Deepfakes and Trust Decay

Deepfakes and Trust Decay

You may have observed a lull in my usual stream of articles. I've been working on some exciting things behind the scenes, and I look forward to sharing more soon. During this period of intense ideation, I’ve been exchanging insights with a diverse network of peers, family, professionals, and patrons, contemplating the trajectory AI will chart in the imminent future. The year 2024 looms with potential breakthroughs that are as thrilling as they are transformative. Yet, it is imperative at this juncture to pivot our focus to a pressing dialogue—addressing the immediate challenges posed by Generative AI.

Warning: This topic is weighty, and far from the more uplifting thought leadership I usually put out. It's pragmatic, candid, and admittedly grim. But it is important and, I believe, necessary.

Setting the Stage

In recent years, our collective grip on reality has been slipping. Society has been thrust into a vortex of doubt, where even the most established facts can be questioned, and the most reliable sources scrutinized with suspicion. With the rapid integration of Generative AI into every conceivable digital platform and application, this trend is accelerating. We are facing a near-term risk where the lines between fact and fiction become dangerously blurred, potentially unraveling the fabric of our society, democracy, and the very concept of truth.

The insights I share here might strike some as alarmist, but from my vantage point, deeply embedded in the nuances of this technology, the risks are clear and present.

Content Overview

In laying out this claim, I come armed with experience, research, evidence, logical reason, and practicality. I’ve structured this article to ease you into a grim forecast:

  • Chapter 1: Initially, we will look at pre-existing conditions—the pervasive distrust in information that has been sown within society before Generative AI became a household term.
  • Chapter 2: Moving forward, we'll pivot to contemporary examples where Generative AI has not just entered the chat but has amplified it to a deafening roar.
  • Chapter 3: As we analyze these precedents, they will serve as a springboard to explore what lies on the horizon for 2024. Next year, we will see that the fabric of truth is not just stretched thin but is systematically rewoven by the looms of advanced, Generative AI technology.
  • Final Thoughts: I'll distill my perspective, shedding light on where I believe we stand. Moreover, I'll suggest some steps to consider to navigate this burgeoning storm of Generative AI.




Chapter 1: Starting From a Foundation of Distrust

The seeds of doubt were sown well before the rise of Generative AI, and this section highlights recent threads that wove the tapestry of distrust in our media landscape. From the orchestrated echoes of the Sinclair Broadcast Group, through the labyrinthine revelations of the Twitter Files, to the enigmatic UAP Disclosures, we trace the lineage of our current plight. These are the breadcrumbs that led us to the forest's edge.

Sinclair Broadcast Group Controversy

The Sinclair Broadcast Group controversy epitomizes a significant challenge within the traditional media landscape—the potential for a centralized narrative to be imposed across a diverse array of channels.

As seen in the video above, when anchors at various stations under Sinclair's umbrella were required to read a script decrying the proliferation of 'fake news,' it exposed the mechanisms through which a parent company could exert editorial control on a national scale, effectively homogenizing the message delivered to the public. This orchestrated dissemination of a singular perspective demonstrates the influence media conglomerates can wield.

The message, ostensibly about combating misinformation, paradoxically raised concerns about the integrity of the news itself. The centralization of messaging by Sinclair created an echo across its network, reaching millions, which could stifle local journalistic independence and prioritize corporate directives over unbiased reporting. This situation feeds into the larger tapestry of public distrust.

If a media company can script reality across numerous stations, what assurances does the public have that what they are hearing and seeing is genuine and not simply a narrative constructed for convenience or profit?

The Twitter Files

The Twitter Files, a collection of internal communications made public, illuminate the mechanics behind the curtain of social media. These documents purport to reveal the platform's use of 'visibility filtering'—a method by which the visibility of specific tweets can be artificially inflated or suppressed without the knowledge of the platform's users.

This practice, on its surface, is a tool for curating content to enhance user experience. Yet, it allegedly doubles as a lever of power, capable of quietly shaping public perception by amplifying select viewpoints and muting others.

This mechanism of control becomes particularly troubling in light of further allegations involving the United States Central Command (CENTCOM). The Twitter Files suggest that CENTCOM's accounts were given a form of immunity against the standard visibility filtering, allowing them to operate influence campaigns with a veneer of organic support. These accounts, reportedly, did not disclose their connection to the military, masquerading instead as the voices of everyday civilians.

Such claims, if true, cast a shadow on the role social media plays in our society. Platforms once heralded as bastions of free speech and democratic discourse are implicated as potential instruments for psychological operations (psyops). This potential misuse of power to covertly steer public conversation erodes the foundational trust users place in these platforms. It also raises profound ethical questions about the responsibility of social media giants in safeguarding the integrity of public dialogue. Amidst this debate, figures like Elon Musk have championed a return to unfettered speech on social media—a stance that, while contentious, underscores the complexity of this situation.

Unidentified Aerial Phenomena Disclosures

The unfolding narrative of Unidentified Aerial Phenomena (UAP) and the accounts of alleged extraterrestrial encounters serve as a compelling allegory for the informational quagmire that engulfs our era.

The pervasive uncertainty surrounding these sightings is emblematic of a larger crisis—a crisis of discernment. With each new UAP sighting reported, with every claim of close encounters, the public is plunged into a maelstrom of debate, skepticism, and conspiracy, which further obscures the line between reality and myth. These phenomena do more than just captivate the imagination; they challenge the very processes by which we establish truths in a world brimming with data yet starved for veracity.

UAPs, in their elusive and unverified nature, provoke a cascade of questions. Skeptics and believers alike dissect footage and eyewitness reports, often arriving at diametrically opposed conclusions based on the same set of information. These debates are not confined to the fringes but have prompted official investigations and reports from some of the world's most venerable institutions, which sometimes raise more questions than they answer.

This struggle mirrors our daily confrontations with the information we encounter. In a digital age where content is king, the veracity of that content has become increasingly suspect. The challenge lies not just in the content itself but in the intent behind its dissemination. Who benefits from public belief in, or dismissal of, such phenomena? Are narratives being shaped by those seeking to exploit the mysteries for entertainment, for profit, or for more insidious purposes such as distraction or disinformation? UAPs, thus, become a fitting metaphor for the complexities of our society.

Chapter Wrap-up (so what)

The erosion of trust is systemic, leading to a state where expertise is derided and authority is doubted. The intelligence apparatus and influence groups appear to some as puppeteers, shaping public perception from behind a multiplicity of curtains. Individuals find themselves torn between disbelief in conspiracies and skepticism of mainstream narratives, unable to reconcile these conflicting realities. Before Generative AI, we were already in an age where discerning reality has become a Herculean task. The issue transcends the boundaries of mere skepticism and ventures into a realm where the very essence of what we accept as reality is under scrutiny. Doubt has seeped into the mainstream, challenging the veracity of everyday information.





Chapter 2: The Rise of Generative Deception

Generative AI has emerged as one of the most important technological breakthroughs of the last century. However, if weaponized, this technology has the power to erode truth. We are witnessing the rise of sophisticated digital forgeries that use AI to make people appear to say or do things they never did. These fabricated images and videos have become increasingly convincing, making them a potent tool for misinformation and manipulation. And amidst this unfolding narrative, remember, folks, we are still at the starting line.

Pentagon Deepfake and Market Impact

The Pentagon incident underscores the potential hazards of deepfake technology in a more serious context. A fake image that depicted a large explosion near the Pentagon was disseminated on Twitter (now X), causing a brief yet real dip in the stock market. This event vividly illustrates the disruptive power of AI-generated misinformation, capable of swaying financial markets and skewing public perception within moments. It signals an alarming vulnerability in our information ecosystem, where the veracity of content is easily compromised, and the ripple effects can be felt across the economic landscape with swift and serious consequences.

Tom Hanks and Mr Beast Deepfake Scam

Tom Hanks found himself at the center of a deepfake scam. A video that went viral appeared to show him promoting, in rather colorful language, dubious investment strategies. This video gained traction on Reddit's Wall Street Bets subreddit. In a separate event, Hanks had to issue a warning about a deepfake involving a dental plan advertisement that featured an AI-generated likeness of himself, cautioning his 9.5 million Instagram followers about the scam.

Turning to the YouTube space, we find MrBeast—another victim of deepfake technology. Jesse Wellens, for his podcast 'Not A Normal Podcast', created an AI clone of MrBeast, which he shared on social media. Despite the initial shock from MrBeast himself, it was made clear that the intention was not to profit from his likeness but rather to engage in a novel form of conversation.

The Rise of Newsbots

NewsGuard uncovered hundreds upon hundreds of websites worldwide that seemed to be almost entirely run by Generative AI. These websites span the gamut of human interest — from the political arena to the minutiae of health, the glitz of entertainment, the ebb and flow of finance, and the rapid advancements in technology. The catch? They're shrouded in mystery, their proprietors a shadowy question mark, but their purpose is singular and clear: farm ad revenue through clickbait headlines that capture human attention. It's the new gold rush of the information age, and AI has staked its claim.

Westfield High Deepfake Violation

The incident at Westfield High School in New Jersey is a sobering example of the dark potential of deepfake technology. Students at the school were implicated in the creation and dissemination of AI-generated pornographic images featuring their underage classmates. These images were spread through group chats, causing distress among the victims and confusion among parents and school authorities due to the lack of clear legal recourse. The incident highlights critical questions about the categorization of such materials and the legal definitions that should apply to deepfakes. Efforts are being made in various states to establish laws against the nonconsensual creation and distribution of deepfake pornography, but at the time of the incident, New Jersey had no such laws. The principal of Westfield High School, Mary Asfendi, emphasized the gravity of the situation and the importance of understanding the impact of misusing technology. In response to the incident, at least four parents filed police reports. This episode has amplified calls for legislative action, highlighting the need for a legal framework that specifically addresses the nonconsensual use of one's likeness in deepfake media.

Chapter Wrap-up (so what)

The technology, while a marvel of human ingenuity, poses unique threats to the fabric of truth, as evidenced by the Pentagon deepfake incident and the troubling events at Westfield High School. The question is no longer about the potential of Generative AI to disrupt—it's about our collective resolve to steer this force toward the greater good while curbing its capacity for harm.





Chapter 3: The Oncoming Reality of 2024

As we usher Generative AI into the consumer technology sector, we must recognize we are not merely adopting a new suite of tools, but rather we are sowing the seeds of an epistemological crisis. The push for open-source AI, while noble in its pursuit of progress and inclusivity, inadvertently skirts the chilling potential for misuse by a shrewd minority. This notion is punctuated by the deep and sometimes insidious impact social media has already carved into the bedrock of societal discourse.

Adobe Represents The Double-Edged Sword of Digital Creativity

Adobe, a titan in digital content creation, illustrates the paradox of our times. On one hand, their advancements democratize creativity, giving more people the tools to express and create. Yet, they simultaneously equip individuals with the means to fabricate convincing realities. Let's look at the Adobe MAX 2023.

Adobe has a session called 'Sneaks' where Adobe engineers give a first look at potential future technologies. The Sneaks are a fan favorite moment every year at Adobe MAX. The Sneaks highlight several new Generative AI capabilities across photo, video, audio, 3D, and design.

Products like 'Project Fast Fill ' and 'Project Stardust ' automate and refine content creation, making it difficult to distinguish genuine digital artifacts from fabricated ones. 'Project Dub Dub Dub ' and 'Project See Through ' further enhance this capability, presenting a world where language is no barrier and obstacles to 'perfection' in content are but a memory. While these tools have noble intentions, they inadvertently hand a loaded weapon to those with malicious agendas: the ability to craft disinformation at an unprecedented scale.

Psychological Consequences

The psychological ramifications of this are profound. As the line between authentic and artificial blurs, we risk engendering a pervasive skepticism that undermines social cohesion. Individuals may become increasingly insular, wary of engaging with the content and perhaps even with each other. The principle of 'seeing is believing' no longer holds water in an age where seeing no longer equates to truth.

Furthermore, consider the implications for identity in a world where one's digital presence can be convincingly fabricated. The concept of 'self' becomes malleable in the public eye, leading to potential crises of identity and trust. In a digital landscape rife with potential for manipulation, individuals may find themselves questioning their own memories and experiences—after all, if a conversation, an event, or a person's image can be falsified, where does that leave our own perception of reality?

This psychological impact also raises the stakes for mental health. The constant vigilance required to navigate this new reality may lead to increased anxiety and paranoia. The cognitive load of discerning real from fake, truth from falsehood, is non-trivial and may contribute to collective mental fatigue.

Open Source Debate Needs to Shift from Why to How

Yann LeCun , a luminary in the field of artificial intelligence and the Chief AI Scientist at Meta, stands as a vocal proponent for the democratization of AI technologies. Dr. LeCun posits that by making AI platforms accessible to all, we can harness the collective genius of the crowd—not only to drive forward the boundaries of innovation but also to oversee and regulate the technology in a manner that is both inclusive and transparent.

In Dr. LeCun's view, the open source movement within AI is a critical equalizer. It prevents the concentration of AI knowledge within the silos of a few corporations or governments, which could lead to abuses of power and the suppression of beneficial innovations that do not align with the interests of those at the helm. By advocating for crowd-sourced oversight, Dr. LeCun envisions a community-driven governance model where ethical considerations and societal impact are at the forefront of AI development.

Indeed, the open sourcing of AI is necessary to foster transparency and collective growth. However, to democratize access to such powerful tools also means to arm an unprepared public with a technology that has the dual potential to weave tapestries of innovation as well as to rend the fabric of societal norms. My concern lies not with the empowered many but with the unscrupulous few who might exploit this egalitarian resource for malevolent ends.

Therefore, the conversation must pivot from the simplistic advocacy of open sourcing to a nuanced debate on the mechanisms of its implementation. How do we ensure that open-source AI becomes a tool for widespread benefit and not a Pandora's box that, once opened, could be impossible to close? The path to democratization must be trodden carefully, safeguarding against the inherent risks while nurturing the seeds of innovation and inclusion.

Technological Countermeasures

In response to the escalating concerns over the unauthorized use of artists' work to train AI models, a tool named Nightshade has emerged as a technical countermeasure. Nightshade represents a pivotal shift in the digital rights arena, providing artists a means to safeguard their work against unauthorized AI consumption. It embeds stealth alterations in artwork pixels, which corrupt AI learning, resulting in nonsensical outputs. This tool not only shields individual pieces but could inject systemic noise into AI training sets globally.

This tactic is disruptive by design, challenging AI reliability and forcing a reevaluation of data harvesting practices. It's a digital countermeasure, reflecting a broader call to action against the exploitation of creative content. Its widespread adoption could catalyze a new era in AI development, characterized by an arms race between AI advancement and data integrity preservation.

The introduction of Nightshade ushers in a new chapter in the struggle for digital autonomy. It's a manifestation of the growing tension between AI innovation and the rights of content creators. This battle over the digital commons is not just about technology—it's a complex narrative of ethics, ownership, and the evolution of digital consent. Nightshade's deployment may well redefine the power dynamics within the digital ecosystem, sparking a necessary conversation on the ethical use of AI in relation to creative works.

Chapter Wrap-up (so what)

The evidence of misuse is no longer anecdotal but systematic, as seen in deepfakes that blur reality and phishing attacks that are indistinguishable from authentic communications. Regrettably, our existing tools, policies, and governance are not just trailing behind; they are becoming obsolete in the face of an ever-evolving adversary. The speed at which AI is advancing—a pace that is logarithmic rather than linear—suggests that our traditional approaches to control and oversight are woefully inadequate.

Generative AI amplifies the anti-trust dichotomy. It will make us question the very essence of our perceptions. The concept of a 'chain of custody' for information will become obsolete in a world where the origins of our digital interactions are inherently suspect.





Final Thoughts

In 2024, our reality will become a hall of mirrors, each reflection more distorted than the last, challenging the notion of objective truth.

You might ask, "Kris, how are you personally handling this?"

I'm not. I'm struggling just like everyone else.

How do we trust what we hear when voice clips can be stitched together to fabricate a conversation? How do we trust what we see when images can be altered to create scenes that never happened? In a world where fake interactions can be as convincing as real ones, discerning truth requires us to question and verify before we believe.

It’s a profound challenge.

But, let me be clear. Acknowledging the gravity of our situation isn't pessimism—it's a necessary step toward solutions. Openly addressing the challenges with Generative AI and its innate ability to amplify disinformation, misinformation, and deepfakes starts the vital conversation on how we can adapt and evolve our strategies.

What can we do?

This train is moving at breakneck speed, and it shows no signs of slowing down. In this context, we can endeavor to mitigate the negative impacts of Generative AI through a concerted strategy:

  1. We must invest in digital literacy education to help the public discern between authentic and manufactured content. Programs that cover critical thinking, source evaluation, media awareness, information ethics, and cybersecurity and privacy practices.
  2. We must push for technological solutions that can verify the authenticity of digital content. Blockchain and similar technologies have the potential to serve as the vehicle for verifying the authenticity of digital content. But, it's crucial to approach any solution cautiously to ensure we do not inadvertently subscribe to a form of state surveillance that could compromise individual privacy and freedom. The balance between truth verification and personal liberty is delicate and must be navigated with care.
  3. Policy and legal frameworks need to adapt to hold creators and disseminators of deepfakes accountable, but here, too, we must tread carefully. Over-regulation carries the risk of stifling innovation, and, as Dr. LeCun's has aptly noted, over-regulating AI models may limit access to these powerful technologies to those already in power, contravening the principle of democratization.


Disclaimer: The views and opinions expressed in this article are my own and do not reflect those of my employer. This content is based on my personal insights and research, undertaken independently and without association to my firm.



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