Enactivism, the leading view in embodied cognitive science, has long credited phenomenology as its main inspiration but overlooked its deep roots in pragmatism. This article argues that pragmatism anticipated core enactivist ideas: cognition arises from ongoing interaction between organisms and their environment, cognitive abilities evolve through that history of interaction, and both biology and the organism's active capacities are central to understanding mind. Ontologically, both positions hold a neutral monism. The author contends that pragmatism is not only a precursor to enactivism but also offers conceptual resources and methods to resolve problems within enactivist theory, making it a rich area for further exploration.
Human intelligence is inseparable from emotion, yet current AI theories treat cognition as computing, reducing thought to symbolic manipulation. This approach has failed to replicate genuine intelligence, which is driven and motivated by emotion. Drawing on cognitive neurology, psychology, and anthropology, the article proposes 'emotional thinking'—the capacity to process and integrate emotions for sound decisions. This thinking splits into positive and negative types, reflecting opposing cognitive forces. The authors argue that future AI consciousness depends on emotional computing that simulates such emotional thinking, marking a necessary shift from purely computational models.
The moral status of artificial intelligence (AI) depends on the level of consciousness an AI possesses. Drawing on the evolution of consciousness in nature, this paper examines several consciousness abilities of AIs and proposes several possible relationships between humans and AIs. The advantages and disadvantages of those relationships are analyzed using classical ethics theories, including contract theory, utilitarianism, deontology, and virtue ethics. This approach helps construct a common hypothesis about the future relationship between humans and AIs, offering practical and normative guidance for distinguishing among different possible relationships.