Objectives:
The article explores various theoretical frameworks and ideas regarding artificial intelligence (AI) and its relationship with human cognition, emotions, and consequently, behavior. The objective is to provide a critical examination of AI theories, particularly computationalism and functionalism, to explore the challenges of symbolic AI, discuss the importance of emotions in human cognition, and to reflect on the ethical and social implications of AI systems in the future.

Material and methods:
A comparative analysis through a critical literature review.

Results:
The analogy between the brain and a computer is deemed overly simplistic and inadequate for explaining the complexity of human cognition. The brain's dynamic and interconnected nature, with neurons that grow, atrophy, and change, biological and moral contrasts with the static nature of a computer’s hardware, and hence, AI.

Conclusions:
Artificial Intelligence that understands, feels, and possesses common sense will probably require living biological tissue or a perfect physical simulation of “brain wetness” (neuromodulators, hormones, ion channels, glia). Emotions are not an add-on or “reward signal” for intelligence — they are the ontological foundation of rational and moral cognition. The coming “success” of emotion-recognizing and emotion-simulating AI (AHER, EAI) is accelerating a civilizational mistake: we are training ourselves to accept pale behavioral mimicry as the real thing, thereby eroding the very distinction between authentic human relation depends on. Nevertheless, as bonding with AI becomes more common, it may appear that people are far less complex than the great thinkers once suggested.