ARTIFICIAL EMPATHY: THE PROMISE OF AI IN HUMAN COMMUNICATION

Jezik, književnost i empatija (2025) (22-34. стр.)

АУТОР(И) / AUTHOR(S):Nune Ayvazyan  

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DOI: 10.46793/LLE25.022A

САЖЕТАК / ABSTRACT:

This article examines artificial empathy in large language models (LLMs) and its implications for social interaction and translation. Artificial empathy is defined as the simulation of cognitive empathy, that is, recognition and context-appropriate response without felt emotion, emerging from pretraining on narrative-rich corpora and alignment that rewards prosocial language. It is shown how politeness and validation function as trust signals, which may explain why users experience LLMs as caring. Two use cases illustrate benefits and risks: (1) migrants and linguistic minorities, for whom conversational systems can lower barriers to participation in host-society environments; and (2) young users seeking emotional support, where simulated empathy may help in low-to-moderate-stakes exchanges but can miscalibrate trust in high-stakes situations. Building on Putnam’s thin/thick trust, a calibration framework is proposed that links empathic style to confidence through transparency, privacy protection, and human involvement in high-stakes situations. An important argument is that literature matters as a crucial component of model training data, which can shape the quality of simulated empathy.

КЉУЧНЕ РЕЧИ / KEYWORDS:

artificial intelligence, large language models, empathy, communication, translation

ПРОЈЕКАТ / ACKNOWLEDGEMENT:

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