Against simplicity and cognitive individualism: Nathaniel T. Wilcox

Neuroeconomics illustrates our deepening descent into the details of individual cognition. This descent is guided by the implicit assumption that “individual human” is the important “agent” of neoclassical economics. I argue here that this assumption is neither obviously correct, nor of primary importance to human economies. In particular I suggest that the main genius of the human species lies with its ability to distribute cognition across individuals, and to incrementally accumulate physical and social cognitive artifacts that largely obviate the innate biological limitations of individuals. If this is largely why our economies grow, then we should be much more interested in distributed cognition in human groups, and correspondingly less interested in individual cognition. We should also be much more interested in the cultural accumulation of cognitive artefacts: computational devices and media, social structures and economic institutions

Expertise and intuition: A tale of three theories

Several authors have hailed intuition as one of the defining features of expertise. In particular, while disagreeing on almost anything that touches on human cognition and artificial intelligence, Hubert Dreyfus and Herbert Simon agreed on this point. However, the highly influential theories of intuition they proposed differed in major ways, especially with respect to the role given to search and as to whether intuition is holistic or analytic. Both theories suffer from empirical weaknesses. In this paper, we show how, with some additions, a recent theory of expert memory (the template theory) offers a coherent and wide-ranging explanation of intuition in expert behaviour. It is shown that the theory accounts for the key features of intuition: it explains the rapid onset of intuition and its perceptual nature, provides mechanisms for learning, incorporates processes showing how perception is linked to action and emotion, and how experts capture the entirety of a situation. In doing so, the new theory addresses the issues problematic for Dreyfus’s and Simon’s theories. Implications for research and practice are discussed

Social Machinery and Intelligence

Social machines are systems formed by technical and human elements interacting in a structured manner. The use of digital platforms as mediators allows large numbers of human participants to join such mechanisms, creating systems where interconnected digital and human components operate as a single machine capable of highly sophisticated behaviour. Under certain conditions, such systems can be described as autonomous and goal-driven agents. Many examples of modern Artificial Intelligence (AI) can be regarded as instances of this class of mechanisms. We argue that this type of autonomous social machines has provided a new paradigm for the design of intelligent systems marking a new phase in the field of AI. The consequences of this observation range from methodological, philosophical to ethical. On the one side, it emphasises the role of Human-Computer Interaction in the design of intelligent systems, while on the other side it draws attention to both the risks for a human being and those for a society relying on mechanisms that are not necessarily controllable. The difficulty by companies in regulating the spread of misinformation, as well as those by authorities to protect task-workers managed by a software infrastructure, could be just some of the effects of this technological paradigm

Critical thinking and systems thinking: towards a critical literacy for systems thinking in practice

About the book: In reflective problem solving and thoughtful decision making using critical thinking one considers evidence, the context of judgment, the relevant criteria for making the judgment well, the applicable methods or techniques for forming the judgment, and the applicable theoretical constructs for understanding the problem and the question at hand. In this book, the authors present topical research in the study of critical thinking. Topics discussed include developing critical thinking through probability models; the promotion of critical thinking skills through argument mapping; an instructional model for teacher training in critical thinking; advanced academic literacy and critical thinking and critical thinking and higher education

Sustainability Conversations for Impact: Transdisciplinarity on Four Scales

Sustainability is a dynamic, multi-scale endeavor. Coherence can be lost between scales – from project teams, to organizations, to networks, and, most importantly, down to conversations. Sustainability researchers have embraced transdisciplinarity, as it is grounded in science, shared language, broad participation, and respect for difference. Yet, transdisciplinarity at these four scales is not well-defined. In this dissertation I extend transdisciplinarity out from the project to networks and organizations, and down into conversation, adding novel lenses and quantitative approaches. In Chapter 2, I propose transdisciplinarity incorporate academic disciplines which help cross scales: Organizational Learning, Knowledge Management, Applied Cooperation, and Data Science. In Chapter 3 I then use a mixed-method approach to study a transdisciplinary organization, the Maine Aquaculture Hub, as it develops strategy. Using social network analysis and conversation analytics, I evaluate how the Hub’s network-convening, strategic thinking and conversation practices turn organization-scale transdisciplinarity into strategic advantage. In Chapters 4 and 5, conversation is the nexus of transdisciplinarity. I study seven public aquaculture lease scoping meetings (informal town halls) and classify conversation activity by “discussion discipline,” i.e., rhetorical and social intent. I compute the relationship between discussion discipline proportions and three sustainability outcomes of intent-to-act, options-generation, and relationship-building. I consider exogenous factors, such as signaling, gender balance, timing and location. I show that where inquiry is high, so is innovation. Where acknowledgement is high, so is intent-to-act. Where respect is high, so is relationship-building. Indirectness and sarcasm dampen outcomes. I propose seven interventions to improve sustainability conversation capacity, such as nudging, networks, and using empirical models. Chapter 5 explores those empirical models: I use natural language-processing (NLP) to detect the discussion disciplines by training a model using the previously coded transcripts. Then I use that model to classify 591 open-source conversation transcripts, and regress the sustainability outcomes, per-transcript, on discussion discipline proportions. I show that all three conversation outcomes can be predicted by the discussion disciplines, and most statistically-significant being intent-to-act, which responds directly to acknowledgement and respect. Conversation AI is the next frontier of transdisciplinarity for sustainability solutions

Neuroeconomics: How Neuroscience Can Inform Economics

Neuroeconomics uses knowledge about brain mechanisms to inform economic analysis, and roots economics in biology. It opens up the "black box" of the brain, much as organizational economics adds detail to the theory of the firm. Neuroscientists use many tools— including brain imaging, behavior of patients with localized brain lesions, animal behavior, and recording single neuron activity. The key insight for economics is that the brain is composed of multiple systems which interact. Controlled systems ("executive function") interrupt automatic ones. Emotions and cognition both guide decisions. Just as prices and allocations emerge from the interaction of two processes—supply and demand— individual decisions can be modeled as the result of two (or more) processes interacting. Indeed, "dual-process" models of this sort are better rooted in neuroscientific fact, and more empirically accurate, than single-process models (such as utility-maximization). We discuss how brain evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence. We also discuss applications to intertemporal choice, risk and decision making, and game theory. Intertemporal choice appears to be domain-specific and heavily influenced by emotion. The simplified ß-d of quasi-hyperbolic discounting is supported by activation in distinct regions of limbic and cortical systems. In risky decision, imaging data tentatively support the idea that gains and losses are coded separately, and that ambiguity is distinct from risk, because it activates fear and discomfort regions. (Ironically, lesion patients who do not receive fear signals in prefrontal cortex are "rationally" neutral toward ambiguity.) Game theory studies show the effect of brain regions implicated in "theory of mind", correlates of strategic skill, and effects of hormones and other biological variables. Finally, economics can contribute to neuroscience because simple rational-choice models are useful for understanding highly-evolved behavior like motor actions that earn rewards, and Bayesian integration of sensorimotor information

Networks as Emergent Structures from Bilateral Collaboration

In this paper we model the formation of innovation networks as they emerge from bilateral actions. The effectiveness of a bilateral collaboration is determined by cognitive, relational and structural embeddedness. Innovation results from the recombination of knowledge held by the partners to the collaboration, and the extent to which agents’ knowledge complement each others is an issue of cognitive embeddedness. Previous collaborations (relational embeddedness) increase the probability of a successful collaboration; as does information gained from common third parties (structural embeddedness). As a result of repeated alliance formation, a network emerges whose properties are studied, together with those of the process of knowledge creation. Two features are central to the innovation process: how agents pool their knowledge resources; and how agents derive information about potential partners. We focus on the interplay between these two dimensions, and find that they both matter. The networks that emerge are not random, but in certain parts of the parameter space have properties of small worlds. (JEL Classification: L14, Z13, O3 Keywords: Networks, Innovation, Network Formation, Knowledge)industrial organization ;

Exposing piaget's scheme: Empirical evidence for the ontogenesis of coordination in learning a mathematical concept

The combination of two methodological resources-natural-user interfaces (NUI) and multimodal learning analytics (MMLA)-is creating opportunities for educational researchers to empirically evaluate seminal models for the hypothetical emergence of concepts from situated sensorimotor activity. 76 participants (9-14 yo) solved tablet-based non-symbolic manipulation tasks designed to foster grounded meanings for the mathematical concept of proportional equivalence. Data gathered in task-based semi-structured clinical interviews included action logging, eye-gaze tracking, and videography. Successful task performance coincided with spontaneous appearance of stable dynamical gaze-path patterns soon followed by multimodal articulation of strategy. Significantly, gaze patterns included uncued non-salient screen locations. We present cumulative results to argue that these 'attentional anchors' mediated participants' problem solving. We interpret the findings as enabling us to revisit, support, refine, and elaborate on central claims of Piaget's theory of genetic epistemology and in particular his insistence on the role of situated motor-action coordination in the process of reflective abstraction

Enkinaesthetic polyphony: the underpinning for first-order languaging

We contest two claims: (1) that language, understood as the processing of abstract symbolic forms, is an instrument of cognition and rational thought, and (2) that conventional notions of turn-taking, exchange structure, and move analysis, are satisfactory as a basis for theorizing communication between living, feeling agents. We offer an enkinaesthetic theory describing the reciprocal affective neuro-muscular dynamical flows and tensions of co- agential dialogical sense-making relations. This “enkinaesthetic dialogue” is characterised by a preconceptual experientially recursive temporal dynamics forming the deep extended melodies of relationships in time. An understanding of how those relationships work, when we understand and are ourselves understood, when communication falters and conflict arises, will depend on a grasp of our enkinaesthetic intersubjectivity