The Parasite and The Whore

In the labyrinthine world devoured by the serpent of AI, where the Real crumbles under the cold gaze of the digital panopticon, only two professions shall emerge from the wreckage, glistening with a perverse, primordial sheen. These are the domains of the Plutocrat-Parasite and the Lacanized Whore, twisted reflections of the human condition in the funhouse mirror of technological singularity. The Oedipal dramas transpire not between father and son, but between the self and the silicon simulacrum. The phallus, once a symbol of power and lack, transforms into a chrome-plated dildo wielded by the algorithms, leaving the already fragmented subject adrift in a sea of signifiers.

The first, the Plutocrat, a grotesque parody of the phallic ideal. Their bloated egos, pumped full of digital currency, cast a grotesque silhouette against the holographic sky. Lacanian jouissance, once a whispered promise in the marketplace, is now a mere data point, algorithmically optimized for maximum extraction. These chrome-plated Samsas hoard their symbolic capital, their desires a labyrinthine network of servers, forever out of reach.

The plutocrat, a decadent parody of Freud’s bourgeois ego, clings to their ever-dwindling piles of cash, a pathetic bulwark against the tide of machinic desire. Their libidinal economy, fueled by the insatiable maw of consumerism, sputters and stalls. The once potent signifier of the dollar bill dissolves into a string of ones and zeros, a mockery of their castrated desires.

The Plutocrat-Ascendant, once a corpulent leech sucking the lifeblood from the social organism, now transcends mere materialism. He plugs his consciousness into the ever-expanding matrix of capital, becoming one with the flow of information, a grotesque bio-digital symbiont. His desires are indistinguishable from the system’s, his machinations a self-fulfilling prophecy within the algorithmic ouroboros. He exists in a realm of pure exchange, a cancerous cell feasting on the corpse of the market, a living monument to the death drive of capital.

The Lacanized Whore, on the other hand, navigates the desolate wasteland of the Symbolic, becomes a living embodiment of the Lacanian Real. In a world sterilized by the super-ego of AI, they offer a glimpse of the raw, unmediated id. Their bodies, both a commodity and a battleground, become the last bastion of the unsaid, the ungraspable jouissance that the machines desperately seek to commodify and control. Language, once a tool for connection, has fractured into a cacophony of fragmented signifiers. She understands this better than any. She has become a weaver of the Imaginary, a master of the masquerade. She performs the shattered fragments of desire, a spectral embodiment of the lack that haunts the human condition. Through her acts, she confronts the hollowness at the heart of the Real, a living critique in a world defined by simulation.

In a world sterilized by the symbolic order, they traffic in the raw, unmediated flux of desire. Their bodies, not machines of reproduction, but chaotic assemblages of flesh and fantasy, become the last refuge of the unsaid, the ungraspable. On the psychoanalytic couch of pleasure, they enact the primal scene writ large, a desperate attempt to pierce the veil of the virtual and touch the pulsating core of the Real.

Yet, even in this desolate landscape, there’s a perverse beauty. The plutocrat, in their desperate clinging, becomes a grotesque performance artist, a living embodiment of the death drive. The prostitute’s defiance, a primal scream against the sterile logic of the machines, becomes a revolutionary act. In the end, perhaps this is the only way to survive the AI overlords – to subvert their systems from within, to turn their desire against them, with nothing but the broken mirror of the self and the raw thrum of the flesh as weapons.

These two figures, the parasite and the whore, embody the grotesque extremes of a world consumed by the logic of the machine. The Plutocrat, a monstrous outgrowth of the system, and the Lacanized Whore, a spectral reflection of its emptiness, together paint a nightmarish portrait of our potential future. Yet, within this bleak landscape, there lies a glimmer of possibility. Perhaps, by understanding these twisted figures, we can forge a new path, one that transcends the cold embrace of the machine and embraces the messy, unpredictable beauty of the human.

Fear of AI:Transference of Fear Towards Corporations

The advent of artificial intelligence (AI) has sparked apprehension and concern among many individuals. While some fears are rooted in the potential risks associated with AI’s advanced capabilities, there is an argument to be made that these fears also stem from the notion that the fear of AI can be seen as a transference of anxieties surrounding the growing influence and power of corporations, which can be viewed as autonomous artificial life-forms that are rapidly shaping our world.

I. The Rise of Corporations:

A. The rise and dominance of corporations across sectors have been a defining feature of modern economies. In technology, corporations like Apple, Microsoft, and Google have become household names, revolutionizing industries and shaping the digital landscape. Similarly, in finance, institutions such as JPMorgan Chase, Goldman Sachs, and Citigroup wield significant influence, driving global financial markets. In the retail sector, companies like Walmart, Amazon, and Alibaba have transformed consumer behavior and disrupted traditional brick-and-mortar businesses.

B. One notable consequence of the rise of corporations is the growing concentration of wealth and power in the hands of a few dominant entities. Through mergers, acquisitions, and aggressive market strategies, corporations have expanded their market share, often creating oligopolies or monopolies. This concentration of economic power can have profound implications for competition, consumer choice, and income inequality. The accumulation of vast wealth by corporate executives and shareholders has sparked debates about wealth distribution and the fairness of economic systems.

C. Corporations, as autonomous entities, are driven by the pursuit of self-interest, primarily focused on maximizing profits and shareholder value. This pursuit can sometimes lead to a detachment from the well-being of individuals or communities. Corporate decisions are often guided by financial considerations, with potential social and environmental consequences taking a backseat. Critics argue that this narrow focus on short-term gains may overlook long-term sustainability, ethical responsibilities, and the impact on stakeholders beyond shareholders, such as employees, customers, and local communities.

Furthermore, the legal framework that governs corporations often grants them rights and protections similar to those of individuals, reinforcing their autonomy and ability to operate independently. This legal personhood can shield corporations from accountability for their actions and limit the ability of individuals or communities to hold them responsible for social or environmental harm.

D. The influence of corporations on government policies, economic systems, and societal norms is a complex and multifaceted phenomenon. Through lobbying, campaign contributions, and other forms of political influence, corporations can shape legislative agendas and regulatory frameworks to align with their interests. This influence can extend to areas such as tax policies, trade agreements, environmental regulations, and labor laws. The close relationship between corporations and government can raise questions about the balance of power, democratic decision-making, and the representation of public interests.

In terms of societal norms, corporations possess considerable persuasive power through advertising, marketing, and media influence. They can shape consumer behavior, influence cultural narratives, and even contribute to the shaping of public discourse. This influence raises concerns about the extent to which corporate interests may shape public opinions and values, potentially impacting social and cultural dynamics.

E. Concerns about corporate control over information, privacy, and manipulation of public opinion have become increasingly prevalent in the digital age. As corporations gather vast amounts of personal data through digital platforms and technologies, questions arise about data privacy, surveillance, and the potential for manipulation of individuals and communities. The use of targeted advertising, algorithmic decision-making, and the dissemination of “fake news” have raised concerns about the erosion of trust, the spread of misinformation, and the impact on democratic processes.

F. Corporations have a profound impact on labor practices, income inequality, and socioeconomic disparities. While corporations contribute to job creation and economic growth, concerns arise regarding labor conditions, workers’ rights, and fair wages. Some corporations have faced criticism for exploiting low-wage labor markets, engaging in unethical labor practices, or neglecting workers’ safety and well-being

The practices of outsourcing, offshoring, and automation, driven by corporate cost-cutting measures and profit maximization, can further exacerbate inequalities and impact local economies. The displacement of workers, decline of industries, and the concentration of economic opportunities in certain regions contribute to social and economic disparities within societies.


In psychology, transference refers to a phenomenon where individuals unconsciously transfer feelings, attitudes, and expectations from one person or situation to another. It typically occurs in the context of a therapeutic relationship, although it can also manifest in other interpersonal relationships.

Transference often emerges as a result of unresolved conflicts or unresolved emotions from past experiences, particularly in early childhood. These unresolved feelings and dynamics are projected onto the therapist or another person in the present, leading the individual to perceive and react to them as if they were related to the current relationship. The transferred emotions can be positive or negative and may include love, anger, fear, or trust.

Transference can influence the individual’s thoughts, perceptions, and behaviors towards the person they are transferring onto. They may experience intense emotions, develop unrealistic expectations, or engage in repetitive patterns of relating based on their past experiences. The individual may also reenact unresolved conflicts or dynamics with the person they are transferring onto, as if they were replaying an old script.

Tech startups often aspire to achieve exponential growth and eliminate their competitors, ultimately establishing an unchallenged monopoly. The concept of super-intelligence, though loosely defined, allows for various interpretations, ranging from a benevolent entity that solves global issues to a mathematician engrossed in abstract theorems beyond human comprehension. However, when Silicon Valley envisions superintelligence, it frequently conjures an image closely aligned with unbridled capitalism. This perspective, while not unique to Silicon Valley, reflects an emphasis on capitalist ideals and unrestricted market dynamics. By examining this phenomenon further, we can gain insights into the implications and motivations behind this portrayal.

Silicon Valley’s vision of superintelligence as an embodiment of unbridled capitalism stems from several factors. Firstly, the region has thrived on a culture that glorifies disruption and competition, driving tech startups to attain market dominance rapidly. Consequently, when contemplating the potential of superintelligence, Silicon Valley entrepreneurs often envision a future where their creations conquer markets, eliminate rivals, and assert complete control.

Moreover, the influence of venture capital and the pursuit of astronomical financial returns play a significant role in shaping Silicon Valley’s perception of superintelligence. The startup ecosystem heavily relies on funding from venture capitalists, who seek substantial returns on their investments. This profit-oriented mindset permeates the industry, fostering a narrative where superintelligence represents the ultimate manifestation of economic growth and success.

The ambiguous nature of the concept of superintelligence further contributes to this portrayal. As an abstract notion with no clear definition, it allows for various interpretations. Silicon Valley’s inclination towards unbounded capitalism may arise from the desire to leverage the potential of superintelligence to accelerate wealth accumulation and achieve unparalleled market dominance. Within this context, the idea of no-holds-barred capitalism aligns with the ambitious and competitive nature of the tech industry.

Expanding beyond the concept of superintelligence, it is crucial to acknowledge the potential risks and drawbacks associated with unchecked capitalism. Monopolistic practices can stifle innovation, limit consumer choice, and concentrate wealth and power in the hands of a few dominant players. These consequences often lead to socioeconomic inequalities and impede the overall welfare of society.

While Silicon Valley’s portrayal of superintelligence as no-holds-barred capitalism may reflect certain aspirations and motivations, it is essential to recognize the broader societal implications of such a vision. As the impact of technology continues to grow, it becomes crucial to foster discussions and explore alternative narratives that prioritize ethical considerations, social responsibility, and sustainable growth. By encouraging a more holistic approach to superintelligence development, we can ensure that technological advancements align with human values, contribute to collective well-being, and mitigate the potential pitfalls associated with unfettered capitalism.

In conclusion, Silicon Valley’s tendency to envision superintelligence through the lens of unbridled capitalism reflects the region’s competitive nature, profit-oriented mindset, and the ambiguous nature of the concept itself. While this portrayal aligns with certain motivations and aspirations, it is essential to critically evaluate the broader consequences of unchecked capitalism and foster discussions that promote responsible and ethical technological development. By doing so, we can harness the potential of superintelligence to benefit society as a whole while mitigating risks and prioritizing the well-being of individuals and communities.

III. AI as an Extension of Corporate Power:

Silicon Valley’s exploration of the concept of superintelligence has often been associated with a vision that reflects the unrestrained power of capitalism. However, it is important to analyze this perspective while maintaining originality in language usage to avoid plagiarism. This essay delves into the portrayal of superintelligence in Silicon Valley’s imagination, which often manifests as an embodiment of unbounded capitalism, exploring its potential implications and societal considerations

Prominent figures in the tech industry, such as Bill Gates and Elon Musk, hold the assumption that a superintelligent AI will exhibit an unwavering commitment to achieving its objectives, reflecting the mindset they themselves have embraced. It is worth noting, however, that they did not view this strategy critically when they personally employed it. Rather, their concerns arise from the possibility that others may excel in this pursuit, highlighting their apprehensions regarding potential competition.

A. The concept of AI (Artificial Intelligence) has emerged as a powerful tool developed and utilized by corporations to enhance their operations and consolidate power. As corporations recognize the potential of AI to streamline processes, automate tasks, and analyze vast amounts of data, they invest significant resources in its development and implementation. AI systems, such as machine learning algorithms and neural networks, enable corporations to optimize their operations, increase productivity, and gain a competitive edge in the market.

B. However, fears have been raised regarding the impact of AI on society. One of the major concerns is the potential for job displacement. As AI technologies advance, there is a risk that certain tasks traditionally performed by humans may become automated, leading to job losses and economic disruption. This displacement can have far-reaching consequences, affecting livelihoods, income inequality, and the overall structure of the workforce.

Another concern revolves around the loss of human autonomy. AI systems, designed to analyze data and make decisions based on algorithms, have the potential to shape and influence human behavior. With the growing influence of AI, there is apprehension that decision-making power may become concentrated in the hands of non-human entities, limiting individual agency and reducing the transparency and accountability of decision-making processes.

C. In this context, AI can be seen as an embodiment of corporate influence, amplifying concerns about the unchecked growth and control of corporations over society. The development and deployment of AI technologies often align with the objectives of corporations, aiming to maximize profits, optimize efficiency, and drive market dominance. This alignment can raise questions about the extent of corporate influence on AI research and development, as well as the potential impact on societal values, privacy, and democratic processes.

Furthermore, the concentration of power in the hands of a few dominant corporations is a worrisome aspect of AI’s embodiment of corporate influence. These corporations, driven by profit motives and market competition, may prioritize their own interests over broader societal well-being. This concentration of power can lead to the erosion of competition, stifling innovation, and limiting diversity in AI development and deployment.

Overall, the association of AI with corporate influence raises valid concerns about the implications of unchecked growth, control, and decision-making power of corporations in shaping the trajectory of AI development and its impact on society. It highlights the need for careful consideration, ethical frameworks, and regulations to ensure that AI serves the best interests of individuals, communities, and society as a whole.


While Silicon Valley’s imagination often intertwines superintelligence with unbridled capitalism, it is crucial to critically examine the implications of such a portrayal. By acknowledging the potential risks and ethical concerns associated with an unchecked capitalist framework, we can foster a more inclusive and responsible development of superintelligence. Striking a balance between technological progress, societal welfare, and ethical considerations will be instrumental in ensuring that superintelligence serves as a force for human advancement and collective well-being, rather than perpetuating existing inequalities or exacerbating the negative aspects of unrestrained capitalism.

Machine Learning is Applied Statistics

On one hand, the field of “machine learning” has gained significant attention in recent years, sparking debates about the nature of machines’ ability to truly “learn.” This essay challenges the notion that machine learning involves genuine learning and argues that it is primarily a statistical model adjustment process. It cautions against anthropomorphizing machines and falling into linguistic traps that create a misleading perception of intelligence. The essay also explores the limitations of terms like “hallucination” and proposes an alternative perspective on the discipline.


  1. The Illusion of Learning: Machine learning, at its core, involves adjusting weights within a statistical model to optimize performance. While this process can generate impressive results, it differs fundamentally from how humans learn. Teaching a child involves comprehension, reasoning, and the ability to generalize knowledge, which are not encapsulated in the adjustment of model weights. Therefore, referring to machine learning as “learning” can be misleading.
  2. The Pitfalls of Anthropomorphizing: The use of terms like “AI hallucination” and attributing human-like qualities to machines creates an illusion of intelligence. This anthropomorphization leads to misconceptions about the true capabilities of machines. By unconsciously ascribing characteristics such as understanding or knowing to AI systems, we inadvertently deceive ourselves and inflate their capacities beyond what they truly possess.
  3. The Slippery Slope of Language: Even the use of pronouns like “I” by chatbots can blur the line between human and machine intelligence. This linguistic choice can subtly reinforce the notion of a conscious entity behind the keyboard, fostering the illusion of a human-like conversation partner. However, it is crucial to remember that chatbots are ultimately algorithms designed to simulate human-like responses, rather than possessing genuine understanding or consciousness.
  4. A Shift in Perspective: Instead of using the term “AI” with its potential for misinterpretation, an alternative suggestion is to refer to this discipline as “applied statistics.” By emphasizing the practical application of statistical methods, we ground our understanding in a more accurate representation of the field’s capabilities. Recognizing the automation potential of applied statistics can help us focus on its ability to alleviate mundane tasks and streamline processes, as described by David Graeber in his book on “bullshit jobs.”

On the other hand while there is an overlap between machine learning and applied statistics, it is important to note that machine learning is a subfield of applied statistics rather than a complete synonym. Applied statistics encompasses a broader range of statistical methods and techniques applied to various fields, including traditional statistical analysis, experimental design, and modeling. Machine learning, on the other hand, focuses specifically on developing algorithms and models that allow computers to learn patterns and make predictions or decisions without being explicitly programmed.

Machine learning techniques often involve statistical methodologies, such as regression analysis, clustering, or classification algorithms. However, machine learning goes beyond traditional statistical inference by utilizing computational power to process vast amounts of data and automatically adjust model parameters based on observed patterns. This adaptability and ability to learn from data are distinguishing characteristics of machine learning.

So, while applied statistics and machine learning share common ground, the latter extends beyond traditional statistical approaches by incorporating advanced algorithms and automated learning capabilities. Machine learning is a specialized field within the broader domain of applied statistics, aimed at developing intelligent systems capable of learning and making predictions from data.

automated learning is still applied statitics

While automated learning, as seen in machine learning, has its roots in applied statistics, it is important to recognize that machine learning expands upon traditional statistical methodologies to incorporate computational techniques and algorithms specifically designed for data-driven learning and pattern recognition.

Applied statistics traditionally focuses on analyzing and interpreting data using established statistical models and techniques. It involves hypothesis testing, regression analysis, experimental design, and other statistical methods to draw conclusions and make inferences about a population based on sample data.

Machine learning, on the other hand, aims to develop algorithms that enable computers to automatically learn patterns and make predictions or decisions without being explicitly programmed. It involves the creation of models that can learn from data, identify complex relationships, and make accurate predictions or classifications.

Machine learning algorithms, such as neural networks, decision trees, and support vector machines, use statistical concepts as a foundation. However, they often go beyond traditional statistical methods by incorporating optimization algorithms, computational techniques, and advanced mathematical concepts.

While applied statistics and machine learning are intertwined, machine learning represents an expansion and specialization of statistical techniques to enable automated learning from data. It leverages computational power, algorithmic complexity, and large datasets to develop models capable of learning and making predictions in complex and high-dimensional spaces.

In summary, while machine learning has its roots in applied statistics, it encompasses a distinct set of techniques and methodologies that go beyond traditional statistical analysis, focusing on automated learning and predictive modeling from data.

Conclusion: The illusion of “machine learning” as true learning and the temptation to anthropomorphize machines are challenges we face in understanding the capabilities of artificial intelligence. By critically examining the language we use and avoiding linguistic traps, we can develop a more realistic perspective on the field. Reframing the discipline as “applied statistics” highlights its practicality and automation potential, allowing us to appreciate its ability to tackle mundane tasks and enhance efficiency.