Emotions in Artificial Intelligence

TL;DR

This paper investigates whether AI can meaningfully emulate emotions and what that implies for alignment, interpretability, and ethics. It proposes a minimal, function-driven architecture in which synthetic emotions are encoded as affective labels attached to episodic memories and fused with real-time need signals to bias action proposals, demonstrated via a thought-experiment-like pseudo-code. A central claim is that moral patiency requires both affect and awareness, with a complexity-based threshold used to exclude sub-threshold systems from ethical standing. The work further develops thought experiments and ethical considerations to anticipate how increasing architectural complexity and emotional expressiveness could shape societal norms, policy, and governance around AI.

Abstract

This conceptual contribution offers a speculative account of how AI systems might emulate emotions as experienced by humans and animals. It presents a thought experiment grounded in the hypothesis that natural emotions evolved as heuristics for rapid situational appraisal and action selection, enabling biologically adaptive behaviour without requiring full deliberative modeling. The text examines whether artificial systems operating in complex action spaces could similarly benefit from these principles. It is proposed that affect be interwoven with episodic memory by storing corresponding affective tags alongside all events. This allows AIs to establish whether present situations resemble past events and project the associated emotional labels onto the current context. These emotional cues are then combined with need-driven emotional hints. The combined emotional state facilitates decision-making in the present by modulating action selection. The low complexity and experiential inertness of the proposed architecture are emphasized as evidence that emotional expression and consciousness are, in principle, orthogonal-permitting the theoretical possibility of affective zombies. On this basis, the moral status of AIs emulating affective states is critically examined. It is argued that neither the mere presence of internal representations of emotion nor consciousness alone suffices for moral standing; rather, the capacity for self-awareness of inner emotional states is posited as a necessary condition. A complexity-based criterion is proposed to exclude such awareness in the presented model. Additional thought experiments are presented to test the conceptual boundaries of this framework.