From Canvas to Code: Artificial Intelligence as a potential demonstration for Object-Oriented Ontology in the realm of art and design

This paper investigates Artificial Intelligence (AI)-generated art and design as a compelling case study to demonstrate the core tenets of Object-Oriented Ontology (OOO). Our central thesis posits that AI-generated art and design exhibit a profound autonomy, one that operates independently of any human’s subjectivity, irrespective of whether we consider the artistic outcome or the underlying creative process. Research shows that AI art and design possess an “intention” inherent to the object itself, characterised by an unpredictable yet goal-oriented behaviour. This intentionality, thus defined, underscores the autonomy of AI art from an outcome-based perspective. In order to contextualise this discussion within the realm of AI, the paper further develops a comprehensive typology of autonomy, which categorises it across approaches, types, dimensions, and principles. Crucially, the outcome-based autonomy is complemented by the autonomy embedded within the algorithmic process. A parallel is drawn between this approach to AI-generated art and design and the historical concept of “mechanical objectivity” in science, characterised by “self-elimination.” This analogy ultimately leads to the proposition of “objectivist autonomy.” By considering the outcome, process, and objectivist autonomy perspectives, this paper reveals a significant alignment with, while also providing new insights into, the tenets of OOO’s theory of art. An experiment is conducted to support the thesis, which demonstrates the potential passive role of humans in the artistic creation process. This approach, therefore, offers a robust theoretical justification for understanding AI art and design within the OOO framework.