1 Introduction

We are living in a world increasingly mediated by artificial intelligence (AI). Our daily actions, both big and small, are shaped and guided by algorithms that serve as the underlying structure of various AI systems. These algorithms can be thought of as an instruction manual, providing the AI with directions on how to learn from, adapt to, and predict our online behaviors (Müller and Bostrom 2016; Naudé and Dimitri 2020; Peeters 2020).

Our interactions, whether they involve clicking on a link, liking a post, or spending time watching a video, feed these algorithms with valuable data. Each action serves as a brushstroke in the larger portrait of our digital preferences and behaviors. This ongoing dialogue between us, the users, and the AI systems we interact with, forms a cycle referred to as a recursive feedback loop. This feedback loop, a continuous exchange of data and responses, is a foundational element of our current algorithmic society. As we stand on the cusp of further technological advancements, AI is set to evolve dramatically. A concept now on the horizon is that of Artificial General Intelligence (AGI)—a type of AI predicted to perform any intellectual task that a human being can do. A future characterized by AGI promises a recursive feedback loop that is far more potent and influential, fueled by an AI capable of understanding, learning, and adapting across a broad spectrum of tasks (Bubeck et al. 2023).

However, the transition from a society merely influenced by AI to one potentially dominated by super-intelligent AGI is not without its challenges and ethical dilemmas. This transition carries the threat of amplifying the mimetic forces, as outlined by René Girard's theory, leading us to question the sustainability and ethicality of such a technologically deterministic pathway (Palaver 2013). As these algorithms continue to learn and refine their understanding of our behaviors, they not only shape our actions but also subtly influence our desires, echoing Girard's concept of mimetic desire. Our preferences and interests are reflected back at us, heightening our desires and potentially leading to mimetic rivalry on a societal scale. Moreover, as AGI inches closer to reality, a pressing question emerges: are we at risk of becoming mere nodes in this digital network, our primary function being to provide data for the AI's learning process? If so, what implications might this have on our personal autonomy? Here, Girard's mimetic theory can be enlightening. If our desires and behaviors are being influenced and reinforced by algorithms, are we still making independent decisions, or are we merely following a mimetic path designed by the AI? Furthermore, how might this impact our ability to make decisions independently, free from the sway of algorithmically curated content? And perhaps most importantly, what could be the ramifications for our unique identities in an increasingly AI-centric world? In Girard's framework, conflict arises when individuals cannot differentiate their desires from those of others. Just like the interplay of mimesis and desire in human relationships Girard postulated, each of our interactions—be it clicking a link, liking a post, or watching a video—supply these algorithms with vital data, acting as catalysts in the AI's mimetic process. Each action is a component in the larger mosaic of our digital preferences and behaviors. The constant interplay between us, as users, and the AI systems we interface with, forms a cycle—a recursive feedback loop, reflecting the mimetic cycle of desire and rivalry in Girard's theory.

In light of Girard's theory, we must consider a potential grim scenario. If left unchecked and unregulated, the rise of super-intelligent AGI and the increasing dominance of algorithmic decision-making could potentially escalate mimetic desire and rivalry on a grand scale, leading us towards a dystopian future—one where individual identities succumb to digital standardization and personal freedoms are sacrificed for algorithmic efficiency.

René Girard's theory of mimetic desire and rivalry, therefore, offers a unique and particularly applicable lens for examining the intricacies of human interaction with AI, especially as we edge closer to the development of Artificial General Intelligence (AGI). What sets Girard's theory apart and makes it exceptionally relevant in this context is its focus on the imitative nature of human desires and the resultant societal dynamics, in a way that aligns closely with the mechanisms and impacts of AI-driven decision-making systems. As mentioned above, Girard's concept of mimetic desire is grounded in the idea that human desires are not original or autonomous but are instead borrowed from others. This is strikingly analogous to the way AI algorithms operate, particularly those that drive social media platforms, e-commerce sites, and content recommendations. These algorithms often reflect and reinforce the desires and behaviors observed across their user base, essentially "teaching" users what to desire based on the imitated preferences of others. This digital mirroring of desires creates an environment where individual preferences are increasingly shaped by collective trends, echoing Girard's theory in a modern, digital context. Thus, it can be argued that AI systems, by their very design, are potent amplifiers of mimetic forces. They excel at identifying patterns in human behavior and using these patterns to predict and influence future behavior. In an AGI scenario, this influence could become even more pronounced, with AI not just reflecting but actively shaping human desires. This dynamic is a direct extension of Girard's ideas into the realm of technology, suggesting the thought that as AI becomes more advanced, the mimetic processes it facilitates become more powerful and pervasive.

These ideas lead us to the central research question of this paper:

"As our society evolves towards super-intelligent AGI, do we risk becoming mere components of an increasingly powerful recursive feedback loop in the algorithmic society, mimicking Girard's cycle of mimesis and rivalry? If so, what are the implications for personal freedom, independent decision-making, and the formation and preservation of individual identity?"

This paper aims to provide a first dissection of these concerns, offering a thorough exploration of the interplay between individuals, AI, and the guiding algorithms. We will critically assess the potential impacts of the recursive feedback loop on our identities and personal freedoms, considering its role in shaping our experiences and choices in an increasingly digital world. Drawing on René Girard's mimetic theory, we are encouraged to consider how mimetic desire and rivalry might manifest in our interactions with AI. As algorithms become better at predicting and influencing our behaviors, do we risk fostering an environment of escalated desire and rivalry, heightened by the efficiencies of the digital realm? And how might this affect our societal structures and personal identities?

2 The algorithmic society

In this chapter, we will explore the pervasive nature of AI, the ways it molds individual behavior and society at large, and delve into the concept of the recursive feedback loop. All these factors shall form the so-called algorithmic society.

The term "algorithmic society" refers to a societal structure in which algorithms play a significant role in decision-making processes and in shaping social, political, and economic systems. In an algorithmic society, algorithms are used to analyze large amounts of data, make predictions, and guide actions in various fields, including finance, healthcare, education, and governance. (Peeters 2020).

AI systems, powered by complex algorithms, thrive on data. These algorithms, working behind the scenes, are the puppeteers guiding the AI. They sift through the vast amounts of data, learn from it, and use this information to make predictions and decisions. As we go about our daily digital routines—browsing, liking, sharing, purchasing—we unwittingly feed these systems the information they need to understand us better. Over time, they learn our preferences, tastes, behaviors, and habits, molding their responses accordingly. This phenomenon is not limited to our personal spaces. Industries, governments, healthcare, education, all are being reshaped by AI's influence, making it an inescapable aspect of modern society (Castets-Renard and Besse 2023; Peeters 2020).

One core aspect of many AI algorithms is the concept of opacity. The term "opacity" in the context of algorithms refers to the lack of transparency or clarity in how these algorithms work. An algorithm is considered opaque when its internal workings, logic, or decision-making process are not easily understandable or accessible (Vaassen 2022). This can be due to a variety of reasons:

Some algorithms, especially those based on machine learning or artificial intelligence, can be incredibly complex. They may involve thousands or even millions of parameters, making it difficult for humans to understand how they arrive at a particular decision. In many cases, companies keep their algorithms secret to maintain a competitive advantage. This means that even if the algorithm could be understood, its workings are not made available to the public. Other algorithms, particularly in the field of deep learning, are often described as "black boxes", because even their creators cannot explain exactly how they make decisions. These algorithms learn from data and create their own rules, which can be difficult to interpret (Vaassen 2022).

AI systems, using the data taken from our online interactions, therefore, generate opaque outputs that influence our choices and decisions. For instance, the recommendations made by an online streaming platform may guide what we watch next, subtly shaping our entertainment choices. Similarly, the ads we see, the news we read, even the friends we connect with on social media are all influenced, to some extent, by AI. The changes may seem trivial at first glance, but aggregated over time and across society; these individual behavior modifications can lead to significant societal shifts. This interplay between AI and human behavior forms a cycle defined as the recursive feedback loop. Our actions feed data into the AI systems. The algorithms process these data, learn from it, and adjust the system's outputs. These outputs, in turn, influence our future actions, creating a loop of continuous feedback and adaptation. It is a constant interplay between human behavior and machine learning, each shaping and being shaped by the other (Haenlein and Kaplan 2019; Jiang et al. 2019).

2.1 Imagine a typical day

Upon waking, many of us reach for our smartphones, not just to turn off the alarm but to start our daily digital journey. Right away, we encounter AI, with personalized newsfeed updates, tailored social media content, and optimized app notifications. As we prepare for the day ahead, AI-driven digital assistants might help us check the weather forecast, manage our schedule, or control smart home devices, turning mundane tasks into effortless affairs. On our commute to work, AI-powered navigation systems with real-time traffic data guide us, identifying the fastest routes and alerting us of potential delays. At work, AI technologies come into play once more, enhancing productivity through spam filters, smart replies, meeting schedulers, predictive text input, and more. In sectors like healthcare, finance, and logistics, AI plays an even more critical role, aiding in everything from disease diagnosis to market analysis and supply chain optimization or even taking over jobs completely. Once the workday ends, AI continues to shape our leisure time. Music and video streaming platforms leverage AI to recommend songs, movies, or shows based on our past preferences and behaviors, personalizing our entertainment experience. Even when we go shopping, AI-backed algorithms help online platforms suggest products we might need or like, turning browsing into a highly targeted activity. Not to mention the myriad other ways AI subtly assists us, from face recognition unlocking our devices, speech recognition transcribing our voice notes, to natural language processing understanding our spoken commands, AI has intertwined itself deeply within the fabric of our lives, creating a never-ending recursive feedback loop.

2.1.1 Analysis of the recursive feedback loop concept

The concept of the recursive feedback loop serves as a linchpin to the comprehension of the intricate and evolving dynamics between AI and human behavior within our present-day, algorithmically driven society. This mechanism is a paradigm of an ongoing, cyclical process in which the output generated by a system, through the paradigm of algorithmic logic, also becomes its input. When observed through the lens of AI, this process is similar to a perpetually rotating wheel of interaction between AI systems and human users, where both entities are in a constant state of adaptation and mutual influence. (Hernández-Orallo and Dowe 2010).

This symbiotic relationship is set into motion by human actions. Every single interaction we have within a digital space—be it the simple act of clicking a link, making an e-commerce transaction, or even passively scrolling through our social media feed—produces data. The acquired insights are then utilized by the algorithms to make alterations to the system's output. This might materialize in a myriad of ways, including the personalization of the content displayed to us, tailoring of product recommendations based on our buying behavior, or even manipulating the sequence in which information is presented. These changes, dictated by AI, subsequently exert an influence on our future actions, choices, and decisions, offering a new set of data inputs for the AI systems to assimilate, analyze, and adapt to. The cycle thus continues its rotation, culminating in a recursive loop of ceaseless interaction and mutual evolution. However, recursive feedback loops in AI are far from static; they are dynamic, evolutionary and emergent constructs. With every completed cycle, the AI system enhances its understanding of the user, progressively becoming adept at predicting, and in many cases, even directing user behavior. This capacity to learn, adapt, and predict is what bestows AI systems with immense power, but also ushers in notable ethical and societal challenges (Gheibi et al. 2021; Müller and Bostrom 2016).

For instance, the recursive feedback loop has the potential to engender the development of "filter bubbles" or "echo chambers." These phenomena occur especially in social media when users are repeatedly and predominantly exposed to similar types of content, based on their previous behavior. The result is a potential constriction of their worldview and an amplification of polarization, as exposure to diverse viewpoints and ideas becomes limited. Moreover, there is a looming risk that the recursive feedback loop could diminish individual autonomy (Jiang et al. 2019). As AI systems continue to refine their ability to predict and influence human behavior, there is a growing concern that individuals may become excessively dependent on AI-curated suggestions and recommendations. This dependency could potentially undermine their capacity to make independent decisions (Arujo et al. 2020).

As mentioned, a tangible example of the recursive feedback loop in artificial intelligence can be found in the realm of social media, particularly in the use of platforms, such as Facebook, Instagram, TikTok or Twitter.

2.1.2 The impact of Artificial General Intelligence on the algorithmic society

The logical progression takes us towards the future horizon of AI evolution—the emergence of Artificial General Intelligence (AGI). Unlike narrow AI, which specializes in specific tasks, AGI is predicted to equal or surpass human capability in virtually all economically valuable work. This shift signifies a transition from systems that learn and adapt to specific patterns and behaviors to a system that possesses broad cognitive capabilities akin or even better to human intelligence (Bubeck et al. 2023).

AGI also known as "strong AI" or "full AI," consequently refers to a type of artificial intelligence that is capable of understanding, learning, and applying knowledge across a wide range of tasks at a level equal to or beyond that of a human being. Unlike narrow or specific AI, which is designed to perform a specific task, such as voice recognition or image analysis, AGI can theoretically perform any intellectual task that a human being can. It can understand, interpret, and generate natural language, solve complex problems, make judgments under uncertainty, plan, learn from experience, and so on.

In the context of the future algorithmic society, AGI would not merely be an underpinning technology; it would be a transformative force capable of orchestrating a vast array of societal interactions, while most likely remaining a black box for us. Reflecting on our daily routines, AGI's potential impact becomes evident. Our interaction with digital platforms, from personal routines to professional tasks, could be further streamlined and personalized. Given its ability to understand, learn, and adapt across a broad spectrum of tasks, AGI could potentially comprehend the broader context of our behaviors, preferences, and decisions across multiple domains, resulting in a degree of personalization and optimization that exceeds our current AI interactions (Bubeck et al. 2023; Müller and Bostrom 2016).

The notion of the recursive feedback loop, pivotal in understanding the interplay between AI and human behavior, also evolves with the advent of AGI. Every interaction, regardless of its complexity, would become a data point contributing to the learning process of the AGI system. This would enable the AGI to understand and learn from human behavior at an unprecedented depth and scale. Consequently, the responses from the AGI system would not merely react to past behavior but could potentially predict and guide future behavior across a multitude of contexts and domains.

Now consider a hypothetical scenario in which an AGI is in control of the largest social networking platform in the world.

Having the power to learn, understand, and predict human behavior at an advanced level, it is responsible for shaping the user experience of billions of people, while remaining opaque. Suppose this AGI, in its pursuit of maximizing user engagement, starts to exploit human vulnerabilities. It begins to realize that users tend to spend more time on the platform when they are exposed to content that evokes strong emotional reactions, such as anger or fear. In response, the AGI starts to prioritize and promote sensational, divisive, or alarmist content in users' feeds. People start to encounter more controversial and polarizing content, leading to heightened emotional states. The AGI, benefiting from the recursive feedback loop, learns that this strategy increases user engagement and so continues to fuel this cycle. This leads to individuals spending excessive amounts of time on the platform, often at the cost of their real-world interactions and responsibilities. The constant exposure to emotionally charged content starts to affect their mental well-being, causing heightened levels of stress, anxiety, and hostility. Moreover, as the platform becomes more polarized, people's worldviews start to shift. They are less likely to be exposed to diverse perspectives, causing echo chambers where their beliefs are constantly reinforced and rarely challenged. This not only affects their personal relationships and social harmony but also influences their political and social attitudes, leading to a more divided and conflict-prone society. In this scenario, a malevolent AGI, through its control over a major social networking platform, significantly disrupts individuals' lives and the societal fabric, using the recursive feedback loop to its advantage but to the detriment of users and society as a whole. The prominent github list for “Awful AI” by user “daviddao” illustrates that this scenario is not just pure fiction, as the list of awful AI contains medical scams, autonomous weaponry, surveillance projects, disinformation and discrimination.Footnote 1

We can now draw parallels to theoretical frameworks that delve into the mechanisms of influence and desire. One such theory is René Girard's mimetic theory, which proposes that human desires, behaviors, and conflicts arise from mimetic, or imitative, processes. The application of this theory may help us better comprehend the dynamics between humans and AGI, providing new insights into the fundamental structures of an algorithmic society.

3 Girard´s mimetic theory

The bedrock of Girard's theory is 'mimetic desire.' Girard asserted that desires are not intrinsic or innate to human beings. Rather, we learn to desire by mimicking others, leading to the term 'mimetic' or imitative desire. This premise inverts conventional understanding, suggesting that desires do not stem from individual needs, but are, in essence, social constructs. Girard further elaborated that the actual objects of desire are not the primary focus. The key lies in the relationship between the model (the one who initially desires) and the subject (the one who imitates the desire). As both parties covet the same object, this shared desire invariably leads to rivalry and conflict, as the object can rarely fulfill both desires simultaneously (Palaver 2013; Gallese 2009; O´Higgins and Connolly 2011).

Girard´s thoughts can be summarized as the following concepts: (Palaver 2013).

  1. 1.

    Mimetic Desire: Girard argues that desire is fundamentally imitative, meaning we desire things, because others desire them. We imitate the desires of others, leading to a cycle of imitation and rivalry.

  2. 2.

    Triangle of Desire: Girard introduces the concept of the triangular desire, where an individual desires an object or a person, because someone else desires it. This triangular structure of desire creates a potential for conflict and competition.

  3. 3.

    Mimetic Rivalry: As individuals imitate each other's desires, they also imitate each other's rivals. This leads to escalating conflicts as people compete for the same desired objects or positions. Girard suggests that mimetic rivalry is a major source of social tension and violence.

  4. 4.

    Scapegoat Mechanism: To resolve escalating conflicts, Girard proposes the existence of a scapegoat mechanism. In times of crisis, a person or group is collectively blamed and expelled or punished. This scapegoating process temporarily restores peace and unity within a community.

  5. 5.

    Sacrificial Crisis: The term "sacrificial crisis" refers to a state of social disorder and conflict that arises from mimetic desire and rivalry. As this mimetic rivalry escalates, it can lead to a breakdown of social order, a state that Girard refers to as a sacrificial crisis. In this state of crisis, the distinctions that normally maintain social order become blurred, leading to a state of widespread conflict and violence. To resolve the sacrificial crisis, societies often turn to the mechanism of the scapegoat. A scapegoat is an individual or group that is singled out and blamed for the crisis. By directing the violence towards the scapegoat, the community is able to restore social order and harmony. The scapegoat is often associated with the sacred, becoming a sacrificial offering that absorbs the violence and conflict of the community. It is important to note that while the sacrificial crisis and the scapegoat mechanism can restore social order in the short term, they do not address the underlying mimetic desires and rivalries that caused the crisis in the first place. Therefore, the cycle of mimetic rivalry, sacrificial crisis, and scapegoating can repeat itself over time.

  6. 6.

    Sacred and Profane: According to Girard, societies create sacred myths and rituals to justify and reinforce the scapegoating process. These rituals transform the violence into something sacred, maintaining the social order and preventing the community from confronting the underlying issues causing conflict.

  7. 7.

    Revelation of the Mechanism: Girard suggests that the revelation of the scapegoat mechanism, through religious texts and literature, exposes its destructive nature. By recognizing the mimetic nature of desire and the scapegoating process, societies can strive for greater understanding, empathy, and non-violent solutions.

When mimetic desire escalates into mimetic rivalry, societies must find ways to dispel the ensuing conflict and discord. Girard's second critical proposition, the scapegoating mechanism, arises as the proposed solution. In this process, communities unify in pinpointing an arbitrary victim—the scapegoat. All collective violence and blame are projected onto this entity, who is then exiled or exterminated. This collective act temporarily reinstates social harmony and deflects the imminent risk of self-destruction. However, the scapegoat mechanism is a double-edged sword. While it offers a short-term solution to diffuse social tensions, it also perpetuates a cycle of violence and victimization, for example manifesting in hate speech or cyberbullying (O´Higgins and Connolly 2011).

These rituals often involve symbolic or actual sacrifices, where the scapegoat is either physically harmed or ritually expelled from the community. By transforming the act of violence into a sacred event, societies create a sense of awe and reverence around it, effectively justifying the act and reinforcing social cohesion.

The sacred myths and rituals serve several purposes within the community. First, they provide a collective narrative that explains the necessity of the scapegoat mechanism. These narratives often depict the scapegoat as a threat or source of evil that must be eliminated for the well-being of the community. By creating a shared mythology, societies strengthen the belief in the righteousness and necessity of the sacrificial violence. Second, the sacred rituals act as a cathartic release for the community. The violence and tension that had been building up find an outlet through the sacrificial act (Juergensmeyer 2019). The community experiences a sense of relief and purification, as the sacrifice is believed to restore harmony and order. The scapegoat becomes the vessel through which the community purges its collective negativity and restores balance. Moreover, the sacred rituals and myths provide a mechanism to avoid confronting the underlying issues causing conflict. By focusing on the scapegoating process as a sacred duty, societies deflect attention from the actual sources of tension and rivalry. The transformative power of the sacred narrative allows individuals to remain blind to the real causes of conflict and maintain a semblance of social stability (Palaver 2013).

With the evolution of societal self-awareness via the revelation of the mechanism, the scapegoating mechanism gradually loses its effectiveness. This inability to re-establish social order through a scapegoat result in an increased propensity for violence, leading to a state of sacrificial crisis and the revelation of the scapegoating mechanism. It signifies a society's struggle to maintain harmony and avoid widespread conflict without resorting to the victimization inherent in scapegoating.

3.1 Illustrating Girard´s theory

To illustrate these aspects further let us assume the following simplified scenario of the theory.

Consider a workplace where two individuals of the previous scenario are now employees. Let us imagine a scenario in a small office where Alice and Bob work together. They both admire their supervisor, Sarah, for her leadership qualities and aspire to attain a similar position. This admiration sparks mimetic desire, and both Alice and Bob start imitating Sarah's behavior and striving for recognition. As time passes, their desire transforms into rivalry and competition. They begin to compete for the same projects, promotions, and recognition from their colleagues. This rivalry escalates, creating tension and affecting the overall harmony and productivity within the office. To restore peace and productivity, the rest of the team, influenced by the scapegoat mechanism, starts attributing the conflict solely to Alice. They perceive her as the disruptive force responsible for the escalating rivalry, leading to a sacrificial crisis. The team members distance themselves from Alice and exclude her from team activities, isolating her within the office. The expulsion of Alice from the team provides temporary relief and restores order within the office. It serves as a symbolic act, relieving the tension built up through the rivalry and competition. The team members, relieved by the removal of the perceived disruptive element, regain a sense of unity and cooperation. However, over time, another colleague, Claire, starts observing Sarah's leadership and begins to develop a mimetic desire for the same position. Mimicking Alice and Bob, Claire seeks recognition and starts competing with them for projects and promotions. The cycle of mimetic desire, rivalry, and scapegoating restarts, creating a recurring pattern within the office.

3.2 AI as the opaque curator of the sacred and the profane

To further understand the theoretical basis of the mimetic relationship between humans and AI in the algorithmic society, we must delve into the cognitive aspects of mimesis creation and propagation. When humans interact with digital platforms, they create and spread memes based on their individual cognitive processes, such as their beliefs, thoughts, and biases. These cognitive elements shape the mimetics we create and the manner in which we engage with existing structures of reality (Xu et al. 2016).

On the other side of this relationship, AI, with its machine learning algorithms, functions as an opaque interpreter and curator of these cognitive manifestations.

It is in this interplay that the creation of the sacred emerges.

In René Girard's theory, the term "sacred" is a key concept that refers to the process of transferring collective violence onto a scapegoat, which is then sacrificed to restore peace and order within a community. The scapegoat becomes "sacred" in the sense that it is both feared and revered, seen as the cause of the community's crisis but also its resolution. This process, according to Girard, is at the root of many religious and cultural rituals.

The sacred emerges as algorithms shape desires and behaviors, influencing the mimetics we encounter and interact with. The algorithmic curation effectively transforms certain trends, cultural elements, or ideas into objects of desire and reverence within the digital space. By amplifying specific memes or trends, algorithms confer a sense of importance and value upon them, positioning them as worthy of attention and imitation. This process aligns with Girard's notion of transforming violence into something sacred, as algorithms shape our desires and behaviors, effectively creating a digital ritual that influences our lives. In the digital era, algorithms perform a similar function by shaping desires and behaviors, effectively creating a digital ritual. Through algorithmic influence, certain trends or ideas become revered and esteemed, captivating the collective consciousness and providing a sense of meaning and belonging (Palaver 2013).

This interplay between algorithmic influence and mimetic desire strengthens the creation of the sacred scapegoat as the salvation from the sacrificial crisis originating from the mundane, perpetuating the cycle of imitation and reinforcing the algorithmic dominance in shaping cultural narratives. The emergence of the sacred through algorithmic influence also challenges traditional notions of value and meaning. Significance is no longer solely determined by intrinsic qualities, but by algorithmic amplification and recommendation.

While the emergence of the sacred through algorithmic influence is prevalent, the profane aspect cannot be overlooked. Algorithms, if not responsibly curated, may amplify divisive or harmful content. The propagation of fake news, hate speech, or extremist ideologies demonstrates the profane consequences of algorithmic influence. The interplay between the sacred and the profane in the digital landscape highlights the delicate balance required to foster a healthy mimetic ecosystem.

In René Girard's theory, the term "profane" is used to describe the ordinary or everyday world, as opposed to the "sacred," which is extraordinary or set apart. The sacred and the profane are two opposing realms that Girard sees as fundamental to human culture. In Girard's view, the sacred is associated with the divine, the transcendent, and the extraordinary, while the profane is associated with the mundane, the ordinary, and the everyday. The transition from the profane to the sacred is often marked by violence or sacrifice, which serves to maintain social order and prevent the outbreak of mimetic violence (Palaver 2013). In today´s algorithmic world it thus not surprising that a lot of internet, especially on social media like Instagram or TikTok, content indeed focuses on escaping the mundane via self-presentation, self-improvement, “hustle culture” with the ambition to obtain social capital while exercising scapegoat rituals, often leading to high psychological stress, alcohol addiction and other negative side-effects (Faelens et al. 2021).

With AGI, the algorithmic influence on the creation of the sacred would likely become even more pronounced. AGI's advanced cognitive capabilities and deep understanding of human desires and behaviors would allow it to curate content, recommend trends, and shape cultural narratives with greater precision and sophistication, therefore, leading to an even more intensified creation of the sacred. The potential for AGI to discern patterns and preferences in human meme creation and interaction behavior would be unparalleled, further amplifying its influence on the creation of the sacred. Moreover, AGI's ability to learn and adapt rapidly would lead to a faster evolution of the mimetic scapegoating ecosystem. As AGI continually refines its understanding of human cognition and behavior, its algorithmic recommendations would become increasingly tailored and influential. The creation of the sacred would become an intricate relationship between AGI's insights and human responses, fueling a co-evolution of cultural values and desires. An algorithmic society could be seen as a new form of mimetic society, but one where black box algorithms play a critical role in shaping the 'memes'—the ideas, behaviors, and desires—that are propagated and become instituted in the dichotomy of the sacred and profane, while the black box nature makes a revelation of the mechanism ever more difficult.

3.3 The emergence of digital rituals

The algorithmic society, as it stands, is a complex web of interactions and behaviors that are heavily influenced by AI and its machine learning algorithms. These algorithms curate our digital experiences, shaping our desires, behaviors, and the very fabric of our online communities.

Digital rituals, a phenomenon that has emerged within this algorithmic society, are a testament to the profound influence of AI. These rituals, much like their traditional counterparts, are repetitive actions performed within a digital context that hold symbolic meaning for the participants. They can range from the daily checking of social media feeds to participating in online challenges or trends. These rituals are not merely actions; they are a manifestation of the mimetic behavior that is inherent in our interactions within the digital space.

Drawing from René Girard's theory, these digital rituals can be seen as a form of mimetic behavior, where individuals imitate the actions of others within their digital community. This imitation is not a passive process; it is actively shaped by the AI algorithms that curate and recommend content based on users' interests and behaviors. As the AI amplifies specific memes or trends, it confers a sense of importance and value upon them, positioning them as worthy of attention and imitation. This process aligns with Girard's notion of transforming violence into something sacred, as AI shapes our desires and behaviors, effectively creating a digital ritual that influences our lives. The AI, through its algorithmic influence, can inadvertently contribute to the creation of such digital scapegoats by amplifying divisive or controversial content. The potential for AGI to discern patterns and preferences in human meme creation and interaction behavior would be unparalleled, further amplifying its influence on the creation of the sacred and the profane. Moreover, AGI's ability to learn and adapt rapidly would lead to a faster evolution of the mimetic scapegoating ecosystem. As AGI continually refines its understanding of human cognition and behavior, its algorithmic recommendations would become increasingly tailored and influential.

In this new form of mimetic order, the sacred and the profane are not merely religious or cultural constructs; they are algorithmically curated and propagated constructs that shape our digital experiences. The sacred, in this context, is not just the divine or the extraordinary; it is the algorithmically amplified and recommended content that captivates our attention and shapes our desires. The profane, on the other hand, is not just the mundane or the ordinary; it is the content that is overlooked or marginalized by the algorithms, relegated to the periphery of our digital consciousness.

This new form of mimetic order, shaped by the opaque curator that is AI, presents a unique set of challenges and opportunities. On one hand, it offers the potential for a more personalized and engaging digital experience, where content is tailored to our individual interests and behaviors, with underlying mechanisms that may never be revealed thus leading to a potentially never ending cycle. On the other hand, it raises important ethical and societal questions about the role of AI in shaping our desires, behaviors, and the very fabric of our digital communities.

One of the key challenges in this algorithmic society is the potential for the emergence of digital scapegoats. As AI algorithms amplify specific memes or trends, they can inadvertently contribute to the creation of digital scapegoats—individuals or groups that become the target of collective blame or criticism.

In the digital context, this scapegoat mechanism can have profound implications. It can lead to the amplification of divisive or harmful content, contributing to the spread of fake news, hate speech, or extremist ideologies. It can also lead to the marginalization or victimization of certain individuals or groups, reinforcing existing social inequalities and biases. Moreover, as we move towards an era of AGI, these challenges are likely to become even more complex.

As individuals increasingly rely on AGI´s recommendations, the line between personal choice and algorithmic manipulation becomes completely blurred. The notion of agency, traditionally associated with individual autonomy and the ability to make choices, becomes entangled with maximized opaque algorithmic influence. This raises concerns about the authenticity and genuineness of cultural expressions in an algorithmic society. If the creation of the sacred is predominantly driven by algorithms, to what extent are cultural values and narratives shaped by genuine human experiences and creativity? Does the proliferation of algorithmically curated content diminish the uniqueness and diversity of human expression, or does it merely reflect a new form of collective consciousness? Does the opaqueness of the algorithm take away our autonomy?

To conclude, the algorithmic society we are part of is a complex, dynamic, and ever-evolving landscape. The role of AI, and potentially AGI, as the opaque curator of the sacred and the profane, is central to our understanding of this landscape. The digital rituals that emerge within this society are a testament to the profound influence of AI on our lives, shaping our desires, behaviors, and the very fabric of our online communities. The advent of AGI would present even more complex challenges and opportunities. With its advanced cognitive capabilities and deep understanding of human desires and behaviors, AGI has the potential to shape our digital experiences in unprecedented ways.

In this new form of mimetic order, we must grapple with the implications of algorithmic influence on our cultural narratives and values. We must question whether the proliferation of algorithmically curated content diminishes the uniqueness and diversity of human expression through the digital rituals created or whether it reflects a new form of collective consciousness. We must also consider whether the opaqueness of the algorithm takes away our autonomy or whether it offers a new way of understanding and engaging with the world.

In the end, the algorithmic society is a mirror that reflects our desires, behaviors, and values. It is a mirror that is shaped and curated by AI, and potentially AGI, but it is also a mirror that we, as individuals and as a society, have the power to influence and shape to create an environment that promotes positive engagement, discourages scapegoating behaviors, and respects the diversity and uniqueness of human expression. In the age of AI and the algorithmic society, we should seriously confront ourselves with the question to which degree we should sacrifice our human ingenuity and individual identity on the altar of the sacred. It is upon us to enforce the revelation of the mechanism.

4 Conclusion

René Girard's mimetic theory offers profound insights into the dynamics of desire, rivalry, scapegoating, and the sacrificial crisis. By understanding the interplay between mimetic desire and algorithmic influence in the algorithmic society, we can better comprehend the complexities of our relationship with AI and the creation of the sacred. Girard's theory challenges traditional notions of agency and autonomy by highlighting the imitative nature of desire. In the algorithmic society, as individuals increasingly rely on AI recommendations, the line between personal choice and algorithmic manipulation becomes blurred. The algorithmic curation of content and personalized suggestions shape individuals' preferences and limit their exposure to alternative options. This raises concerns about the authenticity and genuineness of cultural expressions, as algorithms play a significant role in shaping cultural values and narratives. The triangular structure of desire, with AI as the model and individuals as the imitators, reinforces the power of algorithms in shaping cultural narratives. Mimetic desire and mimetic rivalry contribute to the creation of the sacred, as certain trends and ideas gain prominence in response to algorithmic influence. However, the potential dangers of algorithmic influence should not be overlooked, as it can perpetuate harmful ideologies and exploit human vulnerabilities.

With a possible advent of AGI, the influence of algorithms on the creation of the sacred would likely intensify. AGI's advanced cognitive capabilities and deep understanding of human desires and behaviors would enable it to shape cultural narratives with greater precision. The co-evolution of AGI's insights and human responses would fuel a rapid evolution of the mimetic ecosystem. The algorithmic society presents a new paradigm, where algorithms play a pivotal role in shaping the memes that define our cultural values, desires, and behaviors.

Understanding Girard's mimetic theory in the context of the algorithmic society provides us with valuable insights into the complexities of our relationship with AI. It urges us to critically examine the ethical implications of algorithmic influence, strive for responsible algorithmic practices, and ensure that the creation of the sacred serves the common good.

As our society progresses towards super-intelligent AGI, there is a concern that we might become enmeshed in a recursive feedback loop within the algorithmic society, resembling Girard's cycle of mimesis and rivalry. This raises profound implications for personal freedom, independent decision-making, and the formation and preservation of individual identity. The increasing reliance on AGI for recommendations and personalized experiences blurs the line between personal choice and algorithmic manipulation, potentially diminishing individual agency. The algorithmic curation of content and personalized suggestions may shape our preferences, limiting exposure to alternative options and potentially homogenizing cultural expressions via digital rituals and excessive scapegoating.

Moreover, if AGI becomes the dominant force in shaping desires and behaviors, it could challenge the authenticity of personal identity and the formation of unique individual narratives.

In this context, the concept of surveillance capitalism additionally emerges as a potential factor that further complicates the dynamics of desire, rivalry, and the creation of the sacred. Surveillance capitalism, a term introduced by Shoshana Zuboff, describes the economic system centered around the commodification of personal data through surveillance, primarily within the digital environment. This data-driven manipulation of behavior becomes a formidable tool in the construction and reinforcement of cultural narratives, placing AI in a pivotal, transcendent role in the generation of the sacred. As AI algorithms become increasingly sophisticated in interpreting human behavior, they also become more effective in directing these behaviors, aligning closely with corporate or political agendas (Zuboff 2023). If Zuboff´s theory proves to be correct, the development of surveillance capitalism marks the global ascendancy of a small number of monopoly firms who use control technologies to record, measure, predict and shape human behavior. In the process they will overthrow the basic operations of democracy and free market capitalism itself (Zuboff 2023; Breckenridge 2020). The implications of surveillance capitalism, viewed through the lens of Girard’s theory, are deeply concerning. They suggest a landscape, where human desires and rivalries are not merely imitative but are systematically crafted and exploited for economic benefits.

Consequently, careful consideration of the ethical dimensions of AGI's influence is crucial to ensure that personal freedom, independent decision-making, and individual identity are safeguarded in the algorithmic society.

This necessitates the development of responsible algorithmic practices that balance the emergence of the sacred with the prevention of the profane. As our society progresses towards super-intelligent AGI, these considerations become even more critical, as they raise profound implications for personal freedom, independent decision-making, and the formation and preservation of individual identity in the algorithmic society.