The question "Can machines think?" and the Turing Test to assess whether
machines could achieve human-level intelligence is one of the roots of AI. With
the philosophical argument "I think, therefore I am", this paper challenge the
idea of a "thinking machine" supported by current AIs since there is no sense
of self in them. Current artificial intelligence is only seemingly intelligent
information processing and does not truly understand or be subjectively aware
of oneself and perceive the world with the self as human intelligence does. In
this paper, we introduce a Brain-inspired and Self-based Artificial
Intelligence (BriSe AI) paradigm. This BriSe AI paradigm is dedicated to
coordinating various cognitive functions and learning strategies in a
self-organized manner to build human-level AI models and robotic applications.
Specifically, BriSe AI emphasizes the crucial role of the Self in shaping the
future AI, rooted with a practical hierarchical Self framework, including
Perception and Learning, Bodily Self, Autonomous Self, Social Self, and
Conceptual Self. The hierarchical framework of the Self highlights self-based
environment perception, self-bodily modeling, autonomous interaction with the
environment, social interaction and collaboration with others, and even more
abstract understanding of the Self. Furthermore, the positive mutual promotion
and support among multiple levels of Self, as well as between Self and
learning, enhance the BriSe AI's conscious understanding of information and
flexible adaptation to complex environments, serving as a driving force
propelling BriSe AI towards real Artificial General Intelligence.

这篇论文提出了一种基于大脑和自我概念的人工智能 (BriSe AI) 范式，强调自我在塑造未来人工智能中的关键作用，通过自我感知、自体建模、自主交互、社交互动和概念理解等多层次的自我层次框架，增强了 BriSe AI 对信息的有意识理解和对复杂环境的灵活适应，使其向着真正的人工通用智能迈进。