Saturday, January 25, 2023.
Figure 1. Interaction between the author and ChatGPT on January 25, 2023, approximately two months after ChatGPT’s public release. Screenshot archived by the author (*).
Today, Friday, May 29, 2026, the screenshots look almost quaint.
The interface is simpler. The responses are shorter. The confidence is often greater than the understanding. Yet these screenshots capture something more significant than an old conversation. They are historical artifacts documenting a private interaction between a human user and an early generative AI system during the first months following ChatGPT’s public release. (GenAI, for short).
At the time, nobody quite knew what this new technology would become.
One exchange in particular stands out.
The prompt was deceptively simple:
“A night without the dark.”
The system answered literally. Night requires darkness; therefore a night without darkness is impossible.
The answer was not wrong. It simply missed the point.
The user replied:
“It’s a metaphor, not literal. Please interpret it in the style of Slavoj Žižek.”
The system adjusted. It began speaking about negativity, reality, and the impossibility of eliminating unpleasant aspects of human existence. Then the conversation moved further still. The user requested a hypothetical debate between Slavoj Žižek and Zygmunt Bauman on the meaning of the riddle.
Looking back from 2026, what is striking is not the quality of the answers. By contemporary standards, they are rudimentary. The “Žižek” produced by the system is only vaguely Žižekian. The “Bauman” sounds more like a generic advocate of social progress than the author of liquid modernity. The machine was capable of generating philosophical language but not yet of fully inhabiting philosophical traditions.
Yet the historical significance of the exchange lies elsewhere.
The conversation documents an early encounter between a human interpreter and a generative system capable of producing interpretive language without itself participating in interpretation.
From the perspective of Ernst Cassirer (1944), this asymmetry is significant. Human beings do not merely process signals or respond to stimuli; they inhabit symbolic worlds. As animal symbolicum, humans seek meaning through language, myth, religion, art, and culture. The GenAI system could generate language suggestive of interpretation, but the interpretive horizon itself remained human.
The emergence of GenAI does not force us to abandon the belief that interpretation is a uniquely human capacity. What it does force us to reconsider is how a non-interpreting system can nevertheless participate in, shape, provoke, and transform human interpretive practices.
The machine approached the phrase as a problem to solve.
The user approached it as a text to interpret.
That distinction mattered.
The early GenAI could generate words fluently, but it often remained captive to literal meanings. It could define concepts before it could dwell within them. It could describe interpretations before it could genuinely perform interpretation. The user, meanwhile, repeatedly nudged the conversation toward a hermeneutic horizon. Not by correcting facts, but by reframing the question itself.
In retrospect, the riddle became an accidental metaphor for the encounter.
A night without the dark.
Perhaps that describes the aspiration underlying much of contemporary technology: knowledge without uncertainty, intelligence without limitation, answers without ambiguity. Yet the conversation itself demonstrated the opposite. Understanding emerged not through the elimination of ambiguity but through engagement with it.
The darkness was not where interpretation began. The darkness was not an obstacle to understanding. It was the cloud of unknowing itself—veiling meanings not yet brought into view. The user repeatedly redirected the conversation from literal description toward metaphorical and philosophical inquiry. In Gadamerian terms, understanding did not emerge through the elimination of ambiguity but through engagement with it (Gadamer, 2004).
Three years later, the technological landscape has changed dramatically. Generative AI systems are more capable, more knowledgeable, and more contextually aware than their predecessors from early 2023. Many of the shortcomings visible in these screenshots have since been reduced.
The more interesting continuity, however, is not technological.
It is human.
The screenshots reveal a persistent intellectual disposition already present long before later academic achievements, professional milestones, or formal credentials. The same instinct appears throughout the dialogue: dissatisfaction with superficial readings, attraction to hermeneutic inquiry, and a tendency to push beyond what a text says toward what makes its meaning possible.
The machine became increasingly capable of enveloping the world through more sophisticated computational representations, extending the range of informational structures through which aspects of reality could be modelled and processed (Floridi, 2011). The human matured. Yet the orientation toward questioning remained remarkably stable.
That is why these screenshots deserve to be preserved. Not because they record what an early GenAI system could do, but because they capture an encounter that was simultaneously formative and informative: formative because it shaped subsequent human–GenAI engagements, and in-formative because it participated in the evolving informational environment through which humans and computational systems increasingly came to interact (Floridi, 2013).
The technology was becoming increasingly capable of generating plausible responses.
The human was already engaged in the older task of seeking meaning.
The screenshots preserve neither the emergence of machine understanding nor the obsolescence of human interpretation. They preserve a moment in which a symbolic being encountered a technology increasingly capable of enveloping the world through computation—and discovered that the oldest questions remained.
(*) Note on the screenshots. The screenshots reproduced in this essay were captured by the author on January 25, 2023, during interactions with ChatGPT shortly after its public release in November 2022. They are reproduced as historical artifacts documenting a private human–GenAI interaction during the early adoption phase of generative AI.
References
Cassirer, E. (1944). An essay on man: An introduction to a philosophy of human culture. Yale University Press.
Floridi, L. (2011a). The philosophy of information. Oxford University Press.
Floridi, L. (2011b). Enveloping the world for AI. The Philosophers’ Magazine, 54(3), 20–21. https://doi.org/10.5840/tpm20115437
Floridi, L. (2013). The ethics of information. Oxford University Press.
Gadamer, H.-G. (2004). Truth and method (2nd rev. ed., J. Weinsheimer & D. G. Marshall, Trans.). Continuum. (Original work published 1960)
