This study titled John locke’s notion of representational realism and its implications for knowledge representation in artificial intelligence, examined the intersection between Locke’s epistemology and how artificial intelligence employs symbolic systems, semantic network to encode and process knowledge. Symbolic AI has made progress in representing facts, rules, and relationships; however, it still struggles with grounding these representations in the real world. This has led to problems such as ambiguity, context-dependence, and misinterpretation. John Locke’s representational realism on the other hand, posits that human knowledge arises from mental ideas that represent the external world. Locke’s theory raises philosophical questions about the accuracy and reliability of representation. The relationship between Locke’s epistemological framework and modern knowledge representation in AI has not been fully explored by scholars in the field of philosophy and computer science. As a result, this gap limits our ability to design AI systems that can better mirror reality. There is therefore the need to investigate how Locke’s theory of representational realism can provide a conceptual framework for addressing the problem of accurate knowledge representation in AI. The main objective of this study was to examine Locke’s representational realism and its implications for artificial intelligence. To achieve this objective, this study employed the comparative and analytic methods to highlight how Locke’s theory of ideas sheds light on the gap between abstract representation and realworld reference in artificial intelligence. The study found that Locke’s theory of representational realism parallels knowledge representation in AI. Furthermore, the problem of representational accuracy in Locke’s theory is also a limitation to knowledge representation in AI. The study concluded that integrating the insights from the theory of representational realism will deepen our understanding of the limits of AI and this, in turn, will enable humans to design better systems that can better mirror the world.
Keywords: Representational Realism, Knowledge Representation, Artificial Intelligence, Ideas.
Written By:
Professor Idorenyin Esikot
idorenyinesikot@uniuyo.edu.ng
Courage Ofuka
courageofuka@gmail.com