What would be pre-modern human cognition?

In the terms of cognitive abilities, the highest species is humans. However, human cognitive capacity is not unlimited. Internal and external resources are used to complete cognitive tasks. The concept of cognitive offloading refers to the methods used to increase cognitive performance. This study aims to bring this concept into Turkish psychology literature by presenting a general framework about the concept of cognitive offloading, which can be considered as new. Studies show that cognitive offloading is frequently used by humans. Evaluations made by metacognitive processes decide when to cognitive offloading. However, evaluations made by metacognitive processes are not always accurate. Cognitive limitations are sometimes exaggerated and cognitive offloading is used even if it is not needed. Although cognitive offloading causes increased performance, it also makes us susceptible to various performance failures such as false memory. Current studies have led up for many studies to get better understanding humans’ cognitive processes. Further studies on this subject will enable the understanding of human cognition and the use of this ability more effectively. Keywords cognitive offloading, intention offloading, metacognition, cognitive capacity, cognitive load

The idea that human cognitive capacities are explainable by computational models is often conjoined with the idea that, while the states postulated by such models are in fact realized by brain states, there are no type-type correlations between the states postulated by computational models and brain states (a corollary of token physicalism). I argue that these ideas are not jointly tenable. I discuss the kinds of empirical evidence available to cognitive scientists for (dis)confirming computational models of cognition and argue that none of these kinds of evidence can be relevant to a choice among competing computational models unless there are in fact type-type correlations between the states postulated by computational models and brain states. Thus, I conclude, research into the computational procedures employed in human cognition must be conducted hand-in-hand with research into the brain processes which realize those procedures.

Many human cognitive capacities are rendered possible by enculturation in combination with specific neuronal and bodily dispositions. Acknowledgment of this is of vital importance for a better understanding of the conditions under which sophisticated cognitive processing routines could have emerged on both phylogenetic and ontogenetic timescales. Subscribing to enculturation as a guiding principle for the development of genuinely human cognitive capacities means providing a description of the socio-culturally developed surrounding conditions and the profound neuronal and bodily changes occurring as a result of an individual’s ongoing interaction with its cognitive niche. In this commentary, I suggest that the predictive processing framework can refine and enrich important assumptions made by the theory of cognitive integration and the associated approach to enculturated cognition. I will justify this suggestion by considering several aspects that support the complementarity of these two frameworks on conceptual grounds. The result will be a new integrative framework which I call enculturated predictive processing. Further, I will supplement Richard Menary’s enculturated approach to mathematical cognition with an account of reading acquisition from this new perspective. In sum, I argue in this paper that the cognitive integrationist approach to enculturated cognition needs to be combined with a predictive processing style description in order to provide a full account of the neuronal, bodily, and environmental components giving rise to cognitive practices. In addition, I submit that the enculturated predictive processing approach arrives at a conceptually coherent and empirically plausible description of reading acquisition.

In this paper, I propose to understand argumentative decoupling—that is, the structural fact of the argumentative chain self-referring to one (or more) of its constituents (reason, data, conclusion, point of view) in subsequent arguments—as part of the way in which cognitive decoupling representation works. In order to support this claim, I make use of part of the discussion developed in cognitive studies and evolutionary theories that describes this phenomenon when explaining intentional communication. By using Toulmin’s model, I exemplify how decoupling representation may be seen as part of a chain of arguments in which a second argumentative move is usually oriented to action. I conclude by reflecting on the relationship between this human cognitive capacity and the problem of recursion to hold that these two concepts are not synonymous but stand in a subordinated and complementary relation to each other.

Foundations of Evolutionary Economics, Chapter Five: Networks

Business Intelligence and Artificial Intelligence represent two transformative forces reshaping organizational decision-making processes. Business Intelligence offers structured frameworks for data collection, storage, visualization, and reporting. Artificial Intelligence extends analytical capabilities through machine learning algorithms, predictive modeling, and natural language processing. The integration of both technologies creates a powerful synergy for modern enterprises. Data warehousing architectures serve as foundational infrastructure for analytical operations. Dimensional modeling organizes information to facilitate efficient querying and historical comparison. Dashboard interfaces transform complex datasets into intuitive visual representations. Machine learning enables pattern recognition beyond human cognitive capacity. Predictive models anticipate future trends based on historical observations. Natural language interfaces democratize access to analytical insights across organizational hierarchies. Bias mitigation and fairness considerations demand attention during model development and deployment. Interpretability requirements ensure regulatory compliance and stakeholder trust. Edge computing architectures distribute analytical processing closer to data generation points. Autonomous analytics platforms reduce manual intervention through automated insight generation. Bringing together organized rules with smart automation helps companies gain an edge in markets that rely on data.

The Importance of Data Access Regimes for Artificial Intelligence and Machine Learning

The rapid, perplexing increase in the incidence of autism has led to a correlative increase in research on it and on normally developing children as well. In this paper I consider some of this research, not only for what it shows us about human cognitive capacities but also for its suggestive implications regarding the ability of science to teach us about the world.

G. E. R. Lloyd's economically persuasive study addresses the question of the universalism or relativism of rationality. Drawing careful comparisons, primarily between ancient Greek and Chinese thought, but also more widely, Lloyd introduces a range of disciplinary perspectives and specific points of focus. In doing so, he challenges his reader to think critically about their own assumptions and concepts. In particular, he asks us to consider the degree to which our own broad concepts, especially oppositions such as between rationality and irrationality, are themselves informed by their derivation from ancient Greek thought. His first chapter (‘Aims and Methods’) introduces his central commitments. Rationality and irrationality are not universal across societies in such a way that they can be judged by a single set of criteria. But nor are they just cultural constructs, so that the possibility of mutual intelligibility collapses. The truth lies somewhere in between, in the recognition of the heterogeneity to be identified in what is shared across cultures. Lloyd argues that ancient China is a particularly useful foil for a consideration of these questions, since it provides a perspective from beyond the reach of the Graeco-Roman legacy. His subtle middle road is further supported by his second chapter (‘Rationality Reviewed’), which summarizes some influential accounts of rationality and considers the ‘state of play’ across a variety of disciplines, including palaeontology, child development, and psychology, all of which present evidence of continuities between societies. The next four chapters approach the question of the diversity and commonality of reason from a range of perspectives, including cosmology, metaphysics, language, epistemology, and religion. In the case of cosmology, for example, Lloyd argues that we can identify a difference between the Greeks’ tendency to focus on the thing that is ‘Nature’, and the Chinese interest in natural phenomena and processes, absent a concept of ‘Nature’ itself. He is careful to note the difficulty of generalizing across all Greek or all Chinese thinkers. We can, however, identify a significantly similar belief in the two societies: that understanding the cosmos matters for the sake of the life you live as a result of that knowledge. In the case of the binary ‘Seeming and Being’ (as discussed in Chapter 4), Lloyd argues that the Chinese shared with the Greeks an awareness that appearances can be deceptive. However, their conception of the fundamental binaryyinandyangis one of interdependence rather than sharp differentiation, such as we sometimes see in Greek thought between Being and Becoming. Throughout the volume, Lloyd argues for the need to recognize both the similarities and the differences identified as a result of careful comparative study. He ends with a recommendation for his readers to reconsider the universal applicability of certain key Western concepts, without resorting to a claim that it is impossible to recognize or communicate similarities. We must, he suggests, work from a position that demonstrates ‘due recognition both of the commonalities in human cognitive capacities, and of the differences in their deployment’ (96).

When presented with two fully proved formal methods-based specifications, how can a System Engineer decide which is superior when both models specify the same requirements, but in two different ways? This paper investigates and propose a methodology by which formal methods (using the specific example of the Event-B notation) can be differentiated in terms of their quality, using criteria that may be highly subjective in nature. Established complexity functions applied to software are not applicable to formal methods, thus the paper proposes a new function which quantifies the “quality” of a given model. Complexity is not the only factor involved in determining the quality of formal methods, the quality of system thinking involved also play an impactful role. We propose a quality function which uses the well-established properties of axiomatic systems in theoretical mathematics with the addition of a specifically formulated complexity function. The distinction criteria are based on evaluating how four main properties have been achieved: “Consistency”, “Completeness”, “Independence” and “Complexity”. We base our approach according to the paradigm of; “if the formal specification looks visually complicated for a set-theory novice, then it is a poorly modeled specification”. Furthermore, we explore the notion of Miller’s rule (magic No. 7) to define what “good” should look like. We conclude that we need more than Miller’s 7, we need 1, 2 and 3 to help us with defining what good quality looks like, by taking human cognitive capacity as a benchmark. This novel approach implies considerable further research, described in future work section.

Traits that are clinally distributed are under the control of selective forces that are distributed in graded fashion. Traits that cluster in certain regions are simply the results of relatedness and are not adaptively important. Traits that are of equal survival value for all human populations should show no average difference from one population to another. Human cognitive capacity, founded on the ability to learn a language, is of equal survival value to all human groups, and consequently there is no valid reason to expect that there should be average differences in intellectual ability among living human populations. The archaeological record shows that, at any one time during the Pleistocene, survival strategies were essentially the same throughout the entire range of human occupation. Both archaeological and biological data contribute to the picture of the slow emergence of human linguistic behavior and its subsequent maturation. The similarities in human capability were not the result of a sudden, recent, and localized common origin. Instead, the widely shared common human condition was the consequence of a long-term adaptation to common conditions during which specific unity was maintained by low but nontrivial rates of genetic exchange among groups. The differences in human lifeways that have arisen since the end of the Pleistocene--and in most instances much more recently--have had too little time to have had any measurable effect on the generation of inherited differences in intellectual ability. When average group differences in "intelligence" test scores are encountered, the first conclusion to be drawn is that the circumstances under which intellectual capabilities are nurtured and developed are not the same for the groups in question. Where such tests show different "racial" averages in test scores, this should be taken as an index of the continuing effects of "race" prejudice and not of inherent differences in capability.

The paper seeks to explore the hidden assumptions that are imbedded in a modern, atheistic, naturalistic philosophical outlook, and the conclusions of which are often overlooked. Particularly, the authors highlight that a philosophically naturalistic outlook leads to untenable conclusions regarding human morality, volition, and subjective conscious experience. The analysis finds that a modern approach, if taken to its logical conclusion, would leave humanity bereft of meaning. The authors argue that the naturalistic approach requires leaps of faith regarding human cognitive capacities, as it assumes sound reasoning without justification to such a premise. The authors conclude that religious grounding, specifically an Islamic conceptual framework, is necessary to account for consciousness, logic, and morality, while the abandonment of this tradition along with the metaphysical foundation it provides leaves the modern man struggling to justify rationality, moral arguments, and even basic articulation with which he rejects faith in God. Thus, the authors conclude that modernity, while commended for its advancements in the sciences, must not lose the metaphysical underpinnings upon which it is founded.

This article explores the psychology behind thinking and communicating, subsequently proposing a pragmatic model for improving these processes. It begins from the consideration that we all operate very limited cognitive “machines”: in an average lifetime, the human brain can theoretically store up to 0.0000084% (8.4×10⁻⁸) and consciously process some 0.0000000000512% (5.12×10⁻¹³) of the (digital) information that was ever created, captured or replicated by humans. Such a dismally low ratio between human cognitive capacities on the one side, and the total amount of existing information on the other means that thinking and communicating—especially on “difficult” topics such as warfare, politics or religion—usually involves unilateral or hypolateral thinking. This is defined as people’s general tendency to ignore most of the existing information on any topic; to specialize only on information immediately available and; to use cognitive strategies and other cognitive meta-mechanisms to simplify thinking processes. On the basis of these considerations, the article proposes: (1) a logical proof of why most of our “objective” knowledge is in fact built from emotions and intentions, rather than from rationality and ontological proofs—suggesting that our “inner world” is the ultimate driver of the “outer world” as we perceive it; and (2) a model of hyperlateral or omnilateral thinking, whereby we consciously follow a technique to become aware of the existence of a multitude of perspectives on any one topic, a necessary precondition for meaningful thinking and communication to happen.

Finding Ourselves after Darwin: Conversations on the Image of God, Original Sin, and the Problem of Evil

Archaic and modern human frontal bones are known to be quite distinct externally, by both conventional visual and metric evaluation. Internally this area of the skull has been considerably less well-studied. Here we present results from a comparison of interior, as well as exterior, frontal bone profiles from CT scans of five mid-Pleistocene and Neanderthal crania and 16 modern humans. Analysis was by a new morphometric method, Procrustes analysis of semi-landmarks, that permits the statistical comparison of curves between landmarks. As expected, we found substantial external differences between archaic and modern samples, differences that are mainly confined to the region around the brow ridge. However, in the inner median-sagittal profile, the shape remained remarkably stable over all 21 specimens. This implies that no significant alteration in this region has taken place over a period of a half-million years or more of evolution, even as considerable external change occurred within the hominid clade spanning several species. This confirms that the forms of the inner and outer aspects of the human frontal bone are determined by entirely independent factors, and further indicates unexpected stability in anterior brain morphology over the period during which modern human cognitive capacities emerged. Anat Rec (New Anat): 257:217-224, 1999.