Group items matching

in title, tags, annotations or url

In the plethora of copyright lawsuits against artificial intelligence developers, a pair of complaints filed on Wednesday against OpenAI and related defendants stands out.Unlike most of the authors, artists and news organizations that have sued AI developers, The Intercept Media, opens new tab and Raw Story Media, opens new tab are not alleging straightforward copyright infringement claims. The media companies are instead asserting only that OpenAI and its co-defendants violated the Digital Millennium Copyright Act, or DMCA, deliberately undermining their copyrights by stripping identifying information out of articles used to train the AI system behind the popular chatbot ChatGPT.As my Reuters colleague Blake Brittain reported on Wednesday, the 1998 federal DMCA statute prohibits the removal of information that can help copyright holders detect infringement, including article titles, author names and copyright dates.

“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.

Eric Schmidt, the Executive Chairman of Google’s parent company Alphabet, says the company will “engineer” specific algorithms for RT and Sputnik to make their articles less prominent on the search engine’s news delivery services. “We are working on detecting and de-ranking those kinds of sites – it’s basically RT and Sputnik,” Schmidt said during a Q & A session at the Halifax International Security Forum in Canada on Saturday, when asked about whether Google facilitates “Russian propaganda.”

“We are well of aware of it, and we are trying to engineer the systems to prevent that [the content being delivered to wide audiences]. But we don’t want to ban the sites – that’s not how we operate.”The discussion focused on the company’s popular Google News service, which clusters the news by stories, then ranks the various media outlets depending on their reach, article length and veracity, and Google Alerts, which proactively informs subscribers of new publications.

The Alphabet chief, who has been referred to by Hillary Clinton as a “longtime friend,” added that the experience of “the last year” showed that audiences could not be trusted to distinguish fake and real news for themselves.“We started with the default American view that ‘bad’ speech would be replaced with ‘good’ speech, but the problem found in the last year is that this may not be true in certain situations, especially when you have a well-funded opponent who is trying to actively spread this information,” he told the audience.

In its seventh CIA leak since March 23rd, WikiLeaks has just revealed the user manual of a CIA hacking tool known as ‘Archimedes’ which is purportedly used to attack computers inside a Local Area Network (LAN).  The CIA tool works by redirecting a target’s The CIA tool works by redirecting a target’s web page search to a CIA server which serves up a web page that looks exactly like the original page they were expecting to be served, but which contains malware. It’s only possible to detect the attack by examining the page source.

This week the Center for Media Justice, ColorOfChange.org, and New America’s Open Technology Institute filed a complaint with the Federal Communications Commission alleging the Baltimore police are violating the federal Communications Act by using cell site simulators, also known as Stingrays, that disrupt cellphone calls and interfere with the cellular network—and are doing so in a way that has a disproportionate impact on communities of color. Stingrays operate by mimicking a cell tower and directing all cellphones in a given area to route communications through the Stingray instead of the nearby tower. They are especially pernicious surveillance tools because they collect information on every single phone in a given area—not just the suspect’s phone—this means they allow the police to conduct indiscriminate, dragnet searches. They are also able to locate people inside traditionally-protected private spaces like homes, doctors’ offices, or places of worship. Stingrays can also be configured to capture the content of communications. Because Stingrays operate on the same spectrum as cellular networks but are not actually transmitting communications the way a cell tower would, they interfere with cell phone communications within as much as a 500 meter radius of the device (Baltimore’s devices may be limited to 200 meters). This means that any important phone call placed or text message sent within that radius may not get through. As the complaint notes, “[d]epending on the nature of an emergency, it may be urgently necessary for a caller to reach, for example, a parent or child, doctor, psychiatrist, school, hospital, poison control center, or suicide prevention hotline.” But these and even 911 calls could be blocked.

The Baltimore Police Department could be among the most prolific users of cell site simulator technology in the country. A Baltimore detective testified last year that the BPD used Stingrays 4,300 times between 2007 and 2015. Like other law enforcement agencies, Baltimore has used its devices for major and minor crimes—everything from trying to locate a man who had kidnapped two small children to trying to find another man who took his wife’s cellphone during an argument (and later returned it). According to logs obtained by USA Today, the Baltimore PD also used its Stingrays to locate witnesses, to investigate unarmed robberies, and for mysterious “other” purposes. And like other law enforcement agencies, the Baltimore PD has regularly withheld information about Stingrays from defense attorneys, judges, and the public. Moreover, according to the FCC complaint, the Baltimore PD’s use of Stingrays disproportionately impacts African American communities. Coming on the heels of a scathing Department of Justice report finding “BPD engages in a pattern or practice of conduct that violates the Constitution or federal law,” this may not be surprising, but it still should be shocking. The DOJ’s investigation found that BPD not only regularly makes unconstitutional stops and arrests and uses excessive force within African-American communities but also retaliates against people for constitutionally protected expression, and uses enforcement strategies that produce “severe and unjustified disparities in the rates of stops, searches and arrests of African Americans.”

Adding Stingrays to this mix means that these same communities are subject to more surveillance that chills speech and are less able to make 911 and other emergency calls than communities where the police aren’t regularly using Stingrays. A map included in the FCC complaint shows exactly how this is impacting Baltimore’s African-American communities. It plots hundreds of addresses where USA Today discovered BPD was using Stingrays over a map of Baltimore’s black population based on 2010 Census data included in the DOJ’s recent report:

On the 21st floor of a high-rise hotel in Cleveland, in a room full of political operatives, Microsoft’s Research Division was advertising a technology that could read each facial expression in a massive crowd, analyze the emotions, and report back in real time. “You could use this at a Trump rally,” a sales representative told me. At both the Republican and Democratic conventions, Microsoft sponsored event spaces for the news outlet Politico. Politico, in turn, hosted a series of Microsoft-sponsored discussions about the use of data technology in political campaigns. And throughout Politico’s spaces in both Philadelphia and Cleveland, Microsoft advertised an array of products from “Microsoft Cognitive Services,” its artificial intelligence and cloud computing division. At one exhibit, titled “Realtime Crowd Insights,” a small camera scanned the room, while a monitor displayed the captured image. Every five seconds, a new image would appear with data annotated for each face — an assigned serial number, gender, estimated age, and any emotions detected in the facial expression. When I approached, the machine labeled me “b2ff” and correctly identified me as a 23-year-old male.

“Realtime Crowd Insights” is an Application Programming Interface (API), or a software tool that connects web applications to Microsoft’s cloud computing services. Through Microsoft’s emotional analysis API — a component of Realtime Crowd Insights — applications send an image to Microsoft’s servers. Microsoft’s servers then analyze the faces and return emotional profiles for each one. In a November blog post, Microsoft said that the emotional analysis could detect “anger, contempt, fear, disgust, happiness, neutral, sadness or surprise.” Microsoft’s sales representatives told me that political campaigns could use the technology to measure the emotional impact of different talking points — and political scientists could use it to study crowd response at rallies.

Facial recognition technology — the identification of faces by name — is already widely used in secret by law enforcement, sports stadiums, retail stores, and even churches, despite being of questionable legality. As early as 2002, facial recognition technology was used at the Super Bowl to cross-reference the 100,000 attendees to a database of the faces of known criminals. The technology is controversial enough that in 2013, Google tried to ban the use of facial recognition apps in its Google glass system. But “Realtime Crowd Insights” is not true facial recognition — it could not identify me by name, only as “b2ff.” It did, however, store enough data on each face that it could continuously identify it with the same serial number, even hours later. The display demonstrated that capability by distinguishing between the number of total faces it had seen, and the number of unique serial numbers. Photo: Alex Emmons

One system builds profiles showing people’s web browsing histories. Another analyzes instant messenger communications, emails, Skype calls, text messages, cell phone locations, and social media interactions. Separate programs were built to keep tabs on “suspicious” Google searches and usage of Google Maps. The surveillance is underpinned by an opaque legal regime that has authorized GCHQ to sift through huge archives of metadata about the private phone calls, emails and Internet browsing logs of Brits, Americans, and any other citizens  all without a court order or judicial warrant.

The power of KARMA POLICE was illustrated in 2009, when GCHQ launched a top-secret operation to collect intelligence about people using the Internet to listen to radio shows. The agency used a sample of nearly 7 million metadata records, gathered over a period of three months, to observe the listening habits of more than 200,000 people across 185 countries, including the U.S., the U.K., Ireland, Canada, Mexico, Spain, the Netherlands, France, and Germany.

GCHQ’s documents indicate that the plans for KARMA POLICE were drawn up between 2007 and 2008. The system was designed to provide the agency with “either (a) a web browsing profile for every visible user on the Internet, or (b) a user profile for every visible website on the Internet.” The origin of the surveillance system’s name is not discussed in the documents. But KARMA POLICE is also the name of a popular song released in 1997 by the Grammy Award-winning British band Radiohead, suggesting the spies may have been fans. A verse repeated throughout the hit song includes the lyric, “This is what you’ll get, when you mess with us.”

HERE WAS A SIMPLE AIM at the heart of the top-secret program: Record the website browsing habits of “every visible user on the Internet.” Before long, billions of digital records about ordinary people’s online activities were being stored every day. Among them were details cataloging visits to porn, social media and news websites, search engines, chat forums, and blogs. The mass surveillance operation — code-named KARMA POLICE — was launched by British spies about seven years ago without any public debate or scrutiny. It was just one part of a giant global Internet spying apparatus built by the United Kingdom’s electronic eavesdropping agency, Government Communications Headquarters, or GCHQ. The revelations about the scope of the British agency’s surveillance are contained in documents obtained by The Intercept from National Security Agency whistleblower Edward Snowden. Previous reports based on the leaked files have exposed how GCHQ taps into Internet cables to monitor communications on a vast scale, but many details about what happens to the data after it has been vacuumed up have remained unclear.

Amid a renewed push from the U.K. government for more surveillance powers, more than two dozen documents being disclosed today by The Intercept reveal for the first time several major strands of GCHQ’s existing electronic eavesdropping capabilities.

The surveillance is underpinned by an opaque legal regime that has authorized GCHQ to sift through huge archives of metadata about the private phone calls, emails and Internet browsing logs of Brits, Americans, and any other citizens — all without a court order or judicial warrant