What Artificial Intelligence May Be Missing—And Why It Is Unlikely to Attain It Under Current Paradigms

Contemporary artificial intelligence excels at data processing and text generation but appears to lack consciousness, autonomous motivation, and genuine understanding. This article uses the metaphor of a motorcycle and a horse to argue that technological progress may obscure deeper principles of life and mind. Drawing on abduction, tacit knowledge, phenomenal consciousness, and autopoiesis, the paper contends that current approaches to Artificial General Intelligence may overlook organizational principles only partially understood in biological systems. It calls for a new paradigm that asks not just how to build smarter machines, but what intelligence, life, and consciousness fundamentally are, acknowledging their relation to computability remains an open question.

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Abstract

Contemporary artificial intelligence (AI) achieves remarkable results in data processing, text generation, and the simulation of human cognition. However, it appears to lack key characteristics typically associated with living systems—consciousness, autonomous motivation, and genuine understanding of the world. This article critically examines the possible ontological divide between simulated intelligence and lived experience, using the metaphor of the motorcycle and the horse to illustrate how technological progress may obscure deeper principles of life and mind. Drawing on philosophical concepts such as abduction, tacit knowledge, phenomenal consciousness, and autopoiesis, the paper argues that current approaches to developing Artificial General Intelligence (AGI) may overlook organizational principles whose role in biological systems remains only partially understood. Methodologically, it employs a comparative ontological analysis grounded in philosophy of mind, cognitive science, systems theory, and theoretical biology, supported by contemporary literature on consciousness and biological autonomy. The article calls for a new paradigm that integrates these perspectives—one that asks not only “how to build smarter machines,” but also “what intelligence, life, and consciousness may fundamentally be,” acknowledging that their relation to computability remains an open question.