“Deep Fake” Video Technology Is Advancing Faster Than Our Policies Can Keep Up
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Alethea.ai sports a grid of faces smiling, blinking and looking about. Some are beautiful, some are oddly familiar, but all share one thing in common—they are fake.
Alethea creates "synthetic media"— including digital faces customers can license saying anything they choose with any voice they choose. Companies can hire these photorealistic avatars to appear in explainer videos, advertisements, multimedia projects or any other applications they might dream up without running auditions or paying talent agents or actor fees. Licenses begin at a mere $99. Companies may also license digital avatars of real celebrities or hire mashups created from real celebrities including "Don Exotic" (a mashup of Donald Trump and Joe Exotic) or "Baby Obama" (a large-eared toddler that looks remarkably similar to a former U.S. President).
Naturally, in the midst of the COVID pandemic, the appeal is understandable. Rather than flying to a remote location to film a beer commercial, an actor can simply license their avatar to do the work for them. The question is—where and when this tech will cross the line between legitimately licensed and authorized synthetic media to deep fakes—synthetic videos designed to deceive the public for financial and political gain.
Deep fakes are not new. From written quotes that are manipulated and taken out of context to audio quotes that are spliced together to mean something other than originally intended, misrepresentation has been around for centuries. What is new is the technology that allows this sort of seamless and sophisticated deception to be brought to the world of video.
"At one point, video content was considered more reliable, and had a higher threshold of trust," said Alethea CEO and co-founder, Arif Khan. "We think video is harder to fake and we aren't yet as sensitive to detecting those fakes. But the technology is definitely there."
"In the future, each of us will only trust about 15 people and that's it," said Phil Lelyveld, who serves as Immersive Media Program Lead at the Entertainment Technology Center at the University of Southern California. "It's already very difficult to tell true footage from fake. In the future, I expect this will only become more difficult."
How do we know what's true in a world where original videos created with avatars of celebrities and politicians can be manipulated to say virtually anything?
As the U.S. 2020 Presidential Election nears, the potential moral and ethical implications of this technology are startling. A number of cases of truth tampering have recently been widely publicized. On August 5, President Donald Trump's campaign released an ad featuring several photos of Joe Biden that were altered to make it seem like was hiding all alone in his basement. In one photo, at least ten people who had been sitting with Biden in the original shot were cut out. In other photos, Biden's image was removed from a nature preserve and praying in church to make it appear Biden was in that same basement. Recently several videos of Speaker of the House Nancy Pelosi were slowed down by 75 percent to make her sound as if her speech was slurred.
During a campaign event in Florida on September 15 of this year, former Vice President Joe Biden was introduced by Puerto Rican singer-songwriter Luis Fonsi. After he was introduced, Biden paid tribute to the singer-songwriter—he held up his cell phone and played the hit song "Despecito". Shortly afterward, a doctored version of this video appeared on self-described parody site the United Spot replacing the Despicito with N.W.A.'s "F—- Tha Police". By September 16, Donald Trump retweeted the video, twice—first with the line "What is this all about" and second with the line "China is drooling. They can't believe this!" Twitter was quick to mark the video in these tweets as manipulated media.
Twitter had previously addressed several of Donald Trump's tweets—flagging a video shared in June as manipulated media and removing altogether a video shared by Trump in July showing a group promoting the hydroxychloroquine as an effective cure for COVID-19. Many of these manipulated videos are ultimately flagged or taken down, but not before they are seen and shared by millions of online viewers.
These faked videos were exposed rather quickly, as they could be compared with the original, publicly available source material. But what happens when there is no original source material? How do we know what's true in a world where original videos created with avatars of celebrities and politicians can be manipulated to say virtually anything?
"This type of fake media is a profound threat to our democracy," said Reid Blackman, the CEO of VIRTUE--an ethics consultancy for AI leaders. "Democracy depends on well-informed citizens. When citizens can't or won't discern between real and fake news, the implications are huge."
In light of the importance of reliable information in the political system, there's a clear and present need to verify that the images and news we consume is authentic. So how can anyone ever know that the content they are viewing is real?
"This will not be a simple technological solution," said Blackman. "There is no 'truth' button to push to verify authenticity. There's plenty of blame and condemnation to go around. Purveyors of information have a responsibility to vet the reliability of their sources. And consumers also have a responsibility to vet their sources."
Yet the process of verifying sources has never been more challenging. More and more citizens are choosing to live in a "media bubble"—gathering and sharing news only from and with people who share their political leanings and opinions. At one time, United States broadcasters were bound by the Fairness Doctrine—requiring them to present controversial issues important to the public in a way that the FCC deemed honest, equitable and balanced. The repeal of this doctrine in 1987 paved the way for new forms of cable news channels such as Fox News and MSNBC that appealed to viewers with a particular point of view. The Internet has only exacerbated these tendencies. Social media algorithms are designed to keep people clicking within their comfort zones by presenting members with only the thoughts and opinions they want to hear.
"I sometimes laugh when I hear people tell me they can back a particular opinion they hold with research," said Blackman. "Having conducted a fair bit of true scientific research, I am aware that clicking on one article on the Internet hardly qualifies. But a surprising number of people believe that finding any source online that states the fact they choose to believe is the same as proving it true."
Back to the fundamental challenge: How do we as a society root out what's false online? Lelyveld suggests that it will begin by verifying things that are known to be true rather than trying to call out everything that is fake. "The EU called me in to talk about how to deal with fake news coming out of Russia," said Lelyveld. "I told them Hollywood has spent 100 years developing special effects technology to make things that are wholly fictional indistinguishable from the truth. I told them that you'll never chase down every source of fake news. You're better off focusing on what can be proved true."
Arif Khan agrees. "There are probably 100 accounts attributed to Elon Musk on Twitter, but only one has the blue checkmark," said Khan. "That means Twitter has verified that an account of public interest is real. That's what we're trying to do with our platform. Allow celebrities to verify that specific videos were licensed and authorized directly by them."
Alethea will use another key technology called blockchain to mark all authentic authorized videos with celebrity avatars. Blockchain uses a distributed ledger technology to make sure that no undetected changes have been made to the content. Think of the difference between editing a document in a traditional word processing program and editing in a distributed online editing system like Google Docs. In a traditional word processing program, you can edit and copy a document without revealing any changes. In a shared editing system like Google Docs, every person who shares the document can see a record of every edit, addition and copy made of any portion of the document. In a similar way, blockchain helps Alethea ensure that approved videos have not been copied or altered inappropriately.
While AI companies like Alethea are moving to ensure that avatars based on real individuals aren't wrongly identified, the situation becomes a bit murkier when it comes to the question of representing groups, races, creeds, and other forms of identity. Alethea is rightly proud that the completely artificial avatars visually represent a variety of ages, races and sexes. However, companies could conceivably license an avatar to represent a marginalized group without actually hiring a person within that group to decide what the avatar will do or say.
"I don't know if I would call this tokenism, as that is difficult to identify without understanding the hiring company's intent," said Blackman. "Where this becomes deeply troubling is when avatars are used to represent a marginalized group without clearly pointing out the actor is an avatar. It's one thing for an African American woman avatar to say, 'I like ice cream.' It's entirely different thing for an African American woman avatar to say she supports a particular political candidate. In the second case, the avatar is being used as social proof that real people of a certain type back a certain political idea. And there the deception is far more problematic."
"It always comes down to unintended consequences of technology," said Lelyveld. "Technology is neutral—it's only the implementation that has the power to be good or bad. Without a thoughtful approach to the cultural, moral and political implications of technology, it often drifts towards the bad. We need to make a conscious decision as we release new technology to ensure it moves towards the good."
When presented with the idea that his avatars might be used to misrepresent marginalized groups, Khan was thoughtful. "Yes, I can see that is an unintended consequence of our technology. We would like to encourage people to license the avatars of real people, who would have final approval over what their avatars say or do. As to what people do with our completely artificial avatars, we will have to consider that moving forward."
Lelyveld frankly sees the ability for advertisers to create avatars that are our assistants or even our friends as a greater moral concern. "Once our digital assistant or avatar becomes an integral part of our life—even a friend as it were, what's to stop marketers from having those digital friends make suggestions about what drink we buy, which shirt we wear or even which candidate we elect? The possibilities for bad actors to reach us through our digital circle is mind-boggling."
Ultimately, Blackman suggests, we as a society will need to make decisions about what matters to us. "We will need to build policies and write laws—tackling the biggest problems like political deep fakes first. And then we have to figure out how to make the penalties stiff enough to matter. Fining a multibillion-dollar company a few million for a major offense isn't likely to move the needle. The punishment will need to fit the crime."
Until then, media consumers will need to do their own due diligence—to do the difficult work of uncovering the often messy and deeply uncomfortable news that's the truth.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
Awash in a fluid finely calibrated to keep it alive, a human eye rests inside a transparent cubic device. This ECaBox, or Eyes in a Care Box, is a one-of-a-kind system built by scientists at Barcelona’s Centre for Genomic Regulation (CRG). Their goal is to preserve human eyes for transplantation and related research.
In recent years, scientists have learned to transplant delicate organs such as the liver, lungs or pancreas, but eyes are another story. Even when preserved at the average transplant temperature of 4 Centigrade, they last for 48 hours max. That's one explanation for why transplanting the whole eye isn’t possible—only the cornea, the dome-shaped, outer layer of the eye, can withstand the procedure. The retina, the layer at the back of the eyeball that turns light into electrical signals, which the brain converts into images, is extremely difficult to transplant because it's packed with nerve tissue and blood vessels.
These challenges also make it tough to research transplantation. “This greatly limits their use for experiments, particularly when it comes to the effectiveness of new drugs and treatments,” said Maria Pia Cosma, a biologist at Barcelona’s Centre for Genomic Regulation (CRG), whose team is working on the ECaBox.
Eye transplants are desperately needed, but they're nowhere in sight. About 12.7 million people worldwide need a corneal transplant, which means that only one in 70 people who require them, get them. The gaps are international. Eye banks in the United Kingdom are around 20 percent below the level needed to supply hospitals, while Indian eye banks, which need at least 250,000 corneas per year, collect only around 45 to 50 thousand donor corneas (and of those 60 to 70 percent are successfully transplanted).
As for retinas, it's impossible currently to put one into the eye of another person. Artificial devices can be implanted to restore the sight of patients suffering from severe retinal diseases, but the number of people around the world with such “bionic eyes” is less than 600, while in America alone 11 million people have some type of retinal disease leading to severe vision loss. Add to this an increasingly aging population, commonly facing various vision impairments, and you have a recipe for heavy burdens on individuals, the economy and society. In the U.S. alone, the total annual economic impact of vision problems was $51.4 billion in 2017.
Even if you try growing tissues in the petri dish route into organoids mimicking the function of the human eye, you will not get the physiological complexity of the structure and metabolism of the real thing, according to Cosma. She is a member of a scientific consortium that includes researchers from major institutions from Spain, the U.K., Portugal, Italy and Israel. The consortium has received about $3.8 million from the European Union to pursue innovative eye research. Her team’s goal is to give hope to at least 2.2 billion people across the world afflicted with a vision impairment and 33 million who go through life with avoidable blindness.
Their method? Resuscitating cadaveric eyes for at least a month.
If we succeed, it will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo. -- Maria Pia Cosma.
“We proposed to resuscitate eyes, that is to restore the global physiology and function of human explanted tissues,” Cosma said, referring to living tissues extracted from the eye and placed in a medium for culture. Their ECaBox is an ex vivo biological system, in which eyes taken from dead donors are placed in an artificial environment, designed to preserve the eye’s temperature and pH levels, deter blood clots, and remove the metabolic waste and toxins that would otherwise spell their demise.
Scientists work on resuscitating eyes in the lab of Maria Pia Cosma.
Courtesy of Maria Pia Cosma.
“One of the great challenges is the passage of the blood in the capillary branches of the eye, what we call long-term perfusion,” Cosma said. Capillaries are an intricate network of very thin blood vessels that transport blood, nutrients and oxygen to cells in the body’s organs and systems. To maintain the garland-shaped structure of this network, sufficient amounts of oxygen and nutrients must be provided through the eye circulation and microcirculation. “Our ambition is to combine perfusion of the vessels with artificial blood," along with using a synthetic form of vitreous, or the gel-like fluid that lets in light and supports the the eye's round shape, Cosma said.
The scientists use this novel setup with the eye submersed in its medium to keep the organ viable, so they can test retinal function. “If we succeed, we will ensure full functionality of a human organ ex vivo. It will be the first intact human model of the eye capable of exploring and analyzing regenerative processes ex vivo,” Cosma added.
A rapidly developing field of regenerative medicine aims to stimulate the body's natural healing processes and restore or replace damaged tissues and organs. But for people with retinal diseases, regenerative medicine progress has been painfully slow. “Experiments on rodents show progress, but the risks for humans are unacceptable,” Cosma said.
The ECaBox could boost progress with regenerative medicine for people with retinal diseases, which has been painfully slow because human experiments involving their eyes are too risky. “We will test emerging treatments while reducing animal research, and greatly accelerate the discovery and preclinical research phase of new possible treatments for vision loss at significantly reduced costs,” Cosma explained. Much less time and money would be wasted during the drug discovery process. Their work may even make it possible to transplant the entire eyeball for those who need it.
“It is a very exciting project,” said Sanjay Sharma, a professor of ophthalmology and epidemiology at Queen's University, in Kingston, Canada. “The ability to explore and monitor regenerative interventions will increasingly be of importance as we develop therapies that can regenerate ocular tissues, including the retina.”
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation.
But is the world ready for eye transplants? “People are a bit weird or very emotional about donating their eyes as compared to other organs,” Cosma said. And much can be said about the problem of eye donor shortage. Concerns include disfigurement and healthcare professionals’ fear that the conversation about eye donation will upset the departed person’s relatives because of cultural or religious considerations. As just one example, Sharma noted the paucity of eye donations in his home country, Canada.
Yet, experts like Sharma stress the importance of these donations for both the recipients and their family members. “It allows them some psychological benefit in a very difficult time,” he said. So why are global eye banks suffering? Is it because the eyes are the windows to the soul?
Seemingly, there's no sacred religious text or a holy book prohibiting the practice of eye donation. In fact, most major religions of the world permit and support organ transplantation and donation, and by extension eye donation, because they unequivocally see it as an “act of neighborly love and charity.” In Hinduism, the concept of eye donation aligns with the Hindu principle of daan or selfless giving, where individuals donate their organs or body after death to benefit others and contribute to society. In Islam, eye donation is a form of sadaqah jariyah, a perpetual charity, as it can continue to benefit others even after the donor's death.
Meanwhile, Buddhist masters teach that donating an organ gives another person the chance to live longer and practice dharma, the universal law and order, more meaningfully; they also dismiss misunderstandings of the type “if you donate an eye, you’ll be born without an eye in the next birth.” And Christian teachings emphasize the values of love, compassion, and selflessness, all compatible with organ donation, eye donation notwithstanding; besides, those that will have a house in heaven, will get a whole new body without imperfections and limitations.
The explanation for people’s resistance may lie in what Deepak Sarma, a professor of Indian religions and philosophy at Case Western Reserve University in Cleveland, calls “street interpretation” of religious or spiritual dogmas. Consider the mechanism of karma, which is about the causal relation between previous and current actions. “Maybe some Hindus believe there is karma in the eyes and, if the eye gets transplanted into another person, they will have to have that karmic card from now on,” Sarma said. “Even if there is peculiar karma due to an untimely death–which might be interpreted by some as bad karma–then you have the karma of the recipient, which is tremendously good karma, because they have access to these body parts, a tremendous gift,” Sarma said. The overall accumulation is that of good karma: “It’s a beautiful kind of balance,” Sarma said.
For the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the already existing body is sacred since it will be the basis of a new refashioned body in an afterlife.---Omar Sultan Haque.
With that said, Sarma believes it is a fallacy to personify or anthropomorphize the eye, which doesn’t have a soul, and stresses that the karma attaches itself to the soul and not the body parts. But for scholars like Omar Sultan Haque—a psychiatrist and social scientist at Harvard Medical School, investigating questions across global health, anthropology, social psychology, and bioethics—the hierarchy of sacredness of body parts is entrenched in human psychology. You cannot equate the pinky toe with the face, he explained.
“The eyes are the window to the soul,” Haque said. “People have a hierarchy of body parts that are considered more sacred or essential to the self or soul, such as the eyes, face, and brain.” In his view, the techno-utopian transhumanist communities (especially those in Silicon Valley) have reduced the totality of a person to a mere material object, a “wet robot” that knows no sacredness or hierarchy of human body parts. “But for the Jews, Christians, and Muslims who believe in the physical resurrection of the body that will be made new in an afterlife, the [already existing] body is sacred since it will be the basis of a new refashioned body in an afterlife,” Haque said. “You cannot treat the body like any old material artifact, or old chair or ragged cloth, just because materialistic, secular ideologies want so,” he continued.
For Cosma and her peers, however, the very definition of what is alive or not is a bit semantic. “As soon as we die, the electrophysiological activity in the eye stops,” she said. “The goal of the project is to restore this activity as soon as possible before the highly complex tissue of the eye starts degrading.” Cosma’s group doesn’t yet know when they will be able to keep the eyes alive and well in the ECaBox, but the consensus is that the sooner the better. Hopefully, the taboos and fears around the eye donations will dissipate around the same time.
As Our AI Systems Get Better, So Must We
As the power and capability of our AI systems increase by the day, the essential question we now face is what constitutes peak human. If we stay where we are while the AI systems we are unleashing continually get better, they will meet and then exceed our capabilities in an ever-growing number of domains. But while some technology visionaries like Elon Musk call for us to slow down the development of AI systems to buy time, this approach alone will simply not work in our hyper-competitive world, particularly when the potential benefits of AI are so great and our frameworks for global governance are so weak. In order to build the future we want, we must also become ever better humans.
The list of activities we once saw as uniquely human where AIs have now surpassed us is long and growing. First, AI systems could beat our best chess players, then our best Go players, then our best champions of multi-player poker. They can see patterns far better than we can, generate medical and other hypotheses most human specialists miss, predict and map out new cellular structures, and even generate beautiful, and, yes, creative, art.
A recent paper by Microsoft researchers analyzing the significant leap in capabilities in OpenAI’s latest AI bot, ChatGPT-4, asserted that the algorithm can “solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting.” Calling this functionality “strikingly close to human-level performance,” the authors conclude it “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.”
The concept of AGI has been around for decades. In its common use, the term suggests a time when individual machines can do many different things at a human level, not just one thing like playing Go or analyzing radiological images. Debating when AGI might arrive, a favorite pastime of computer scientists for years, now has become outdated.
We already have AI algorithms and chatbots that can do lots of different things. Based on the generalist definition, in other words, AGI is essentially already here.
Unfettered by the evolved capacity and storage constraints of our brains, AI algorithms can access nearly all of the digitized cultural inheritance of humanity since the dawn of recorded history and have increasing access to growing pools of digitized biological data from across the spectrum of life.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
With these ever-larger datasets, rapidly increasing computing and memory power, and new and better algorithms, our AI systems will keep getting better faster than most of us can today imagine. These capabilities have the potential to help us radically improve our healthcare, agriculture, and manufacturing, make our economies more productive and our development more sustainable, and do many important things better.
Soon, they will learn how to write their own code. Like human children, in other words, AI systems will grow up. But even that doesn’t mean our human goose is cooked.
Just like dolphins and dogs, these alternate forms of intelligence will be uniquely theirs, not a lesser or greater version of ours. There are lots of things AI systems can't do and will never be able to do because our AI algorithms, for better and for worse, will never be human. Our embodied human intelligence is its own thing.
Our human intelligence is uniquely ours based on the capacities we have developed in our 3.8-billion-year journey from single cell organisms to us. Our brains and bodies represent continuous adaptations on earlier models, which is why our skeletal systems look like those of lizards and our brains like most other mammals with some extra cerebral cortex mixed in. Human intelligence isn’t just some type of disembodied function but the inextricable manifestation of our evolved physical reality. It includes our sensory analytical skills and all of our animal instincts, intuitions, drives, and perceptions. Disembodied machine intelligence is something different than what we have evolved and possess.
Because of this, some linguists including Noam Chomsky have recently argued that AI systems will never be intelligent as long as they are just manipulating symbols and mathematical tokens without any inherent understanding. Nothing could be further from the truth. Anyone interacting with even first-generation AI chatbots quickly realizes that while these systems are far from perfect or omniscient and can sometimes be stupendously oblivious, they are surprisingly smart and versatile and will get more so… forever. We have little idea even how our own minds work, so judging AI systems based on their output is relatively close to how we evaluate ourselves.
Anyone not awed by the potential of these AI systems is missing the point. AI’s newfound capacities demand that we work urgently to establish norms, standards, and regulations at all levels from local to global to manage the very real risks. Pausing our development of AI systems now doesn’t make sense, however, even if it were possible, because we have no sufficient ways of uniformly enacting such a pause, no plan for how we would use the time, and no common framework for addressing global collective challenges like this.
But if all we feel is a passive awe for these new capabilities, we will also be missing the point.
Human evolution, biology, and cultural history are not just some kind of accidental legacy, disability, or parlor trick, but our inherent superpower. Our ancestors outcompeted rivals for billions of years to make us so well suited to the world we inhabit and helped build. Our social organization at scale has made it possible for us to forge civilizations of immense complexity, engineer biology and novel intelligence, and extend our reach to the stars. Our messy, embodied, intuitive, social human intelligence is roughly mimicable by AI systems but, by definition, never fully replicable by them.
Once we recognize that both AI systems and humans have unique superpowers, the essential question becomes what each of us can do better than the other and what humans and AIs can best do in active collaboration. We still don't know. The future of our species will depend upon our ability to safely, dynamically, and continually figure that out.
As we do, we'll learn that many of our ideas and actions are made up of parts, some of which will prove essentially human and some of which can be better achieved by AI systems. Those in every walk of work and life who most successfully identify the optimal contributions of humans, AIs, and the two together, and who build systems and workflows empowering humans to do human things, machines to do machine things, and humans and machines to work together in ways maximizing the respective strengths of each, will be the champions of the 21st century across all fields.
The dawn of the age of machine intelligence is upon us. It’s a quantum leap equivalent to the domestication of plants and animals, industrialization, electrification, and computing. Each of these revolutions forced us to rethink what it means to be human, how we live, and how we organize ourselves. The AI revolution will happen more suddenly than these earlier transformations but will follow the same general trajectory. Now is the time to aggressively prepare for what is fast heading our way, including by active public engagement, governance, and regulation.
AI systems will not replace us, but, like these earlier technology-driven revolutions, they will force us to become different humans as we co-evolve with our technology. We will never reach peak human in our ongoing evolutionary journey, but we’ve got to manage this transition wisely to build the type of future we’d like to inhabit.
Alongside our ascending AIs, we humans still have a lot of climbing to do.