011. Close to 1.6 million claim forms were filed ahead of the November 23 deadline for joining, making up roughly 22% of potential class members. Facebook went against the Illinois Biometric Information Privacy Act, the complaint alleged, which is among the toughest privacy laws in the United States. Part of the act requires companies to gain permission from users before being able to start using biometric systems with their data, which includes facial recognition systems.

Google cuts Huawei off Android; so Huawei may migrate to Aurora. Call it mobile Eurasia integration; the evolving Russia-China strategic partnership may be on the verge of spawning its own operating system – and that is not a metaphor. Aurora is a mobile operating system currently developed by Russian Open Mobile Platform, based in Moscow. It is based on the Sailfish operating system, designed by Finnish technology company Jolla, which featured a batch of Russians in the development team. Quite a few top coders at Google and Apple also come from the former USSR – exponents of a brilliant scientific academy tradition.

No Google? Who cares? Tencent, Xiaomi, Vivo and Oppo are already testing the HongMeng operating system, as part of a batch of one million devices already distributed. HongMeng’s launch is still a closely guarded secret by Huawei, but according to CEO Richard Yu, it could happen even before the end of 2019 for the Chinese market, running on smartphones, computers, TVs and cars. HongMeng is rumored to be 60% faster than Android.

Aurora could be regarded as part of Huawei’s fast-evolving Plan B. Huawei is now turbo-charging the development and implementation of its own operating system, HongMeng, a process that started no less than seven years ago. Most of the work on an operating system is writing drivers and APIs (application programming interfaces). Huawei would be able to integrate their code to the Russian system in no time.