Architectural Concepts for Integrating Fundamental Drives and Emotions Into Artificial Intelligence

Teddy Ferdinan, Wiktoria Mieleszczenko-Kowszewicz, Jan Kocon, Przemyslaw Kazienko

Abstract: Current large language models display limited emotional intelligence, often mimicking affective patterns without genuine understanding, which raises manipulation and safety risks. We argue that artificial intelligence (AI) should prioritize long-term human well-being over short-term engagement, and that advancing toward artificial general intelligence (AGI) requires embedding fundamental drives and artificial emotions in model architectures. Building on Lazarus’s cognitive-rational theory, we propose a framework with an emotional module and a rational module, where artificial drives guide affective appraisal and decision-making. This enables alignment of artificial emotions with core values—such as human well-being, fairness, and environmental preservation—anchoring AI safety at the architectural level rather than through post hoc fixes. We discuss technical and ethical challenges, including data needs and reward modeling, and call for open science and regulation to ensure human-centered AGI.

External IDs:dblp:journals/expert/FerdinanMKK25