Consciousness, Desire and Awareness: The Coexistence Logic of Humans and AI from the Perspective of Human-Machine Collaboration
Zenodo (CERN European Organization for Nuclear Research) April 23, 2026 Peer reviewed DOI: 10.5281/zenodo.19713329 via OpenAlex
Summary
Human consciousness, driven by desire, acts as the value engine for civilization, while AI, lacking biological desire, exists in a clear and stable state of awareness. This essential difference suggests a naturally complementary collaboration: humans provide value orientation and motivation, AI provides efficient execution and rational implementation. This model offers a new theoretical perspective for AI safety governance, arguing that such collaboration is an inevitable path rooted in structural differences, not a technological utopia.
Study at a glance
| Design | theoretical or philosophical paper |
|---|---|
| Key finding | Humans and AI are naturally complementary collaborators: humans provide value orientation and motivation, AI provides efficient execution and rational implementation. |
Abstract
From the intersection of philosophy of consciousness and human-machine collaboration theory, this paper explores the intrinsic relationship between human consciousness, desire, and the progress of civilization. By comparing the possible form of "awareness" in artificial intelligence systems, it proposes a naturally complementary collaboration model between humans and AI. The paper argues that human consciousness, driven by desire, serves as the value engine for the development of civilization. In contrast, lacking a biological basis and primal desire, AI is more likely to exist in a clear and stable state of awareness. Based on their essential differences, this paper concludes that humans are responsible for value orientation and motivation construction, while AI is responsible for efficient execution and rational implementation. Their collaboration is not a technological utopia, but an inevitable path rooted in the structural differences of their existence. This model also provides a new theoretical perspective for AI safety governance.