David Young

When an AI large language model (LLM) generates false information it is said to hallucinate. The same can be said for the hype generated by the tech industry about the promise and future of these systems. The titles of these works are quotes from tech leaders and organizations.

David Young uses AI and machine learning tools in ways that are contrary to the expected technological applications of big data, efficiency, and optimization. By constricting these tools, his work reveals the strangeness of AI logic, and the fallacy that it can serve as a substitute for human intelligence and creativity.

To create these works he begins with an AI tool known as a GAN (Generative Adversarial Network) which learns from the images it sees and then create new similar images. But, rather than training the GAN on hundreds of millions of photos, Young trains it using just a handful of images — an approach he refers to as “Little AI.” With such limited training data the machine struggles to create coherent images.

In this series, each AI generated images is expanded into a grid of disconnected pixels. Young then manipulates the grids with his custom software, creating expressive patterns that reveal structures previously invisible to us. 

We believe that the machine is creating images similar to what it was shown. But this prioritization on the visual reflects our own human biases and prejudices. The machine “sees” differently from us, and, so too, what it creates may not be entirely visible to our eyes. By manipulating the machine-created images he seeks to reveal that which we cannot see, but may be apparent, perhaps even obvious, to the machine. The work asks us to question: What are the hidden patterns, or the “irrational logic,” embedded within images created by the machine? Is its perception different from ours? And how compatible are its capabilities with the industry which is hyping it?