Deepfakes: The Unstoppable Technological Shift and Its Societal Implications

Introduction

Deepfakes are a frequent topic in political and media discussions, often framed as a threat that must be banned due to their significant implications. However, rather than being a controllable phenomenon, deepfake technology is rapidly evolving and becoming more accessible to the public, requiring no specialized expertise to create convincing manipulations. This article explores what deepfakes are, how easily they can be accessed, and their broad political and societal ramifications.

We will also examine why deepfakes represent an unstoppable and unregulatable trend, even with significant legislative efforts. Finally, we will discuss how society must adapt to this emerging technology by shifting perspectives on media trust, enhancing critical thinking, and recognizing the broader consequences of living in a world where seeing is no longer believing.

• What Are Deepfakes?
• Accessibility: No Special Expertise Needed
• The Futility of Regulation
• Societal Implications of Deepfakes
• How Society Must Adapt
• The Upsides of This Technology
• Conclusion: Fighting Windmills

What Are Deepfakes?

Deepfakes refer to synthetic media generated using artificial intelligence (AI), particularly deep learning techniques such as deep neural networks and stable diffusion models. These tools allow for the creation of hyper-realistic videos, images, and audio recordings in which individuals appear to say or do things they never actually did. The realism of deepfakes has reached a point where even experts often struggle to distinguish them from genuine media. Originally an experimental AI application, deepfake technology has rapidly evolved into a powerful and accessible tool available to the general public.

Stable diffusion is a generative AI technique that allows for the creation of highly detailed and realistic images by iteratively refining noise into coherent visuals. It uses deep neural networks to learn complex patterns from vast datasets, enabling users to produce believable synthetic media with minimal effort. A deep neural network, on the other hand, is a multi-layered artificial neural network designed to mimic human cognitive processes, making it capable of recognizing and generating intricate features in images, videos, and audio. These technologies together have revolutionized the field of synthetic media, contributing to the near-indistinguishable quality of deepfakes.

LoRAs (Low-Rank Adaptation) and algorithms like FaceSwap, CPDS, and PyraCanny play a crucial role in deepfake technology by enabling the transfer of facial features, posture, and even contextual elements from one image or video to another. FaceSwap allows for seamless facial replacement by mapping key facial points and blending them into a new scene, while CPDS (Context-Preserving Deep Synthesis) ensures that generated content remains consistent with surrounding elements, enhancing realism. PyraCanny is utilized to refine edge detection and detail retention, improving the authenticity of deepfake-generated content.

Furthermore, anyone can train LoRAs or use transfer learning to adapt neural networks for specific applications, even if the original models had been censored. This adaptability makes deepfake technology not only widely accessible but also difficult to regulate or control, as individuals can fine-tune models on their own hardware without external oversight.

Accessibility: No Special Expertise Needed

Contrary to popular belief, deepfake technology is no longer confined to tech labs or experts with advanced AI knowledge. Open-source models, user-friendly applications, and consumer-grade hardware enable almost anyone to create realistic deepfakes. Pre-trained models and software packages are available across the internet, making it possible to manipulate digital content with little more than a basic understanding of AI tools. This democratization of synthetic media generation is what makes it so unstoppable.

Running models does not require special knowledge. The most basic software packages run efficiently on consumer GPUs with as little as 6–12 GB of VRAM or even on CPUs, making them accessible to a broad audience. Many tools now come with single-click installations and intuitive graphical user interfaces (GUIs) designed for ease of use. These GUIs streamline the entire process, enabling users to generate deepfake images and videos with minimal effort. Within a few days of experimentation and learning, anyone can create highly realistic synthetic media in just a few minutes, without needing to write a single line of code.

The Futility of Regulation

Politicians and regulatory bodies have responded to the deepfake phenomenon with attempts to regulate its use—an almost reflexive reaction to any emerging technological challenge. Their approach follows a familiar pattern: if something appears disruptive, attempt to control or outlaw it. However, such reactive measures often fail to address the reality that technology, once widely accessible, cannot be effectively restricted or banned. Proposals range from criminalizing unauthorized deepfake creation to restricting access to AI training data. However, such regulations are fundamentally flawed for several reasons:

• AI models and deepfake tools are widely distributed. Once a model is released, it spreads across countless platforms, making it impossible to recall or restrict. This is simply the nature of the internet, where information flows freely and is inherently difficult to contain. This unrestricted access has historically been a fundamental principle supporting technological freedom, ensuring that innovations are available to all. It also aligns with one of the core ideologies behind modern technology: the belief that access to information and tools should not be limited by gatekeepers but should empower individuals to explore, create, and innovate independently.
• Training deepfake networks is feasible for anyone with mid-range computing power. Attempts to control distribution cannot prevent individuals from running models on personal devices. Some governments have attempted to restrict access to high-end GPUs and TPUs, allowing only trusted partner companies to acquire them. However, this occurs on an industrial scale and serves more as a business advantage rather than offering any real protection against deepfakes or propaganda. Additionally, these GPUs are widely used in other fields, such as scientific simulations, cryptographic computations, and medical research, leading to their classification as dual-use technology. This further complicates any efforts to regulate their availability or prevent their use in AI-based misinformation.
• Monitoring private machine usage is infeasible. No government or entity can fully regulate what people do on their personal computers, making enforcement nearly impossible. Governments have already attempted similar measures in other contexts, such as scanning users’ devices for child pornography, yet even in such cases—where the content is deterministic and well-defined—these efforts have largely failed. The same applies to deepfake generation, where regulation is even more impractical due to the decentralized and adaptable nature of the technology.
• Privacy is one of the most fundamental rights, and any attempt to compromise it sets a dangerous precedent. Granting governments access to personal devices or private data under the guise of regulation will inevitably lead to misuse, regardless of the initial intent. History has repeatedly shown that such powers, once granted, are expanded and exploited over time, turning temporary measures into permanent surveillance mechanisms.

Simply put, deepfakes are here to stay, and no amount of legislation will prevent their widespread use. Efforts to regulate their creation and use are akin to trying to ban encryption—it is a fight against an unstoppable technological force. Just as encryption has safeguarded privacy and secured digital communications despite attempts to control it, deepfake technology represents another frontier where technological freedom prevails over restrictive policies.

Societal Implications of Deepfakes

The pervasive nature of deepfake technology challenges the very fabric of media credibility and trust. Some of the key consequences include:

• Erosion of Photo and Video as Evidence: Courts and legal systems have long relied on visual media as evidence. With deepfakes, any photo or video can be dismissed as fake, making it harder to prove crimes or hold individuals accountable. While photo and video manipulation existed before, it required massive resources and was restricted to large-scale political affairs or high-budget scenarios. Today, deepfake technology has scaled down to a level where a single individual with consumer hardware can create highly convincing forgeries. What once took expert skills and significant financial investment can now be done effortlessly, impacting not just powerful figures but also ordinary individuals at the societal level.
• Political Manipulation: Politicians can be framed with fake statements or actions. Conversely, real recordings of politicians making controversial statements can be discredited as deepfakes, further muddying public discourse. While propaganda has always existed, producing convincing fakes in the past required massive financial resources and coordinated efforts involving multiple actors. Today, with consumer-grade hardware and widely available AI tools, a single individual can generate highly realistic deepfakes, making manipulation easier and more widespread than ever before. This democratization of misinformation no longer affects just large-scale political affairs or corporate interests but extends down to everyday individuals, amplifying misinformation at all levels of society.
• Social Damage Through Fabricated Scandals: From revenge deepfakes to fake confessions, individuals can be falsely accused or humiliated with convincing AI-generated content. This extends beyond simple defamation; deepfake technology enables targeted blackmail and humiliation, particularly in a sexual context. For example, a coworker could be threatened with the release of faked nude images, exploiting the fact that most people have never seen them naked and may assume the images are real. This form of abuse is only effective because society still stigmatizes leaked nudes, making such threats socially and professionally damaging. Furthermore, deepfakes can fabricate meetings between individuals, reinforcing harmful narratives and conspiracies. Society often prioritizes who is involved in an action or interaction rather than critically analyzing the content itself, making this type of manipulation particularly potent.
• Propaganda and Groupthink: The ability to create fake endorsements or inflammatory rhetoric attributed to influential figures fuels misinformation, exacerbating ideological divisions. Society often falls for misinformation if it presents a simple solution or explanation that does not directly affect them. Additionally, people tend to believe falsehoods when they are presented by the right figure, as many operate within a culture of personality-driven trust rather than critical evaluation of facts. This tendency makes deepfakes a powerful tool in reinforcing existing biases and shaping public perception based on group loyalty rather than objective truth.

How Society Must Adapt

Since deepfakes will not and cannot be stopped, society must fundamentally change its approach to information consumption:

• Question Content, Not Just the Source: Instead of relying on the reputation of a person in a video, people must critically analyze whether the content aligns with established facts and logical consistency. This is something that should have already been the norm—trusting a single source of information, even a so-called ‘trustworthy’ one, without cross-checking has always been a dangerous approach. People must learn how to verify information properly, recognize when verification is not possible, and acknowledge that in such cases, they cannot truly know the truth. Decisions should not be built on assumptions about unverified information, no matter how much one wants to believe it.
• Prioritize Objective Evidence Over Media Appearances: Legal systems and media must shift from using videos as conclusive proof to requiring supplementary evidence. Viewers must also adapt by moving beyond believing single video sequences and instead considering the broader context. Proper reasoning and critical thinking should be applied to all media content, acknowledging that any statement—regardless of its source—can be false. Even trusted media outlets or court rulings are not infallible, and individuals must recognize that everything can potentially be wrong. Learning to assess when verification is possible and, crucially, when it is not, is an essential skill to avoid making decisions based on unverified information.
• Ignore Scandalous Deepfakes: Society must collectively recognize that private images and videos, especially scandalous ones, can no longer be taken at face value. If fake nudes become indistinguishable from real ones for example, blackmail and public shaming must lose their effectiveness. This is not an organic shift but a necessary adaptation to prevent escalation. Society must stop giving weight to such fabricated content and refuse to engage in the cycle of judgment and humiliation that empowers these manipulative tactics.

The Upsides of This Technology

While deepfakes and generative AI often draw criticism for their risks, they also offer significant benefits. These technologies streamline content creation, drive innovation, and make various aspects of life more accessible. Large language models provide personalized tutoring, accelerate information processing, improve translation accuracy, and function as intelligent personal assistants. They also enhance creativity by helping users generate structured content quickly and efficiently.

Moreover, image-generation tools like stable diffusion allow individuals to explore artistic expression once reserved for trained professionals. By democratizing creativity, these tools empower users to build their own fantasy worlds, bring ideas to life, and develop unique perspectives. Generative AI removes financial and technical barriers, enabling a wider audience to experiment, invent, and innovate without requiring expensive resources or specialized training.

Though these technologies may challenge traditional artistic professions, they simultaneously expand creative opportunities for many. Previously, creative expression was limited to a select few with the necessary skills and resources, leaving others as passive consumers. Now, AI-driven tools allow anyone to participate in content creation, shifting society from mere consumption to active engagement in the creative process.

Conclusion: Fighting Windmills

Deepfake technology is not a temporary trend but an irreversible paradigm shift. Any attempt to ban or regulate it is as futile as Don Quixote’s battle against windmills. Instead of trying to control an uncontrollable force, individuals and institutions must adapt, fostering a society that is educated in media literacy and critical thinking. People must learn how to analyze digital content beyond its surface, understanding its origins, intent, and technical plausibility.

A crucial part of this adaptation is shifting societal perspectives on blackmailable content and public shaming. As deepfake technology makes it impossible to verify authenticity with certainty, blind trust in media must give way to rigorous scrutiny. Additionally, society must recognize and move beyond its fixation on personality cults and focus instead on evaluating ideas and actions based on merit rather than the identity of the individual involved.

Education must play a central role in this shift—teaching individuals from an early age to question information, recognize biases, and verify claims independently. Without this transformation, society risks being manipulated at an unprecedented scale. The ability to critically evaluate digital content will become one of the most important competencies in the modern era, determining whether deepfake technology is a tool for empowerment or a catalyst for deception and chaos.

This article is tagged:

• Opinion
• Internet