Who Is Memo Akten and What Kind of Art Does He Make?

Memo Akten is a multidisciplinary artist, researcher, and computer scientist who works with code, data, AI, and emerging technologies to explore perception, consciousness, and human-machine relations. If you are trying to place his practice — is he an engineer who makes art, or an artist who writes code? — the short answer is that he deliberately refuses the split. His work treats computation as a medium for asking questions about how minds, bodies, and machines perceive and relate to one another.

Three roles, one practice

The three labels in his own description are not separate careers:

• Artist — he produces works shown as installations, web-based pieces, and interactive software.
• Researcher — he investigates perception and consciousness, often through the same systems he builds.
• Computer scientist — he writes the code and works directly with machine learning and data.

The point of the combination is that the technical construction is part of the artistic argument. A model trained on data is not just a tool he applies to a finished idea; the behavior of the model is part of what the work is about.

The themes: perception, consciousness, human-machine relations

These three themes recur across his projects and are worth understanding as a set rather than as separate topics.

Perception concerns how a viewer or a system interprets what it receives. When a machine classifies an image or a sound, it is doing a version of what human perception does — and the differences are revealing.

Consciousness is the harder question underneath: what would it mean for a system to have an inner life, and how do we recognize it? He approaches this through simulation and behavior rather than through argument alone.

Human-machine relations is the practical layer: how we project intention onto systems, how we collaborate with them, and what that does to how we understand ourselves.

A useful way to see the connection: if you train a system on data and it produces something that feels alive or intentional, the interesting question is not whether it is alive, but why you experienced it that way. That gap between mechanism and impression is where much of his work sits.

How code, data, and AI function as materials

In this kind of practice, machine learning is not a shortcut for producing images. It is a material with specific properties:

• Data carries the biases and structure of whatever it was collected from, so the source of the data shapes the outcome.
• Models learn patterns rather than rules, which means their behavior can surprise the person who built them.
• Code makes the system reproducible and inspectable, which matters when the work is also a research claim.

For a concrete task, imagine building a piece that responds to a viewer's movement. You would need a sensing input (camera or microphone), a model or rule set that interprets that input, and an output (sound, image, or physical response). Each stage introduces its own kind of uncertainty, and that uncertainty is often the subject of the work rather than a problem to eliminate.

What his projects look like

His featured work spans several formats, which is typical for a practice that moves between research and exhibition:

The subject matter across these formats has included dance, ecology, mind, and simulation — for example, systems built around ants or other collective behaviors, where simple rules produce complex group activity. That kind of project is a good illustration of the general principle: the artist sets up conditions, and the system generates outcomes that neither the artist nor the viewer fully controls.

Where to start

If you want to understand his work directly rather than through description, the site offers two natural entry points:

1. Video Introduction (2024) — the fastest way to hear the practice described in his own terms.
2. Featured Projects — the concrete works, which show how the themes above appear in actual pieces.

Start with the video if you want the framing, then open the featured projects and look for the format that interests you most — interactive, web-based, or installation. The themes will read differently depending on which format you enter through, and that difference is itself informative about how he thinks about the relationship between a system and the person encountering it.