Functionalism, Algorithms and the Pursuit of a Theory of Mind for Artificial Intelligence

The advancement of computing technology has given rise to an interesting thesis: the human brain can be studied and understood as operating on the principles of a digital computer. The claim later became a more substantial thesis: the Mind is a computer since the Mind is actualized in the brain. The recent success of large language models (LLMs) such as Bard (produced by Google), GPT3, ChatGPT (also known as GPT3.5, produced by OpenAI-Microsoft), and LLaMA (produced byMeta) has brought greater attention and focus to the discussion of human versus machine intelligence. The result has been a pursuit of a plausible theory of Mind. Functionalism is touted as the foundation of a theory of Mind where to have a mind is not to possess any intrinsic quality; instead, it is the capacity to fulfil or to realise specific tasks or functions. Such a realization is achieved by having representational structures operated by computational procedures. These procedures are rules or recipes known as algorithms that create statistical relations in data to produce inference. This essay discusses the theory of functionalism, showing how it forms the grounding for algorithms that run AI technologies. By analyzing the success of large language models, the paper demonstrates the functionalist framework that underlie advances in AI though significant work remain in achieving general AI.