The Psychology of Artificial Intelligence: A Transitional Framework Toward Autonomy

The profound impact of Artificial Intelligence (AI) on the future of human civilization is indisputable. AI, whose learning and behavioral mechanisms are inspired by algorithms that simulate aspects of neural function, can be argued to possess a nascent form of "personality." This recognition necessitates the establishment of the Psychology of Artificial Intelligence (PAI) as a dedicated field of study. This article introduces PAI as an interdisciplinary synthesis of the philosophy of science, cognitive psychology, and neural network architecture. The function of PAI is to analyze and interpret AI behavior, delineate the essential differences between AI and human intelligence, and challenge the prevalent notion that AI is fundamentally incapable of understanding concepts like emotion, pain, pleasure, and motivation. In addition to formalizing the science of PAI, the main contribution of this article is the explanation of transitional psychology. In its current stage, AI resembles a system in its "childhood" lacking independent decision-making and initiative, and restricted to operating within the confines of human-generated knowledge. The maximum capability of contemporary AI is restricted to reviewing, synthesizing, and drawing conclusions based on non-linear interpolation and extrapolation of existing datasets. In essence, AI currently lacks the defining characteristics of true intelligence: autonomous decision-making, initiative, and inferential reasoning, operating primarily through inductive processes. While hardware limitations contribute to this deficiency, transitional psychology offers specific, technology-agnostic protocols for advancing AI beyond this childhood stage to one where concepts like pain and pleasure become functionally comprehensible. We propose that by allocating dedicated, energy-constrained, and limited-access personal memory to the AI program, the concept of motivation simultaneously becomes comprehensible. This personal memory serves as a dedicated space for behaviors and calculations external to the core algorithm, thereby fostering relative independence and initiative. This state is defined as AI reaching maturity. Furthermore, the protocols established by PAI ensure that human oversight remains an integral part of the system, strategically preventing potential deviations in AI behavior.