In recent years, the evolving landscape of artificial intelligence has initiated significant discourse around its integration into human cognition and behavior. A groundbreaking study by J. Noller, titled “4E Cognition and the Coevolution of Human–AI Interaction,” published in the journal Discover Artificial Intelligence, delves deeply into this intersection of AI and human cognition. It highlights the implications of what Noller terms “4E cognition,” which emphasizes embodied, embedded, enacted, and extended aspects of cognitive processes. This multi-faceted approach encourages us to reconsider traditional views of cognition purely as a computational or internal mental activity, inviting a broader understanding that incorporates environmental and social influences, particularly in our interaction with AI systems.
As we plunge into the details of Noller’s findings, it is evident that humans and AI are not merely categories of cognitive agents operating in isolation; rather, they are locked in a complex coevolutionary relationship. This relationship is marked by mutual influence, where advancements in AI technology reshape human cognition, while human behavioral patterns concurrently inform the design and function of AI systems. Noller posits that this interaction is not limited to simple task execution or data processing; it extends into the realm of emotional and social engagement, fundamentally altering the way we think, communicate, and relate to one another.
One of the key elements of Noller’s research is the notion of “embodied cognition,” which stresses that cognition stems from the interplay between the mind and body in relation to our environments. This perspective is critical when assessing how AI becomes a part of our daily lives. As AI integrates into environments through devices like smartphones and smart homes, our interactions with these technologies are reshaping cognitive schemas and behavioral norms. Noller argues that as we continually adapt to AI interfaces, we are also learning to navigate new patterns of thinking and responding, which in turn informs future AI developments.
The “embedded” aspect of 4E cognition further advocates for the importance of context. Noller emphasizes that human cognition is largely context-dependent, and this becomes particularly relevant when we consider AI’s role within educational settings, workplaces, and social interactions. For instance, in learning environments, AI can assist in tailoring personalized educational experiences, which compel students to engage differently with the materials presented to them. As this personalization grows increasingly sophisticated, the students’ cognitive processes evolve concurrently, leading to a circular pattern of development where AI not only serves as a tool but also as a catalyst for cognitive growth.
In terms of “enacted cognition,” Noller explores how both humans and AI systems learn through direct interaction with the world. This suggests that learning is not a passive reception of information but an active engagement with the environment. AI algorithms, particularly those employing machine learning, are designed to learn and adapt based on input from their human counterparts. As we interact with AI—whether through voice commands, searches, or recommendations—our choices and behaviors provide a feedback loop that enhances AI’s capabilities. Consequently, these systems become increasingly refined, influencing how we learn and process information on a day-to-day basis.
The final component of 4E cognition, “extended cognition,” invites contemplation on how external tools and technologies act as extensions of our own cognitive processes. This raises intriguing questions about identity and agency. When we rely on AI to perform tasks, store information, or organize our lives, we are, in essence, extending our cognitive reach beyond biological constraints. This reality challenges our understanding of what it means to think and function in the digital age. Noller argues that recognizing AI as an extension of our cognitive capabilities encourages a reevaluation of our responsibility towards designing ethically-guided AI systems that can support human flourishing rather than diminish it.
The coevolution of human and AI interaction is palpable in various domains such as healthcare, where AI-driven algorithms analyze vast datasets to aid in decision-making and patient care planning. Noller’s research emphasizes that as healthcare professionals increasingly rely on AI for diagnostics and treatment recommendations, their cognitive approaches evolve to incorporate these advanced tools. This shift prompts a re-examination of skill sets required in the industry and raises ethical questions related to dependency on technology—how can professionals maintain critical thinking and decision-making autonomy when tools are so advanced?
In the realm of communication, AI-powered applications enhance our interpersonal interactions through translated languages and conversational agents. As these technologies continue to evolve, our social skills and communication styles adapt accordingly. Noller advocates for an emphasis on cultivating emotional intelligence and interpersonal skills alongside technological proficiency. This dual focus is vital for ensuring that human interaction retains depth and connection in an AI-driven world.
Moreover, Noller’s insights resonate with concerns regarding job displacement due to automation. While AI may streamline processes and increase efficiency, he underscores the importance of proactive adaptation. Consequently, societal structures must be designed to equip individuals with the cognitive tools necessary for collaboration with AI. Educators and policymakers alike need to prioritize curricula centered around critical thinking, creativity, and emotional intelligence to nurture a workforce capable of thriving in a coevolutionary landscape where human and machine intelligence coexist.
Despite the promising advancements in human–AI interaction, Noller emphasizes the importance of ethical considerations and frameworks to guide these developments. As we navigate this new frontier, considerations surrounding privacy, security, and bias must not be overlooked. The challenge lies in ensuring that AI systems are designed with equity and social justice in mind, as these technologies have the potential to exacerbate existing inequalities if left unchecked. Therefore, interdisciplinary collaboration is essential for creating a holistic understanding of the implications of AI on human cognition and society.
In summation, J. Noller’s innovative framework of 4E cognition presents a compelling lens through which to view the evolving partnership between human cognition and artificial intelligence. The recognition of this coevolution not only informs the design of better AI systems but also encourages us to cultivate cognitive flexibility and resilience. To thrive in an increasingly algorithmic world, we must acknowledge the reciprocal nature of our relationship with technology and work collaboratively toward a future where both human and AI capabilities can flourish side by side.
In conclusion, as we step into a future shaped by AI, we must participate thoughtfully in its design and application. Noller’s work serves as a poignant reminder that the development of intelligent machines cannot be divorced from ethical considerations or the understanding of human cognitive processes. Our capacity for creativity, empathy, and critical thought remains unparalleled and must be protected as we forge ahead. Hence, while AI may change the manner in which we think and act, the fundamental essence of humanity—our values, emotions, and intellect—must remain at the core of this coevolution.
Subject of Research: The interplay of human cognition and artificial intelligence through the framework of 4E cognition.
Article Title: 4E cognition and the coevolution of human–AI interaction.
Article References:
Noller, J. 4E cognition and the coevolution of human–AI interaction.
Discov Artif Intell 5, 323 (2025). https://doi.org/10.1007/s44163-025-00595-0
Image Credits: AI Generated
DOI: https://doi.org/10.1007/s44163-025-00595-0
Keywords: 4E cognition, human-AI interaction, embodied cognition, ethical AI, coevolution, cognitive flexibility, emotional intelligence, future of work.
Tags: 4E cognition frameworkcoevolution of human and AIcognitive processes in AI developmentembodied cognition in technologyemotional engagement with artificial intelligencehuman behavior shaping AI designhuman cognitive processesHuman-AI Collaboration.implications of AI on cognitionintegrated human-AI systemsrevolutionizing cognitive understandingsocial influence on AI interaction
