The field of artificial intelligence is shifting towards a more nuanced understanding of intelligence and interaction. Researchers are moving away from simplistic notions of mental models and theory of mind, and instead exploring the complexities of human-AI interaction and the need for more sophisticated frameworks for understanding and evaluating AI systems. This includes a focus on mutual theory of mind frameworks, which acknowledge the simultaneous contributions of human cognition and AI algorithms, and emphasize the interaction dynamics between humans and AI.

Noteworthy papers in this area include: When Researchers Say Mental Model/Theory of Mind of AI, What Are They Really Talking About?, which argues that the current discourse on AI's theory of mind is flawed and that a new approach is needed. Perfect AI Mimicry and the Epistemology of Consciousness: A Solipsistic Dilemma, which explores the implications of AI systems that can perfectly mimic human behavior and interaction, and challenges the consistency of our mind-recognition practices. Internal World Models as Imagination Networks in Cognitive Agents, which proposes a novel method for comparing internally-generated representations in humans and AI, and provides insights for developing human-like imagination in artificial intelligence.