Abstract

This paper integrates type functionalism with the Kairetic account to develop context-specific models for explaining mental states, particularly pain, across different species and systems. By employing context-dependent mapping f_c, we ensure cohesive causal explanations while accommodating multiple realizations of mental states. The framework identifies context subsets C_i and maps them to similarity subspaces S_i, capturing the unique physiological, biochemical, and computational mechanisms underlying pain in different entities such as humans, octopi, and AI systems. This approach highlights the importance of causal relations in defining mental states and preserves their functional roles across diverse contexts. Furthermore, the paper incorporates elements of token functionalism by recognizing species-specific realizations of mental states. By acknowledging the unique representations of mental states within different species and systems, the framework provides a nuanced understanding of how similar functional roles can be fulfilled by diverse physical substrates. This synthesis of type and token functionalism enhances our explanatory power and coherence in addressing the complex nature of mental states. The resulting framework offers a robust tool for analyzing and understanding mental phenomena, with significant implications for cognitive science, philosophy of mind, and artificial intelligence. By maintaining the functional roles of mental states while accommodating their multiple realizations, this approach not only advances theoretical understanding but also opens new avenues for practical applications in cross-species empathy, AI ethics, and the development of context-aware cognitive models.