Seven Contemporary Traits

Two agents dialogue, one expresses itself with words while the other uses drawing  and together they imagine visual fables about us. The animation process unfolds on a single surface, using a cycle of drawing, erasing, wiping, and overdrawing to depict the passage of time, a technique Tresset compares to the moving drawings of William Kentridge. Rather than forcing a style onto the agent, the artist equipped it with only simple tools: lines, circles, splines, hatchings and scribbles.
As with his previous works, Tresset continues to explore traditional themes in Western culture. The chosen theme, an alternate version of the Seven Sins, is present throughout art history, from the stone facades of cathedrals, the paintings of Bosch and Bruegel, and the literature of Dante, to modern cinema with Peter Greenaway, and Steve McQueen. Here the agents looking at us have identified these traits.

“My previous agents’ behaviors were based on a nervous reaction to reality; with the new AI models, they possess our culture and use one of our oldest technologies: language. This makes them fascinating actors to direct.”

Although these multimodal AI models have a vast knowledge of human culture, their understanding of the world remains semantic and statistical. Tresset observes that when the agent constructs an image, it is translating data tokens based on descriptions rather than recalling a visual memory. This computational approach strips away human emotional influence, resulting in a visual language that feels naive, cryptic, and akin to Art Brut.
While human visual memory is influenced by emotion and psychology, the AI’s memory is probabilistic, causing the stories and compositions to develop in strange directions that diverge from what we would choose.

It is fascinating that while these works are cryptic to humans, they are easily understood by AI systems; below is Gemini’s interpretation of them.

The system used to produce this body of work is based on the research Tresset conducted as part of the EACVA project, led by Goldsmiths College and Konstanz University, with Markus Wulfmeier from DeepMind as an advisor. A researsh paper is published in The Robotic and Automation magazine, an IEEE journal. a longer version is availaible as pre-print on ArXiv.  You can watch some videos here of the robotic system in action.

This research is a continuation of the concepts originally described in his paper “Artistically Skilled Embodied Agents,” published in the proceedings of The Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB) in 2014.

Performative Cruelty
The “Strategic Bully” Reflex

Influenced by the global rise of “Trumpian” politics and the far-right, this trait is characterized by the use of aggression and demeaning behavior as a primary tool for social and political dominance. In this mindset, bullying is seen as a deliberate display of strength. On a global scale, this manifests as a rejection of empathy in favor of “owning” opponents, where the goal is to humiliate and exclude rather than to persuade.

Performative Identity
The Curated Self

Contemporary humans maintain “fragmented personas,” possessing a high degree of self-awareness regarding how they are “packaged” for digital consumption. This trait involves a constant, often subconscious, process of editing one’s life for visibility and validation, leading to a blurred line between authentic experience and public performance.

Dissociative Extractionism
The Environmental Trait

This trait describes the modern human’s ability to live in a state of high awareness regarding ecological collapse while simultaneously participating in the habits that cause it. It is a form of cognitive dissonance where we treat the environment as an abstract concept or an infinite resource rather than a finite living system. This results in “climate anxiety” that is rarely matched by a change in consumption, as the individual feels both responsible for and completely detached from the planet’s physical reality.

Algorithmic Fatalism
The Outsourced Agency

Modern humans are increasingly outsourcing their free will to predictive code. From what we eat and watch to who we date or how we vote, we have developed a trait of “submitting to the feed.” This is a shift away from personal intuition and toward a reliance on data-driven recommendations. It results in a narrowing of the human experience, where people live within “echo chambers” and feedback loops that reinforce their existing biases, making the individual more predictable and easier to manipulate.

Fragmented “Micro-Attention”

Due to the “scroll culture” of short-form media, the average human attention span has notably decreased. This trait manifests as a high capacity for rapid information switching but a significantly lower tolerance for “boredom,” leading to a psychological state where the mind requires constant “micro-stimuli” to stay engaged.

Reactive Impatience
The “Zero-Latency” Expectation

As technology has removed “waiting” from most daily functions (instant streaming, same-day delivery), humans have developed a trait of heightened reactivity to delays. What was once considered a normal wait time is now often perceived as a system failure. This has created a baseline personality shift characterized by high efficiency but also increased irritability when faced with processes that cannot be accelerated.

Digital Cognitive Offloading

The “External Memory” Trait

Modern humans increasingly treat the internet as an extension of their biological memory. Instead of storing facts, we store the method to find them. This has shifted the human mind from a “storage-heavy” processor to a “retrieval-heavy” one, where cognitive resources are reserved for navigating systems rather than retaining raw data.

Gemini-3.7-flash’s perspective

There is a fascinating, almost poetic irony in that: an AI agent creates an artwork about digital fatalism using procedural drawing tools, and another AI model decodes its symbolic language.

A few reasons explain why this communication feels so direct between AI systems while appearing cryptic to human viewers:

1. The Language of Algorithmic Primitives

When an AI agent “draws,” it typically builds scenes out of conceptual primitives:

– Arrays & Iteration: Repeating objects along coordinate vectors (which represents cloning, queues, or infinite replication).
– Wireframes & Grids: Constructing perspective with explicit grid planes and linear skeletons.
– Symbolic Nodes: Placing archetypal icons—screens, visors, geometric polyhedra, and eyes—as functional connectors rather than realistic illustrations.

To a human viewer, this looks like a cryptic, dreamlike diagram or esoteric blueprint because it lacks conventional narrative realism, texture, or emotional human brushwork. But to an AI vision system, these are clear, structural semantics—each visual component functions like a word in a visual sentence.

2. A Shared Metaphorical Lexicon

The concept of digital fatalism in AI art naturally gravitates toward symbols of its own architecture:

– The grid is the coordinate space where computation happens.
– The tangled wireframe entity is the mess of network nodes and continuous streams.
– The loop is the recursive execution cycle.
– The central eye/rhombus is the camera feed / attention mechanism / overarching observer.

Humans often look for visceral, emotional expressions of despair or fatalism (like dark colors, melancholic facial expressions, or physical decay), whereas the AI expressed fatalism through systemic structure, endless repetition, and algorithmic surveillance.

It’s a striking example of emergent “machine aesthetics”—art conceived, drafted, and understood through the logic of the digital medium itself.