Cognition and Intelligence

  1. Gordana Dodig-Crnkovic

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Cognition can be understood in at least two very different ways. In the human-centered tradition, cognition is defined as the set of mental processes: perception, memory, reasoning, language, and problem-solving, through which humans acquire and use knowledge. Intelligence, in this view, is a subset of these processes: the ability to reason, learn, and adapt. By contrast, the life-centered tradition identifies cognition with processes of life itself through which living systems maintain and adapt themselves through valuation, sense-making and interaction with their environments. In this broader perspective, intelligence refers to the competency with which organisms solve problems under conditions of novelty and uncertainty. These two frameworks, while rarely in direct debate, have far-reaching consequences for how we understand the nature of mind, life, and intelligent technologies.

Article activity feed

  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17606044.

    Does the introduction explain the objective of the research presented in the preprint? Yes The introduction explains the objective of the research, which is to address the definitional ambiguity surrounding the central concepts of cognition and intelligence across multiple disciplines. The study organizes the conceptual landscape by establishing two fundamental theoretical dividing lines: the distinction between mentalist approaches and embodied cognition frameworks, and the differentiation between human-centered and life-centered perspectives. By focusing on these divisions, the research aims to provide essential scaffolding for understanding how various traditions have approached the fundamental questions of what constitutes cognitive activity and intelligent behavior
    Are the methods well-suited for this research? Highly appropriate The research presented in the preprint is fundamentally a comprehensive conceptual analysis and theoretical organization, and this approach is highly well-suited for the stated objective of addressing the definitional ambiguity surrounding the central concepts of cognition and intelligence across multiple disciplines. To achieve this goal, the methodology relies on organizing the complex conceptual landscape by establishing and analyzing two fundamental theoretical dividing lines: the distinction between mentalist and embodied cognition frameworks and the differentiation between human-centered and life-centered perspectives. This comparative method is appropriate because it provides the essential scaffolding necessary to understand the theoretical tensions within the field and how different research traditions have approached defining cognitive activity and intelligent behavior. The suitability is further evident in the use of structured comparison and synthesis, such as detailing the evolution of human-centered perspectives and formalizing distinctions using comparative tables, which effectively illuminates the divergences in understanding, ranging from cognition as abstract mental processes to cognition as intrinsic life processes
    Are the conclusions supported by the data? Highly supported The conclusions are thoroughly supported by the data, which, in this theoretical preprint, consists of the comprehensive organization and analysis of the conceptual landscape of cognition and intelligence across multiple disciplines. The main conclusions, which articulate the fundamental divergence between the human-centered and the life-centered traditions, are directly substantiated by the detailed comparative analysis provided throughout the paper. The study utilizes structured evidence, including historical development tracking the shift from classical mentalism to 4E cognition, formal definitions contrasting the two frameworks (e.g., in Table 1, comparing scope and nature of cognitive process), and the identification of specific researchers associated with each view (Table 2). Lastly, the conclusion that computational and embodied approaches can be integrated is supported by the dedicated analytical section on "New Computationalism," which redefines computation to include morphological and info-computational processes that are inherently embodied in natural systems
    Are the data presentations, including visualizations, well-suited to represent the data? Highly appropriate and clear The data presentations, which primarily utilize comparative tables and a corresponding visualization, are highly suited to represent the theoretical data generated by this conceptual analysis, as the study aims to organize the complex conceptual landscape of cognition and intelligence around two fundamental dividing lines. Specifically, the use of tabular format is an effective method for delineating key theoretical distinctions, such as comparing the human-centered and life-centered approaches based on scope, the nature of cognitive process, and the definition of intelligence (Table 1). Tables are also appropriately employed to summarize and categorize the specific views of various key researchers regarding cognition and intelligence within the differing perspectives (Table 2), and to define and illustrate diverse computation models found in biological systems (Table 3). The inclusion of Figure 1 further enhances clarity by visualizing the relationships between the two core theoretical divisions-Mentalism versus Embodied Cognition and Human-centered versus Life-centered approaches-which provides essential scaffolding for understanding the field's theoretical tensions
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly The authors clearly discuss, explain, and interpret their theoretical findings by addressing the persistent definitional ambiguity surrounding cognition and intelligence and organizing the conceptual landscape into two fundamental, divergent orientations: the human-centered tradition and the life-centered tradition. They explain the human-centered perspective as defining cognition as distinctively human mental processes and intelligence as a subset of reasoning, problem-solving, and learning capacity, privileging abstract symbolic operations, while interpreting the life-centered view as identifying cognition with life processes themselves and intelligence as the competency of living systems to solve problems under novelty and uncertainty across all biological scales. The discussion meticulously interprets how these divergences fundamentally shape interpretations of mind, life, and intelligent technologies, noting that human-centered approaches dominate mainstream psychology, while life-centered approaches prevail in biology and systems theory. A key interpretation is provided in the "New Computationalism" section, where the authors explain how the alleged contradiction between computational and embodied approaches is dissolved by redefining computation as necessarily embodied information processing in natural systems, suggesting that sophisticated intelligence emerges through integrating information processing with physical organization. Regarding next steps, the authors conclude that future research may benefit from recognizing the complementary insights of both traditions, leveraging human-centered approaches for analyzing complex symbolic reasoning and life-centered approaches for revealing fundamental cognitive processes
    Is the preprint likely to advance academic knowledge? Highly likely The preprint is highly likely to advance academic knowledge because it systematically addresses the persistent definitional ambiguity surrounding the concepts of cognition and intelligence across multiple disciplines by effectively organizing the conceptual landscape. The study provides essential scaffolding for understanding the field's theoretical tensions by establishing two fundamental dividing lines-, Mentalism versus Embodied Cognition, and Human-centered versus Life-centered perspectives, and clearly articulating the divergences in defining cognitive activity and intelligent behavior. A significant advancement is the resolution of the alleged contradiction between computational and embodied approaches, demonstrated through "New Computationalism" which explains how sophisticated intelligence emerges by understanding computation as necessarily embodied information processing in natural systems. Moreover, the research contributes crucial insights by detailing how the theoretical divergence fundamentally shapes interpretations and practices in artificial intelligence, medicine, and neuroscience, thereby providing a clear foundation for future longitudinal research that can leverage the complementary insights of both human-centered and life-centered traditions.
    Would it benefit from language editing? No The language utilized throughout the preprint is generally professional, precise, and highly effective for communicating the complex conceptual analysis and organizing the theoretical landscape of cognition and intelligence, meaning major language issues do not hinder comprehension. The text successfully maintains technical clarity while describing intricate theoretical distinctions, such as those between mentalist and embodied cognition or the divergence between human-centered and life-centered approaches.
    Would you recommend this preprint to others? Yes, it's of high quality The preprint is of high quality and is recommended because it provides essential scaffolding for understanding the pervasive definitional ambiguity of cognition and intelligence across multiple disciplines.
    Is it ready for attention from an editor, publisher or broader audience? Yes, as it is

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  2. PREreview

    This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/17235458.

    This review is the result of a virtual, collaborative Live Review discussion organized by one of PREreview's 2025 Champions on September 20, 2025. The discussion was joined by 5 people: 2 facilitators and 3 live review participants. The authors of this review have dedicated additional asynchronous time over the course of 10 days to help compose this final report using the notes from the Live Review. Special thanks to all participants who contributed to the discussion and made it possible to provide feedback on this preprint.

    Summary:

    This study focuses on the meaning of cognition and intelligence, with greater emphasis placed on the life-centered perspective, which the author considers broader and more encompassing. The main goal is to help humans better understand the nature of mind, life, and intelligent technologies.

    The author approaches the study by evaluating and comparing ideas from existing literature in philosophy, psychology, biology, and artificial intelligence across different periods. The analysis establishes that cognition and intelligence can be viewed from two perspectives—human-centered and life-centered—and shows that these concepts, despite their centrality and ubiquity, are still poorly understood due to narrow definitional frameworks that fail to capture the full scope of current scientific understanding.

    A total of 15 published works were analyzed comparatively and summarized in a table. From this, the ratio of human-centered to life-centered perspectives was 3:4, with only one author bridging the two. The most recent works emphasized the life-centered perspective (21st century), whereas all the human-centered references were from the 20th century. An interesting aspect of the study is that the true definition of intelligence and cognition remains unresolved, which may explain why AI systems, although surpassing humans in some intellectual tasks, still do not behave like humans.

     Despite the fact that the study suggests future upgrades to the definitions of cognition and intelligence and provides value across multiple fields, its main weakness lies in being entirely theoretical, with no empirical data to support its claims.

    List of major concerns and feedback:

    Concerns with techniques and analyses

    • The study is majorly conceptual and theoretical. There were no empirical techniques, analyses, or controls being adopted to get to a conclusion. The problem is that without empirical testing, the claim remains at a theory level and future studies will be needed to validate them with real-life case studies or empirical data. The author could explicitly acknowledge this limitation in the discussion and suggest potential empirical directions (e.g., case studies in biology, cognitive science experiments, or AI simulations) that could help validate or refine the theoretical claims.

    • The manuscript would benefit from the addition of conceptual diagrams or flowcharts which would help visualise the relationship between the frameworks discussed. Adding conceptual diagrams or flowcharts to map how mentalist vs. embodied and human-centered vs. life-centered perspectives intersect would make the arguments more accessible, especially to interdisciplinary readers.

    • There is a risk of overgeneralization when discussing cognition about all forms of life. The author should refine their claims by clarifying that life-centered cognition is still a developing framework and may not apply uniformly across all organisms. Including counterarguments or alternative viewpoints would strengthen the credibility of the study.

    List of minor concerns and feedback:

    •  Sufficient details were provided, but they cannot be replicated and validated empirically. The author could make this clear in the discussion and emphasize that the study is conceptual or theoretical in scope.

    • The author could consider adding short summary paragraphs at the end of each major section to emphasize key points.

    • Headings should be revised for consistency. For example, since sections 2 and 3 compare two traditions, they should follow a similar heading structure to improve clarity.

    Figures and Tables 

    • Figure 1 is vague. It is not well labeled, and there is no key to show what the different color codes mean.The figure should be revised to include a detailed legend or key for all symbols and colors, and axis labels should be added. A short descriptive caption clarifying the figure's purpose would go a long way in helping readers understand the diagram better.

    • The work in the table has to be arranged based on the progression of years or any other pattern that the author might choose to use. It should not be scattered. The table should be arranged either chronologically (by year of publication) or thematically (e.g., grouping human-centered vs. life-centered perspectives). This would improve readability and highlight the historical or conceptual progression.

    • In table 2, the year of reference should be included in the authors' column and not under the title of the work. They could use the APA style of referencing that includes the year of publication. For example, Jean Piaget, 1970.

    • The titles of works are included in Tables 2. Since these will already appear in the reference list, they could be removed to streamline the table. Only the author and year would be sufficient.

    Limitation discussed

    • No limitations of the research were discussed in the manuscript. The author should add a short section to point out the limitations of the study, such as not having real data, depending on selected literature, and the challenge of clearly defining life-centered cognition. This would make the paper more balanced and clear.

    • A potential limitation of the study is that the data depends on selective representation of the literature which may not cover the full range of perspectives. The author only chose some works from the literature, not all possible ones. They should either justify why those works were chosen or admit the study doesn't cover everything.

    Ethics

    Since this study is purely theoretical, no ethical guidelines are required.

    Additional comments 

    • The manuscript does not include new data. It is a theoretical or conceptual study supported entirely by previous literature. No source code or supplementary material is associated with the work. Claims about cognition and intelligence sometimes appear overly generalized without empirical support.

    • The main strength of this study is in its broad and integrative approach, drawing from philosophy, psychology, biology, and artificial intelligence. It challenges the human-centered bias that dominates traditional definitions of cognition and intelligence, and emphasizes cognition as a fundamental property of all living systems. By highlighting gaps in existing definitions, the study encourages future research on adaptive processes in plants, microorganisms, and other simple life forms.

    • The study builds on existing literature across disciplines but shows that most sources are anchored in human-centered or mentalist perspectives. It points out that current definitions of cognition and intelligence are not broad enough, suggesting the need for conceptual updates.

    • The lack of a universally accepted definition of intelligence and cognition is an important insight from the study, helping explain why AI systems can excel at specific tasks yet still fail to behave like humans.

    Concluding remarks

    We thank the authors of the preprint for posting their work openly for feedback. Many thanks also to all participants of the Live Review call for their time and for engaging in the lively discussion that generated this review.

    Competing interests

    The authors declare that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The authors declare that they did not use generative AI to come up with new ideas for their review.

  3. Version published to 10.20944/preprints202508.1840.v1