This project, which I’ve titled “Little Things,” is a small artistic exploration—though perhaps not what one typically considers “art.” It’s a creative pursuit that exists outside traditional artistic boundaries. Its value is ultimately yours to determine.
Little Things” is an exploration of mental well-being, investigating a potential method for improving internal mental balance. This is a limited experiment. The computer gathers specific, sensitive but non-identifying user data, with safeguards against misuse. This data is then used to generate an AI image presented to the user, intended to have a beneficial effect on their mental state. Currently, this service is offered free of charge.
The mind, as I define it, encompasses the complex of faculties involved in perceiving, remembering, considering, evaluating, and deciding. Jean Piaget, the Swiss psychologist, recognized cognitive adaptation as consisting of two fundamental processes: assimilation and accommodation. Assimilation involves interpreting reality through the lens of one’s existing internal model of the world, while accommodation involves adjusting this model to accommodate new experiences. Faulty assimilation, influenced by past experiences, can lead to subsequent faulty accommodation. In essence, we perceive the world through the filter of our established perceptions.
If this erroneous “habituation” arises from assimilation, contact with the external world should ideally introduce novelty. “Little Things” aims to facilitate this by presenting users with AI-generated images. Data collection is voluntary, and the program utilizes specific methods to identify cognitive dissonances within the user’s existing mental framework. The generated image is then tailored to address these dissonances, based on a pre-existing model. The process primarily employs language-based techniques and, of course, some basic coding.
Here I will present the application, which has an improved version.