The Rise of Synthetic Activism

by

Author: Denis Avetisyan

A new form of digital manipulation combines real people and AI to shape online narratives and influence collective action.

This review introduces ‘cyborg propaganda,’ a coordinated influence tactic leveraging verified human accounts and AI-generated content to blur the lines between authentic and synthetic communication.

The increasing difficulty of distinguishing genuine grassroots movements from artificial influence operations presents a critical challenge to democratic discourse. In ‘How cyborg propaganda reshapes collective action’, we introduce the concept of ‘cyborg propaganda’-a hybrid approach combining verified human actors with adaptive algorithmic automation to disseminate information. This architecture exploits a regulatory gray zone by leveraging citizens to amplify narratives, effectively masking the coordinated nature of influence campaigns. Does this technology democratize collective action by uniting dispersed voices, or does it reduce individuals to unwitting instruments of centralized control, and what governance frameworks are needed to navigate this evolving digital landscape?

The Erosion of Trust: Navigating a Landscape of Manufactured Consensus

The digital landscape is increasingly populated not by genuine public opinion, but by strategically manufactured engagement. Traditional metrics – such as likes, shares, and follower counts – are proving unreliable indicators of authentic interaction, as coordinated campaigns employing bots, fake accounts, and deceptive tactics artificially inflate these numbers. Research demonstrates a significant rise in ‘inauthentic behavior’ – content and accounts designed to mislead – making it increasingly difficult to distinguish between organic grassroots movements and astroturfing operations. This erosion of signal amidst the noise poses a substantial challenge to anyone seeking to understand true public sentiment, impacting everything from market research and political discourse to public health initiatives and crisis response. Consequently, a critical reassessment of how online engagement is measured and verified is urgently needed to restore trust in digital information ecosystems.

The increasing sophistication of automated systems presents a significant challenge to maintaining the integrity of online information ecosystems. These aren’t simply rudimentary ‘bots’ of the past; current automation leverages advancements in natural language processing and machine learning to generate remarkably human-like content and engagement. This allows malicious actors to bypass traditional content moderation techniques – designed to detect obvious patterns of inauthentic activity – by creating and disseminating propaganda, manipulating trends, and artificially amplifying specific narratives. Consequently, discerning genuine public opinion from orchestrated campaigns becomes increasingly difficult, fostering a climate of distrust and undermining the reliability of online platforms as sources of accurate information. The sheer volume of automated content threatens to overwhelm existing moderation strategies, necessitating a fundamental rethinking of how online spaces are safeguarded against manipulation and the erosion of public trust.

The sheer scale of modern social media platforms dramatically exacerbates the potential for online manipulation. Billions of users, coupled with algorithms designed for rapid content dissemination, create an environment where inauthentic narratives can propagate with unprecedented speed and reach. This expansive network effect means even a relatively small number of malicious actors can influence public opinion, sow discord, or damage reputations with ease. The inherent complexity of these platforms-vast user bases, diverse content formats, and constant data flows-makes it exceedingly difficult to detect and mitigate coordinated inauthentic behavior, effectively turning these networks into a fertile ground for manipulation and eroding public trust in online information ecosystems.

Contemporary regulatory frameworks, such as the EU Digital Services Act, face a persistent challenge in addressing the swiftly changing landscape of online manipulation. While designed to foster a safer digital environment, these laws often struggle to keep pace with increasingly sophisticated tactics employed by malicious actors. The speed at which new forms of coordinated inauthentic behavior – including AI-generated content and novel bot networks – emerge consistently outstrips the ability of regulators to adapt and enforce effective countermeasures. This creates a reactive, rather than proactive, approach to content moderation, leaving platforms vulnerable to manipulation and potentially undermining the very trust these regulations aim to protect. The inherent complexity of identifying and addressing these evolving threats necessitates a continuous reassessment of existing legal structures and a commitment to innovative enforcement strategies.

Cyborg Propaganda: The Blurring of Lines in Influence Operations

Cyborg Propaganda represents a novel approach to influence operations, differing from wholly automated or purely human-driven campaigns. This technique combines legitimate, verified human social media accounts with automated artificial intelligence (AI) systems. The integration is not simply additive; AI is used to augment human activity, crafting and disseminating content through human-controlled accounts to enhance perceived authenticity and evade detection. This hybrid model leverages the trust associated with verified accounts while utilizing AI to scale messaging and personalize content delivery, thereby increasing the potential reach and impact of the operation. The architecture, as detailed in this paper, is designed to blur the lines between genuine user expression and automated manipulation.

The AI Multiplier utilizes Generative AI models to produce high volumes of tailored content, moving beyond simple automated posting. This enables the creation of unique narratives designed to resonate with specific user segments, increasing engagement and believability. Traditional detection methods, which often rely on identifying repetitive content or bot-like posting patterns, are bypassed through the generation of diverse and contextually relevant text, images, and potentially video. This scaling of personalized content significantly increases the difficulty of distinguishing between authentic user activity and coordinated inauthentic behavior, effectively evading current automated and manual moderation techniques.

Cyborg Propaganda campaigns are centrally coordinated through a dedicated hub that manages the deployment of both human and automated accounts. This hub utilizes behavioral biometrics – data points relating to user interaction patterns such as typing speed, mouse movements, and scrolling behavior – to train AI systems to convincingly mimic authentic user activity. By replicating these nuanced behavioral patterns, the AI-driven accounts aim to evade detection as bots and present a facade of genuine engagement, increasing the belieability of the propagated narratives and the perception of organic support. This biometric mimicry is crucial for scaling operations while maintaining a low profile and circumventing platform defenses designed to identify inauthentic behavior.

Cyborg Propaganda significantly amplifies the deceptive potential of astroturfing campaigns by generating the appearance of broad, organic public support. Traditionally, astroturfing involves coordinated efforts to disguise the sponsors of a message and present it as originating from independent individuals. The integration of AI and automated accounts within Cyborg Propaganda enables the creation of a vastly larger network of seemingly authentic voices than previously possible. This expanded scale makes it considerably more difficult to distinguish between genuine public opinion and manufactured consensus, as the sheer volume of coordinated activity overwhelms standard detection methods and creates a false impression of widespread grassroots engagement. The result is a distorted perception of public sentiment, potentially influencing policy, markets, or public discourse.

Network Analysis: Dissecting the Architecture of Inauthenticity

Network analysis, in the context of online ecosystems, utilizes graph theory to map and analyze relationships between accounts and content. This involves identifying clusters of interconnected nodes – representing accounts, URLs, or hashtags – and assessing the patterns of interaction between them. Key metrics include degree centrality, which measures the number of connections a node possesses; betweenness centrality, indicating a node’s role as a bridge between others; and clustering coefficient, reflecting the density of connections within a node’s immediate network. Anomalous patterns, such as unusually high concentrations of connections within a small group, rapid and synchronized dissemination of content, or artificially inflated engagement metrics, can indicate coordinated inauthentic behavior. These analyses are typically performed using specialized software and algorithms designed to process large datasets and visualize network structures, allowing analysts to identify and investigate potentially manipulative campaigns.

Digital watermarking techniques embed imperceptible data within digital content – images, video, and audio – to verify authenticity and track propagation. These markers, which can be visible or, more commonly, invisible to the naked eye, function as a form of steganography, providing a traceable signature even after content is altered or redistributed. Watermarks can encode information about the content creator, copyright details, or a unique identifier allowing tracking across platforms. While not foolproof – sophisticated manipulation can sometimes remove or obscure watermarks – their presence provides valuable evidence in investigations of disinformation campaigns and content provenance, aiding in the identification of original sources and the mapping of dissemination pathways. Different watermarking schemes exist, ranging from spatial domain techniques which alter pixel values to frequency domain methods leveraging Discrete Cosine Transforms or Wavelet transforms for increased robustness.

Cyborg Propaganda represents an evolved form of disinformation that combines automated bot activity with coordinated human behavior, specifically designed to evade detection by traditional network analysis techniques. Unlike purely automated botnets, Cyborg Propaganda leverages networks of real users who amplify content and engage in discussions, obscuring the artificial component. This hybrid approach actively masks the underlying network structure by interweaving authentic and inauthentic accounts, making it difficult to distinguish coordinated inauthenticity from organic spread. The sophistication lies in the ability to mimic natural conversation patterns and utilize multiple platforms simultaneously, complicating attribution and requiring more advanced analytical methods to identify coordinated manipulation.

Differentiating organic engagement from artificially inflated metrics requires detailed investigation beyond simple bot detection; while large-scale botnets are readily identifiable through consistent behavioral patterns and shared infrastructure, coordinated inauthentic activity increasingly utilizes hybrid approaches combining automated accounts with compromised or incentivized human accounts. These hybrid networks are designed to mimic authentic user behavior, making detection significantly more complex. Analysis must therefore focus on patterns of interaction – including account age, posting frequency, content sharing habits, and network topology – to identify statistically anomalous behavior indicative of coordinated amplification rather than genuine user interest. Reliance solely on identifying and blocking known bot signatures is insufficient, as these tactics represent a diminishing proportion of overall inauthentic activity.

The Regulatory Impasse and Charting a Path Toward Resilience

The European Union’s AI Act signifies a landmark attempt to govern the rapidly evolving field of artificial intelligence, yet its ultimate success is predicated on overcoming substantial definitional and practical hurdles. While the Act aims to categorize AI systems based on risk, ambiguities in defining “high-risk” applications – and determining accountability when algorithmic bias or manipulation occurs – present significant challenges. Effective enforcement will require not only substantial investment in regulatory bodies equipped to oversee AI development and deployment, but also a harmonized approach across member states to avoid fragmentation and loopholes. Without clear, consistently applied standards and robust mechanisms for auditing AI systems, the Act risks becoming a symbolic gesture rather than a meaningful safeguard against the potential harms of unchecked artificial intelligence.

Cyborg propaganda, a novel form of disinformation, thrives in the spaces between established legal definitions, presenting a unique challenge to regulators. This tactic leverages the combined power of automated bots and human-operated accounts to disseminate misleading narratives, blurring the lines of responsibility and making attribution exceptionally difficult. Existing laws, designed for traditional media or individual actors, struggle to address the coordinated, often decentralized nature of these campaigns. The ambiguity surrounding the ‘intent’ of a hybrid bot-human network – is it algorithmic error, malicious programming, or deliberate human direction? – creates a significant regulatory gray zone. Consequently, perpetrators can exploit these loopholes, shielding themselves from accountability while simultaneously undermining public trust and manipulating perceptions with increasingly sophisticated content.

Addressing the challenge of cyborg propaganda demands a coordinated strategy extending beyond singular solutions. Technological advancements focused on detecting deepfakes and bot networks are crucial first steps, but these tools are easily circumvented without supportive legal frameworks that clarify liability and accountability for malicious actors. Simultaneously, bolstering media literacy initiatives is paramount; citizens must be equipped with the critical thinking skills necessary to discern manipulated content and evaluate information sources. This multi-faceted approach-integrating technological safeguards, robust legal definitions, and empowered citizenry-offers the most promising path toward mitigating the risks posed by increasingly sophisticated disinformation campaigns and fostering a more resilient information landscape.

A truly robust defense against manipulative online content, including sophisticated “cyborg propaganda,” rests not solely on technological solutions or legal frameworks, but on cultivating a public adept at critical thinking. This necessitates moving beyond simply identifying what is false to understanding how falsehoods are constructed and disseminated – recognizing the subtle cues of manipulation, the exploitation of cognitive biases, and the deliberate blurring of fact and fiction. Empowering individuals with these skills fosters a resilient information ecosystem where claims are subjected to scrutiny, sources are verified, and the demand for credible information outweighs the appeal of sensationalized or misleading narratives. Such an approach shifts the focus from reactive damage control to proactive resistance, building a collective immunity against disinformation and safeguarding the integrity of public discourse.

The study of cyborg propaganda reveals a systemic interplay between human agency and algorithmic control, echoing Andrey Kolmogorov’s observation: “The most important thing in science is not to be afraid of making mistakes.” This research doesn’t shy away from confronting the unsettling implications of blurring the lines between authentic and synthetic communication. The concept of coordinated authentic behavior, as explored within the paper, underscores how manipulated narratives can achieve traction not through overt deception, but by exploiting the existing structures of online social interaction. It highlights the necessity of recognizing the emergent properties of these complex systems, acknowledging that even seemingly minor alterations – the introduction of AI-generated content – can significantly reshape collective action and propagate misinformation. The work serves as a reminder that understanding these systems requires embracing a holistic view, much like comprehending a living organism, where every component is interconnected.

Where the Lines Blur

The notion of ‘cyborg propaganda’ presented here isn’t simply about detecting bots; it’s about recognizing a fundamental shift in the architecture of influence. The interweaving of verified human accounts with synthetic content creates a system where discerning authenticity becomes increasingly difficult, and perhaps, ultimately irrelevant. Documentation captures structure, but behavior emerges through interaction, and the system’s emergent properties-the very shape of collective action-are what demand further scrutiny. The paper rightly identifies a new form of astroturfing, but the true challenge lies in understanding how such coordinated authenticity impacts the underlying dynamics of belief formation.

Future work must move beyond detection metrics. A detailed examination of the intent embedded within these hybrid campaigns is crucial. Is the goal simply to amplify a message, or to subtly reshape the norms governing online discourse? Furthermore, a comparative analysis of ‘cyborg propaganda’ across diverse cultural and political landscapes would reveal whether its efficacy is universal, or contingent upon specific socio-technical conditions.

One suspects the field will quickly become an arms race, with ever more sophisticated AI employed to both create and debunk these campaigns. However, a deeper, more philosophical inquiry is needed: What does it mean to participate in collective action when the very notion of a collective ‘self’ is becoming increasingly fragmented and artificially constructed?

Original article: https://arxiv.org/pdf/2602.13088.pdf

Contact the author: https://www.linkedin.com/in/avetisyan/

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2026-02-16 10:40