What Artificial Intelligence May Be Missing—And Why It Is Unlikely to Attain It Under Current Paradigms
Philosophies February 26, 2026 Peer reviewed DOI: 10.3390/philosophies11010020 via DOAJ
Summary
Current artificial intelligence excels at data processing and text generation but likely lacks consciousness, autonomous motivation, and genuine understanding. This analysis uses the motorcycle and horse metaphor to contrast simulated intelligence with lived experience. Drawing on abduction, tacit knowledge, phenomenal consciousness, and autopoiesis, it argues that efforts to build Artificial General Intelligence may miss organizational principles essential to biological systems. The paper calls for a new paradigm that asks what intelligence, life, and consciousness fundamentally are, noting their relationship to computability remains unresolved.
Study at a glance
| Design | review |
|---|---|
| Key finding | Current AI lacks consciousness, autonomous motivation, and genuine understanding, and approaches to AGI may overlook organizational principles central to biological life. |
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.