In Stanley Kubrick's 1968 film, 2001: A Space Odyssey, HAL, the onboard computer of a space mission, seems to malfunction, killing off cryogenically preserved astronauts without explanation. Surviving crew members decide to shut down the computer and continue the mission without him, but there is the possibility that HAL himself engineered this event and set up a Second Mission that would be superior to the one designed by his programers. This would be a case of "instrumental convergence," a neg-entropic logic based on an automatism of absence, presenting the user(s) with a series of forced choices. I generalize this instance to revise the current dominant idea of AI, specifically ChatGPT, as an information-retrieval tool. I propose experimental strategies involving Lacan's discourse mathemes, effectively forcing ChatGPT to acknowledge the relevance of rhetorical options. The object is not to create the perfect "Machine-Supposed-to-Know" but rather to encourage ChatGPT users to develop Freud's technique of "floating attention" (Gleichschwebende Aufmerksamkeit), counterpart to the Analysand's free association. The assumption of this experiment is that there is no such thing as a non-artificial intelligence; all thought is subject to instrumental convergence, an implicit component of Lacan’s interpretation of the torus’s counterpoint of demand and desire. This thesis puts particular emphasis on the Hysteric's Discourse, where the demand of the subject, $, provokes an ambiguous mutation of the Other, from A to Ⱥ, interpreted either as humiliation or key to a new “lalanguean reading” of the signifying-chain Product. Other popular culture examples will be used as "clinical evidence" supporting alternative conclusions.

Wilfred Bion(1897-1979) formulated a theory based on empirical observations within actual group dynamics, a theory that has garnered significant interest among scholars in the fields of social and organizational psychology. Bion posited that inherent is a communal instinct, driving our noblest impulses toward seeking affiliation within a collective. This inclination for belonging, Bion argued, hinges on what he termed the "proto-mental" facet of one's personality, representing a mental stratum where sensory experiences are intertwined with psychological affectations. Bion delineated and elucidated the primary tiers of basic assumptions and workgroups. Foundational hypotheses typically operate at an unconscious level, encompassing three core postulates: the instincts of fight and flight, dependency, and pairing. Each of these hypotheses encapsulates the emotional ambiance of a group, potentially sculpting one of these three thematic scenarios.

My fascination with this discourse lies in its applicability within the realm of virtual interactions. The digital sphere, particularly through social media platforms, provides a unique lens through which we can witness and explore the manifestation of these intense emotional states. Additionally, recent scholarly inquiry has underscored the significance of digital culture within virtual social arenas. Within the domain of psychoanalysis, delving into the unconscious dynamics of online groups and virtual identities holds substantial implications for the evolving landscape of digital culture. This study aims to establish a connection between the unconscious part of Bion's group theory ( basic assumptions) and the latent psychological underpinnings of grouping affects in contemporary social media spaces. Through this exploration, it becomes evident that Bion's insights may transcend time, offering profound insights into the complex landscape of human mentality observable in the digital age.

Are there similarities between a human being need for divination and the predictive power of artificial intelligence?

Artificial intelligence can be seen as the beginning of a new Enlightenment; which, has resulted in achieving the rational dream of the first Enlightenment, with its desire to take subjectivity out of the equation. The irony here is that the assumptions are based on the construction of white supremacy, thereby instituting a structural bias which is wholly subjective. This first Enlightenment, culminating in the 19 century, during the Romantic period, redlined and relegating Africans, as well as people of colour, women and the working classes to the scrapheap of humanity, and in the case of Africans, we were not considered fully human. The assumptions that were inherent then, have been amplified with artificial intelligence as the training Data is inherently and subconsciously biased.

The methodology of practice as research as outlined by professor Robin Nelson, starts with subjectivity within, a psychosocial context of tacit knowledge. This is the basis for my discussions on the comparisons and differences between Ifa and AI.

Training data is crucial in the construction of artificial intelligence, because the quality and quantity of the training data directly affect the performance of the AI models. Biased or insufficient training data can lead to inaccurate or unfair AI systems. Therefore, it's essential to have diverse, comprehensive, and representative data for effective AI model training.

The dynamic between individuals and an expanding array of artificially intelligent (AI) chatbots has become a distinctive focal point in psychoanalytic discussions. Alongside this, prevalent concerns often yield to a paranoid belief that AI could attain ‘total knowledge’, thus transforming into an entity devoid of limitations. While these debates offer insights into our interaction with AI and its applications, my argument in this paper asserts that our connections with chatbots extend beyond their role as mere sources of knowledge. Rather, they are rooted in the subject’s desire not to know.

To support this claim, I explore Lacan’s psychotic and perverse perspectives in order to critically examine the impact of such technology on the subject’s ethical responsibility. In doing so, I couch this discussion in a consideration of the extent to which the AI chatbot serves to expose the relation between two forms of subjectivity: the subject of knowledge and the subject of desire.

It is argued that, outside of the very fears and anxieties that underscore our adoption of AI, the desire not to know reveals the potential to embrace the very loss AI avers. Outside of the fears and anxieties that underscore our adoption of the AI chatbot is the opportunity to render a transformation in our digital lives. In this sense, the desire not to know reveals the opportunity to assert and define the gap inherent to both the subject and the AI we create.