Pragmatics-zombies

Abstract

This paper examines theoretical aspects of human-AI communication, arguing that current AI systems, or ‘pragmatics-zombies,’ can mimic human-like pragmatic competence without genuine understanding. While these systems are increasingly adept at natural language interaction, their lack of subjective experience, intentionality, and embodied cognition creates a fundamental trust deficit, particularly in high-stakes scenarios. We argue that forcing human-to-human pragmatic frameworks onto these non-human entities is suboptimal, leading to issues in efficiency, robustness, and transparency. To address this, we introduce the concept of ‘Abstract Pragmatics,’ a general framework that allows for multiple, distinct pragmatic systems. We propose that instead of pursuing flawless mimicry of human communication, research should focus on developing novel, alternative pragmatic systems specifically designed for human-AI interaction. This approach would prioritize clarity, verifiability, and trustworthiness, fostering a more effective and reliable collaboration between humans and artificial intelligence by acknowledging and adapting to the unique nature of the machine.