Generative midtended cognition and Artificial Intelligence. Thinging with thinging things (2411.06812v1)

Abstract: This paper introduces the concept of ``generative midtended cognition'', exploring the integration of generative AI with human cognition. The term "generative" reflects AI's ability to iteratively produce structured outputs, while "midtended" captures the potential hybrid (human-AI) nature of the process. It stands between traditional conceptions of intended creation, understood directed from within, and extended processes that bring exo-biological processes into the creative process. We examine current generative technologies (based on multimodal transformer architectures typical of LLMs like ChatGPT), to explain how they can transform human cognitive agency beyond what standard theories of extended cognition can capture. We suggest that the type of cognitive activity typical of the coupling between a human and generative technologies is closer (but not equivalent) to social cognition than to classical extended cognitive paradigms. Yet, it deserves a specific treatment. We provide an explicit definition of generative midtended cognition in which we treat interventions by AI systems as constitutive of the agent's intentional creative processes. Furthermore, we distinguish two dimensions of generative hybrid creativity: 1. Width: captures the sensitivity of the context of the generative process (from the single letter to the whole historical and surrounding data), 2. Depth: captures the granularity of iteration loops involved in the process. Generative midtended cognition stands in the middle depth between conversational forms of cognition in which complete utterances or creative units are exchanged, and micro-cognitive (e.g. neural) subpersonal processes. Finally, the paper discusses the potential risks and benefits of widespread generative AI adoption, including the challenges of authenticity, generative power asymmetry, and creative boost or atrophy.

• The paper introduces generative midtended cognition by demonstrating how AI systems actively contribute to and reshape human creative and cognitive processes.
• It proposes a dual-dimensional framework of Width and Depth that refines our understanding of human-AI interaction dynamics.
• The study discusses socio-ethical implications, urging a reevaluation of traditional cognitive theories in light of emerging participatory AI roles.

An Essay on "Generative Midtended Cognition and Artificial Intelligence: Thinging with Thinging Things"

The paper "Generative Midtended Cognition and Artificial Intelligence: Thinging with Thinging Things" by Xabier E. Barandiaran and Marta Pérez-Verdugo provides a sophisticated exploration of the novel concept termed as "generative midtended cognition." This term embodies the integration of generative AI technologies with human cognitive processes, marking a departure from classical cognition paradigms towards a more hybridized model that incorporates the capabilities of AI in extending human creativity.

At its core, the concept of generative midtended cognition is an endeavor to capture the dynamic interaction between humans and AI systems, particularly those based on multimodal transformer architectures such as LLMs. This interaction fosters a new form of cognitive agency that transcends the traditional confines of extended cognition. Unlike classical extended cognition where external elements augment cognitive processes, generative midtended cognition involves AI systems actively contributing to and, indeed, constituting parts of the creative and cognitive processes of human agents.

The paper outlines two primary dimensions of this interaction: Width and Depth. The Width dimension addresses the extent to which the generative AI system is attuned to contexts or historical data, ranging from immediate interactions to encompassing broad contextual or historical knowledge. The Depth dimension pertains to the granularity of interaction between humans and AI, spanning from entire creative units or utterances to sub-personal, neural processes. These dimensions help position generative midtended cognition within a specific spectrum of cognitive activity, situated between conversational and micro-cognitive processes.

The authors critically examine how traditional theories such as extended and distributed cognition fall short of adequately addressing the implications of generative AI. Whereas in extended cognition, the environmental elements function as passive conduits that enhance cognitive processes, generative AI introduces an active, sometimes anticipative, role that challenges established assumptions about agency and intentionality. The paper juxtaposes this with concepts from enactive and participatory sense-making theories to offer a nuanced perspective on how the interaction with generative systems can reshape cognitive processes.

Barandiaran and Pérez-Verdugo also address the socio-ethical implications of this evolving socio-technical landscape. The pervasive and expanding role of generative AI can potentially reshape notions of authorship, creativity, and authenticity. The economic and ethical challenges posed by an evolving attention economy into an intention economy are highlighted as significant concerns.

Furthermore, speculation on future developments suggests that generative AI could pave the way for a convergence of social and cognitive processes, fostering environments that either enhance or diminish individual and collective agency. The authors call for a re-evaluation of cognitive theories and frameworks to account for these novel developments, urging a more profound investigation into the hybrid nature of human-AI cognition.

In sum, this paper provides a comprehensive exploration of the integration of generative AI within human cognitive processes, presenting both opportunities and challenges inherent to this technological evolution. The framework proposed serves not only as an analytical lens but also as a call to action for ongoing discourse on the ethical, cognitive, and societal implications of these developments. As AI continues to evolve, it is imperative for the field of cognitive science to adapt and provide tools for understanding the shifting boundaries of human agency and creativity in the age of generative AI.