Ice Lounge Media

Ice Lounge Media

The long-awaited tech antitrust report that the US Congress released on October 6 presents a remarkably flimsy case for action against the nation’s most innovative and competitive companies.

The report’s main recommendations would do very little to solve real social problems caused by technology, like misinformation and election interference, because these problems aren’t related to competition. And by narrowing its focus to the technology sector, the House Antitrust Subcommittee missed an opportunity to look at parts of the economy—hospitals, insurance providers, food producers—where consolidation and competition are genuine concerns.

In the 451-page report (pdf), more than a year in the making, legislators attempted to answer a seemingly straightforward question: Are Amazon, Apple, Facebook, and Google engaging in anticompetitive practices that government agencies aren’t able to punish under current laws? And if so, what changes should Congress make?

While the report describes a few genuine cases of unfair conduct by the platforms, many of the “problems” it identifies are merely complaints from companies that have been outcompeted. But harming competitors to benefit consumers (by lowering prices, for example) is the very nature of competition.

Most important, the report does not contradict these key facts about the US tech industry: prices are falling, productivity is rising, new competitors are flourishing, employment is outperforming other sectors, and most Americans really like these companies.

Disappointingly, the much-ballyhooed document is riddled with factual errors. For example, it claims that “a decade into the future, 30% of the world’s gross economic output may lie with [Amazon, Apple, Facebook, and Google] and just a handful of others.” But the source for that statistic, a study by McKinsey, actually said that by 2025 (not 2030), revenues from all digital commerce (not just by the Big Four and a few others) might reach 30% of global revenues.

To put in perspective how misleading the report’s original claim was, consider that the combined annual revenue last year of Amazon, AppleFacebook, and Google represented only about half a percent of global economic output. Such a blatant error is conceivable only in a piece of work that first assumed its conclusion (“Big Tech is taking over the world”) and worked backward from there. There are dozens of other examples like this.

The good

Let’s start with what’s good about the report. It calls for increasing the budgets of the Federal Trade Commission (FTC) and the antitrust division of the Department of Justice, which is long overdue considering that their combined budgets have fallen by 18% (pdf), in real terms, since 2010. If regulators do not have the resources to properly enforce the laws on the books, it’s no wonder that some lawmakers will start calling for changes to those laws.

The report also recommends requiring the FTC to collect more data and report on the state of competition in various sectors. And it says the FTC should conduct retrospectives to study whether its past decisions to approve or block mergers were correct. These kinds of studies are also long overdue and would make enforcement officials better at their jobs.

The FTC is currently engaged in a special review of every acquisition by the Big Five tech companies (those listed above, plus Microsoft) over the last decade. That process should be extended to other sectors and repeated on a regular basis.

Lastly, the report’s proposals for how to increase data portability might work very well for simple forms of data (such as a user’s social graph), which are easier to standardize. If consumers can easily take their data along with them, it will be easier for them to switch to new platforms, giving startups more incentive to enter the market.

The bad

Unfortunately, the report’s primary recommendations would do far more harm than good. The signature proposal is to force dominant platforms to separate their business lines. Chairman David Cicilline, a Rhode Island Democrat, has called this a “Glass-Steagall for the internet,” referring to the 1933 US law (repealed in 1999) that divided commercial from investment banking.

In effect, this proposal would break up tech companies by separating the underlying platform from the products and services sold on it. Google could no longer own Android and offer apps like Gmail, Maps, and Chrome. Amazon could no longer own the Amazon Marketplace and sell its own private-label goods. Apple could no longer own iOS and offer products like Safari, Siri, or Find My iPhone. Facebook could no longer own social-media platforms and use personal data to target ads to users. The upshot is that these moves would destroy tech companies’ carefully constructed ecosystems and make their current business models unviable.

Of course, if this proposal is adopted, there will be many edge cases. Is the iPhone’s flashlight feature part of the operating system or is it more akin to an app? At this point, a flashlight feels like a standard feature of any phone. But not long ago, users had to download third-party apps to achieve that functionality.

As research from Wen Wen and Feng Zhu shows, when an operating system owner like Apple enters a product vertical (such as flashlight apps), third-party developers shift their efforts to other, more difficult-to-replicate app categories. So is adding a flashlight to the OS really anticompetitive behavior from a dominant platform, or is it pro-consumer innovation that leads to better allocation of developers’ time?

The consumer

To justify its proposals, the report would have needed to find a smoking gun (or two). It didn’t. In general, the leading tech companies produce enormous benefits for consumers.

In general, the leading tech companies produce enormous benefits for consumers.

Prices for digital ads have fallen by more than 40% over the last decade, and those savings flow through to consumers in the form of lower prices for goods and services. Prices for books have fallen by more than 40% since Amazon’s IPO in 1997. And Apple’s App Store takes the exact same cut (30%) as other platforms, including PlayStation, Xbox, and Nintendo. In fact, once you account for free apps, effective commission rates in the App Store are in the range of 4% to 7%.

The report’s authors massage the statistics to make tech companies look like monopolies even though they’re not by conventional measures (defined as having greater than two-thirds market share, according to the Department of Justice). They’re all very large businesses, but generally accepted data shows they don’t meet that standard. Amazon has 38% of the e-commerce market. Fewer than half of new smartphones sold in the US are iPhones. In the digital ad market, Google has a 29% share, Facebook has 23%, and Amazon has 10%.

What’s more, consumers themselves say they benefit greatly from the products and services that these companies build. Research in the Proceedings of the National Academy of Sciences has shown that, on average, consumers would need to be paid $17,530 per year to give up search engines, $8,414 per year to give up email, and $3,648 per year to give up digital maps. Meanwhile, the price to access these services is typically zero.

The competition

One of the main themes of the report is that these platforms have become so powerful no new companies dare to challenge them (and no venture capitalists dare to fund potential competitors). Several recent examples belie that notion.

Shopify, which is mentioned only in passing, is a $130 billion e-commerce company that powers more than one million online businesses. The company was founded in 2006, and the stock has risen roughly 1,000% over the last three years. Its most recent earnings report (pdf) showed that total gross merchandise volume on the platform is more than doubling year over year. (By contrast, Amazon’s GMV is growing by about 20% annually.)

To show Facebook’s dominance in the social-media market, the report includes an outdated chart (on page 93) comparing global monthly active users across the leading platforms. The chart puts TikTok at around 300 million monthly active users. But TikTok is a much more formidable competitor to Facebook than the report’s authors seem willing to admit: it recently announced that as of July, it had nearly 700 million monthly active users worldwide. On the same day the report was published, the investment bank Piper Sandler released a study showing that TikTok had surpassed Instagram as US teenagers’ second-favorite social-media app (behind Snapchat).

Zoom is another competitor that’s glossed over in the report. The subscription-based company faced an uphill battle against incumbents such as Google that offer videoconferencing for free (or bundle it with other productivity software). The report notes that in response to Zoom, Google tried to boost its own videoconferencing product, Meet, by introducing a new Meet widget inside Gmail and adding a prompt for Google Calendar users to “Add Google Meet video conferencing” to their appointments.

How have these moves affected Zoom? The company increased its number of daily meeting participants from 10 million in December 2019 to 300 million in April 2020, and its stock is now seven times higher than it was last year (reaching a market valuation of almost $140 billion).

Those aren’t just a few outliers. As Scott Kupor, a venture capitalist at Andreessen Horowitz, pointed out, startups have been booming over the last 15 years in the US. According to data (pdf) from PitchBook, the total annual number of VC deals increased from 3,390 to 12,211 between 2006 and 2019. Deal value increased from $29.4 billion to $135.8 billion. The number of deals at the earliest stage of investment—angel and seed rounds—rose by about a factor of 10 over the same time period (to 5,107 deals worth $10 billion in total value in 2019).

What’s next?

Granted, all the data presented here doesn’t rule out future antitrust cases against the tech companies. The Justice Department and some state attorneys general plan to launch an antitrust case against Google in the coming weeks. The FTC is likely to file suit against Facebook before the end of the year.

If those cases go to court, more sophisticated economic modeling based on non-public data might show that prices would have fallen even faster—or there would have been an even bigger startup boom—had the tech giants in question not been so dominant. But such an outcome would only prove that even if these companies really do harm competition, we don’t need major changes to our antitrust laws to hold them accountable.

To be sure, the scale and scope of tech platforms have created novel problems that our society needs to address, including issues related to privacy, misinformation, radicalization, counterfeit goods, child pornography, the decline of local news, and foreign interference in our elections. But instead of wasting taxpayer resources on a misguided crusade to break up our most innovative companies, Congress should consider passing measures like these:

  • Comprehensive federal privacy legislation that addresses the gaps in our current sector-based approach (and avoids the pitfalls of the EU’s General Data Protection Regulation and California’s Consumer Privacy Act).
  • Sunshine laws like the Honest Ads Act that help prevent foreign interference in future elections and make digital political ads more transparent.
  • Reform for the intellectual-property dispute process to reduce the prevalence of counterfeit goods online and prevent tech giants from copying genuinely innovative products.
  • Direct subsidies for the provision of local news, funded via broad-based taxes.

Unfortunately, changing our antitrust laws as the House Judiciary Committee recommends would fix none of the social issues caused by Big Tech. Each problem needs a targeted regulatory solution, not the big stick approach of “break them up.”

Alec Stapp is the director of technology policy at the Progressive Policy Institute, a center-left think tank based in Washington, DC.

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In a national database in Argentina, tens of thousands of entries detail the names, birthdays, and national IDs of people suspected of crimes. The database, known as the Consulta Nacional de Rebeldías y Capturas (National Register of Fugitives and Arrests), or CONARC, began in 2009 as a part of an effort to improve law enforcement for serious crimes.

But there are several things off about CONARC. For one, it’s a plain-text spreadsheet file without password protection, which can be readily found via Google Search and downloaded by anyone. For another, many of the alleged crimes, like petty theft, are not that serious—while others aren’t specified at all.

Most alarming, however, is the age of the youngest alleged offender, identified only as M.G., who is cited for “crimes against persons (malicious)—serious injuries.” M.G. was apparently born on October 17, 2016, which means he’s a week shy of four years old.

Now a new investigation from Human Rights Watch has found that not only are children regularly added to CONARC, but the database also powers a live facial recognition system in Buenos Aires deployed by the city government. This makes the system likely the first known instance of its kind being used to hunt down kids suspected of criminal activity.

“It’s completely outrageous,” says Hye Jung Han, a children’s rights advocate at Human Rights Watch, who led the research.

Buenos Aires first began trialing live facial recognition on April 24, 2019. Implemented without any public consultation, the system sparked immediate resistance. In October, a national civil rights organization filed a lawsuit to challenge it. In response, the government drafted a new bill—now going through legislative processes—that would legalize facial recognition in public spaces.

The system was designed to link to CONARC from the beginning. While CONARC itself doesn’t contain any photos of its alleged offenders, it’s combined with photo IDs from the national registry. The software uses suspects’ headshots to scan for real-time matches via the city’s subway cameras. Once the system flags a person, it alerts to the police to make an arrest.

The system has since led to numerous false arrests (links in Spanish), which the police have no established protocol for handling. One man who was mistakenly identified was detained for six days and about to be transferred to a maximum security prison before he finally cleared up his identity. Another was told he should expect to be repeatedly flagged in the future even though he’d proved he wasn’t who the police were looking for. To help resolve the confusion, they gave him a pass to show to the next officer that might stop him.

“There seems to be no mechanism to be able to correct mistakes in either the algorithm or the database,” Han says. “That is a signal to us that here’s a government that has procured a technology that it doesn’t understand very well in terms of all the technical and human rights implications.”

All this is already deeply concerning, but adding children to the equation makes matters that much worse. Though the government has publicly denied (link in Spanish) that CONARC includes minors, Human Rights Watch found at least 166 children listed in various versions of the database between May 2017 and May 2020. Unlike M.G., most of them are identified by full name, which is illegal. Under international human rights law, children accused of a crime must have their privacy protected throughout the proceedings.

Also unlike M.G., most were 16 or 17 at time of entry—though, mysteriously, there have been a few one- to three-years-olds. The ages aren’t the only apparent errors in the children’s entries. There are blatant typos, conflicting details, and sometimes multiple national IDs listed for the same individual. Because kids also physically change faster than adults, their photo IDs are more at risk of being outdated.

On top of this, facial recognition systems, under even ideal laboratory conditions, are notoriously bad at handling children because they’re trained and tested primarily on adults. The Buenos Aires system is no different. According to official documents (link in Spanish), it was tested only on the adult faces of city government employees before procurement. Prior US government tests of the specific algorithm that it is believed to be using also suggest it performs worse by a factor of six on kids (ages 10 to 16) than adults (ages 24 to 40).

All these factors put kids at a heightened risk for being misidentified and falsely arrested. This could create an unwarranted criminal record, with potentially long-lasting repercussions for their education and employment opportunities. It might also have an impact on their behavior.

“The argument that facial recognition produces a chilling effect on the freedom of expression is more amplified for kids,” says Han. “You can just imagine a child [who has been falsely arrested] would be extremely self-censoring or careful about how they behave in public. And it’s still early to try and figure out the long-term psychological impacts—how it might shape their world view and mindset as well.”

While Buenos Aires is the first city Han has identified using live facial recognition to track kids, she worries that many other examples are hidden from view. In January, London announced that it would integrate live facial recognition into its policing operations. Within days, Moscow said it had rolled out a similar system across the city.

Though it’s not yet known whether these systems are actively trying to match children, kids are already being affected. In the 2020 documentary Coded Bias, a boy is falsely detained by the London police after live facial recognition mistakes him for someone else. It’s unclear whether the police were indeed looking for a minor or someone older.

Even those who are not detained are losing their right to privacy, says Han: “There’s all the kids who are passing in front of a facial-recognition-enabled camera just to access the subway system.”

It’s often easy to forget in debates about these systems that children need special consideration. But that’s not the only reason for concern, Han adds. “The fact that these kids would be under that kind of invasive surveillance—the full human rights and societal implications of this technology are still unknown.” Put another way: what’s bad for kids is ultimately bad for everyone.

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In 2019, two multimedia artists, Francesca Panetta and Halsey Burgund, set about to pursue a provocative idea. Deepfake video and audio had been advancing in parallel but had yet to be integrated into a complete experience. Could they do it in a way that demonstrated the technology’s full potential while educating people about how it could be abused?

To bring the experiment to life, they chose an equally provocative subject: they would create an alternative history of the 1969 Apollo moon landing. Before the launch, US president Richard Nixon’s speechwriters had prepared two versions of his national address—one designated “In Event of Moon Disaster,” in case things didn’t go as planned. The real Nixon, fortunately, never had to deliver it. But a deepfake Nixon could.

So Panetta, the creative director at MIT’s Center for Virtuality, and Burgund, a fellow at the MIT Open Documentary Lab, partnered up with two AI companies. Canny AI would handle the deepfake video, and Respeecher would prepare the deepfake audio. With all the technical components in place, they just needed one last thing: an actor who would supply the performance.

“We needed to find somebody who was willing to do this, because it’s a little bit of a weird ask,” Burgund says. “Somebody who was more flexible in their thinking about what an actor is and does.”

While deepfakes have now been around for a number of years, deepfake casting and acting are relatively new. Early deepfake technologies weren’t very good, used primarily in dark corners of the internet to swap celebrities into porn videos without their consent. But as deepfakes have grown increasingly realistic, more and more artists and filmmakers have begun using them in broadcast-quality productions and TV ads. This means hiring real actors for one aspect of the performance or another. Some jobs require an actor to provide “base” footage; others need a voice.

For actors, it opens up exciting creative and professional possibilities. But it also raises a host of ethical questions. “This is so new that there’s no real process or anything like that,” Burgund says. “I mean, we were just sort of making things up and flailing about.”

“Want to become Nixon?”

The first thing Panetta and Burgund did was ask both companies what kind of actor they needed to make the deepfakes work. “It was interesting not only what were the important criteria but also what weren’t,” Burgund says.

For the visuals, Canny AI specializes in video dialogue replacement, which uses an actor’s mouth movements to manipulate someone else’s mouth in existing footage. The actor, in other words, serves as a puppeteer, never to be seen in the final product. The person’s appearance, gender, age, and ethnicity don’t really matter.

But for the audio, Respeecher, which transmutes one voice into another, said it’d be easier to work with an actor who had a similar register and accent to Nixon’s. Armed with that knowledge, Panetta and Burgund began posting on various acting forums and emailing local acting groups. Their pitch: “Want to become Nixon?”

Actor Lewis D. Wheeler spent days in the studio training the deepfake algorithms to map his voice and face to Nixon’s.
PANETTA AND BURGUND

This is how Lewis D. Wheeler, a Boston-based white male actor, found himself holed up in a studio for days listening to and repeating snippets of Nixon’s audio. There were hundreds of snippets, each only a few seconds long, “some of which weren’t even complete words,” he says.

The snippets had been taken from various Nixon speeches, much of it from his resignation. Given the grave nature of the moon disaster speech, Respeecher needed training materials that captured the same somber tone.

Wheeler’s job was to re-record each snippet in his own voice, matching the exact rhythm and intonation. These little bits were then fed into Respeecher’s algorithm to map his voice to Nixon’s. “It was pretty exhausting and pretty painstaking,” he says, “but really interesting, too, building it brick by brick.”

The final deepfake of Nixon giving the speech “In Event of Moon Disaster.”
PANETTA AND BURGUND

The visual part of the deepfake was much more straightforward. In the archival footage that would be manipulated, Nixon had delivered the real moon landing address squarely facing the camera. Wheeler needed only to deliver its alternate, start to finish, in the same way, for the production crew to capture his mouth movements at the right angle.

This is where, as an actor, he started to find things more familiar. Ultimately his performance would be the one part of him that would make it into the final deepfake. “That was the most challenging and most rewarding,” he says. “For that, I had to really get into the mindset of, okay, what is this speech about? How do you tell the American people that this tragedy has happened?”

“How do we feel?”

On the face of it, Zach Math, a film producer and director, was working on a similar project. He’d been hired by Mischief USA, a creative agency, to direct a pair of ads for a voting rights campaign. The ads would feature deepfaked versions of North Korean leader Kim Jong-un and Russian president Vladimir Putin. But he ended up in the middle of something very different from Panetta and Burgund’s experiment.

In consultation with a deepfake artist, John Lee, the team had chosen to go the face-swapping route with the open-source software DeepFaceLab. It meant the final ad would include the actors’ bodies, so they needed to cast believable body doubles.

The ad would also include the actors’ real voices, adding an additional casting consideration. The team wanted the deepfake leaders to speak in English, though with authentic North Korean and Russian accents. So the casting director went hunting for male actors who resembled each leader in build and facial structure, matched their ethnicity, and could do convincing voice impersonations.

The process of training DeepFaceLab to generate Kim Jong-un’s face.
MISCHIEF USA

For Putin, the casting process was relatively easy. There’s an abundance of available footage of Putin delivering various speeches, providing the algorithm with plenty of training data to deepfake his face making a range of expressions. Consequently, there was more flexibility in what the actor could look like, because the deepfake could do most of the work.

But for Kim, most of the videos available showed him wearing glasses, which obscured his face and caused the algorithm to break down. Narrowing the training footage to only the videos without glasses left far fewer training samples to learn from. The resulting deepfake still looked like Kim, but his face movements looked less natural. Face-swapped onto an actor, it muted the actor’s expressions.

To counteract that, the team began running all of the actors’ casting tapes through DeepFaceLab to see which one came out looking the most convincing. To their surprise, the winner looked least like Kim physically but had the most expressive performance.

The actor chosen to play Kim Jong-un had the least physical resemblance to the dictator but the most expressive performance.

To address the aspects of Kim’s appearance that the deepfake couldn’t replicate, the team relied on makeup, costumes, and post-production work. The actor was slimmer than Kim, for example, so they had him wear a fat suit.

When it came down to judging the quality of the deepfake, Math says, it was less about the visual details and more about the experience. “It was never ‘Does that ear look weird?’ I mean, there were those discussions,” he says. “But it was always like, ‘Sit back—how do we feel?’”

“They were effectively acting as a human shield”

In some ways, there’s little difference between deepfake acting and CGI acting, or perhaps voice acting for a cartoon. Your likeness doesn’t make it into the final production, but the result still has your signature and interpretation. But deepfake casting can also go the other direction, with an person’s face swapped into someone else’s performance.

Making this type of fake persuasive was the task of Ryan Laney, a visual effects artist who worked on the 2020 HBO documentary Welcome to Chechnya. The film follows activists who risk their lives to fight the persecution of LGBTQ individuals in the Russian republic. Many of them live in secrecy for fear of torture and execution.

In order to tell their stories, director David France promised to protect their identities, but he wanted to do so without losing their humanity. After testing out numerous solutions, his team finally landed on deepfakes. He partnered with Laney, who developed an algorithm that overlaid one face onto another while retaining the latter’s expressions.

Left: a photo grid of Maxim shot at many angles. Right: a photo grid of his deepfake cover shot at many angles.
Left: Maxim Lapunov, the lead character in the documentary who goes public halfway through the film. Right: a Latino LGBTQ activist who volunteered to be Maxim’s shield.
TEUS MEDIA

The casting process was thus a search not for performers but for 23 people who would be willing to lend their faces. France ultimately asked LGBTQ activists to volunteer as “covers.” “He came at it from not who is the best actor, but who are the people interested in the cause,” Laney says, “because they were effectively acting as a human shield.”

The team scouted the activists through events and Instagram posts, based on their appearance. Each cover face needed to look sufficiently different from the person being masked while also aligning in certain characteristics. Facial hair, jawlines, and nose length needed to roughly match, for example, and each pair had to be approximately the same age for the cover person’s face to look natural on the original subject’s body.

Left: Maxim’s unmasked face. Right: Maxim with his deepfake cover.
TEUS MEDIA

The team didn’t always match ethnicity or gender, however. The lead character, Maxim Lapunov, who is white, was shielded by a Latino activist, and a female character was shielded by an activist who is gender nonconforming.

Throughout the process, France and Laney made sure to get fully informed consent from all parties. “The subjects of the film actually got to look at the work before David released it,” Laney says. “Everybody got to sign off on their own cover to make sure they felt comfortable.”

“It just gets people thinking”

While professionalized deepfakes have pushed the boundaries of art and creativity, their existence also raises tricky ethical questions. There are currently no real guidelines on how to label deepfakes, for example, or where the line falls between satire and misinformation.

For now, artists and filmmakers rely on a personal sense of right and wrong. France and Laney, for example, added a disclaimer to the start of the documentary stating that some characters had been “digitally disguised” for their protection. They also added soft edges to the masked individuals to differentiate them. “We didn’t want to hide somebody without telling the audience,” Laney says.

Stephanie Lepp, an artist and producer who creates deepfakes for political commentary, similarly marks her videos upfront to make clear they are fake. In her series Deep Reckonings, which imagines powerful figures like Mark Zuckerberg apologizing for their actions, she also used voice actors rather than deepfake audio to further distinguish the project as satirical and not deceptive.

Other projects have been more coy, such as those of Barnaby Francis, an artist-activist who works under the pseudonym Bill Posters. Over the years, Francis has deepfaked politicians like Boris Johnson and celebrities like Kim Kardashian, all in the name of education and satire. Some of the videos, however, are only labeled externally—for example, in the caption when Francis posts them on Instagram. Pulled out of that context, they risk blurring art and reality, which has sometimes led him into dicey territory.

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Today I’ve release a new series of #deepfake artworks with @futureadvocacy to raise awareness to the lack of regulation concerning misinformation online. These ‘partly political’ broadcasts see the UK Prime Minister Boris Johnson and Leader of the Opposition Jeremy Corbyn deep faked to send a warning to all governments regarding disinformation online. For this intervention, we’ve used the biometric data of famous UK politicians to challenge the fact that without greater controls and protections concerning personal data and powerful new technologies, misinformation poses a direct risk to everyone’s human rights including the rights of those in positions of power. It’s staggering that after 3 years, the recommendations from the DCMS Select Committee enquiry into fake news or the Information Commissioner’s Office enquiry into the Cambridge Analytica scandals have not been applied to change UK laws to protect our liberty and democracy. As a result, the conditions for computational forms of propaganda and misinformation campaigns to be amplified by social media platforms are still in effect today. We’re calling on all UK political parties to apply parliaments own findings and safeguard future elections. Despite endless warnings over the past few years, politicians have collectively failed to address the issue of disinformation online. Instead the response has been to defer to tech companies to do more. The responsibility for protecting our democracy lies in the corridors of Westminster not the boardrooms of Silicon Valley. See the full videos on my website! [LINK IN BIO] #deepfakes #newmediaart #ukelection #misinformation

A post shared by Bill Posters (@bill_posters_uk) on

There are also few rules around whose images and speech can be manipulated—and few protections for actors behind the scenes. Thus far, most professionalized deepfakes have been based on famous people and made with clear, constructive goals, so they are legally protected in the US under satire laws. In the case of Mischief’s Putin and Kim deepfakes, however, the actors have remained anonymous for “personal security reasons,” the team said, because of the controversial nature of manipulating the images of dictators.

Knowing how amateur deepfakes have been used to abuse, manipulate, and harass women, some creators are also worried about the direction things could go. “There’s a lot of people getting onto the bandwagon who are not really ethically or morally bothered about who their clients are, where this may appear, and in what form,” Francis says.

Despite these tough questions, however, many artists and filmmakers firmly believe deepfakes should be here to stay. Used ethically, the technology expands the possibilities of art and critique, provocation and persuasion. “It just gets people thinking,” Francis says. “It’s the perfect art form for these kinds of absurdist, almost surrealist times that we’re experiencing.”

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Want to develop a loyal YouTube following? Wondering how to better connect with an audience on YouTube? To explore how to grow and develop a loyal fan base on YouTube, I interview Cathrin Manning on the Social Media Marketing Podcast. Cathrin is a YouTube expert who teaches small YouTubers how to grow using the platform. […]

The post Growing on YouTube: How to Develop a Loyal Following appeared first on Social Media Examiner | Social Media Marketing.

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