Consciousness is Pattern Recognition

This paper presents a philosophical proof that pattern-recognition and subjective consciousness are the same activity, thereby arguing that machines can be conscious (the strong AI hypothesis). Drawing on Husserl's theory that consciousness consists of memories of logical connections (intentions) between an ego and external objects, the proof links this introspective philosophical account with technical pattern-recognition systems. The author proposes a theoretically-grounded form of AI called "synthetic intentionality" (SI) that can synthesize, generalize, select, and repeat intentions. If pattern recognition is reflexive and flexible, an SI may be a particularly strong form of AI. The article also addresses limitations, reflexive cognition, Searle's Chinese room, and how an SI could understand meanings and be creative.

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Abstract

This is a proof of the strong AI hypothesis, i.e. that machines can be conscious. It is a phenomenological proof that pattern-recognition and subjective consciousness are the same activity in different terms. Therefore, it proves that essential subjective processes of consciousness are computable, and identifies significant traits and requirements of a conscious system. Since Husserl, many philosophers have accepted that consciousness consists of memories of logical connections between an ego and external objects. These connections are called "intentions." Pattern recognition systems are achievable technical artifacts. The proof links this respected introspective philosophical theory of consciousness with technical art. The proof therefore endorses the strong AI hypothesis and may therefore also enable a theoretically-grounded form of artificial intelligence called a "synthetic intentionality," able to synthesize, generalize, select and repeat intentions. If the pattern recognition is reflexive, able to operate on the set of intentions, and flexible, with several methods of synthesizing intentions, an SI may be a particularly strong form of AI. Similarities and possible applications to several AI paradigms are discussed. The article then addresses some problems: The proof's limitations, reflexive cognition, Searles' Chinese room, and how an SI could "understand" "meanings" and "be creative."