A Metasemantic-Metapragmatic Framework for Taxonomizing Multimodal Communicative Alignment
This work addresses the challenge of achieving human-like alignment in multimodal communication for AI and human-machine interaction, but it appears incremental as it builds on existing philosophical and linguistic theories without presenting new empirical results or benchmarks.
The paper tackles the problem of multimodal communicative alignment by proposing a metasemantic-metapragmatic framework based on Peircean capacities, introducing concepts like indexical contextualization and contextualization directionality to address gaps in current computational methods that overlook metapragmatic aspects.
Drawing on contemporary pragmatist philosophy and linguistic theories on cognition, meaning, and communication, this paper presents a dynamic, metasemantic-metapragmatic taxonomy for grounding and conceptualizing human-like multimodal communicative alignment. The framework is rooted in contemporary developments of the three basic communicative capacities initially identified by American logician and pragmatist philosopher Charles Sanders Peirce: iconic (sensory and perceptual qualities), indexical (contextual and sociocultural associations), and rule-like (symbolic and intuitive reasoning). Expanding on these developments, I introduce the concept of indexical contextualization and propose the principle of "contextualization directionality" for characterizing the crucial metapragmatic capacity for maintaining, navigating, or transitioning between semantic and pragmatic modes of multimodal communication. I contend that current cognitive-social computational and engineering methodologies disproportionately emphasize the semantic/metasemantic domain, overlooking the pivotal role of metapragmatic indexicality in traversing the semantic-pragmatic spectrum of communication. The framework's broader implications for intentionality, identity, affect, and ethics in within-modal and cross-modal human-machine alignment are also discussed.