scholarly journals An Active Inference Model of Collective Intelligence

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 830
Author(s):  
Rafael Kaufmann ◽  
Pranav Gupta ◽  
Jacob Taylor
Keyword(s):  
Theory Of Mind ◽  
Cognitive Ability ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Composite System ◽  
Collective Intelligence ◽  
Active Inference ◽  
Goal Alignment ◽  
Alignment Model ◽  
The Relationship

Collective intelligence, an emergent phenomenon in which a composite system of multiple interacting agents performs at levels greater than the sum of its parts, has long compelled research efforts in social and behavioral sciences. To date, however, formal models of collective intelligence have lacked a plausible mathematical description of the relationship between local-scale interactions between autonomous sub-system components (individuals) and global-scale behavior of the composite system (the collective). In this paper we use the Active Inference Formulation (AIF), a framework for explaining the behavior of any non-equilibrium steady state system at any scale, to posit a minimal agent-based model that simulates the relationship between local individual-level interaction and collective intelligence. We explore the effects of providing baseline AIF agents (Model 1) with specific cognitive capabilities: Theory of Mind (Model 2), Goal Alignment (Model 3), and Theory of Mind with Goal Alignment (Model 4). These stepwise transitions in sophistication of cognitive ability are motivated by the types of advancements plausibly required for an AIF agent to persist and flourish in an environment populated by other highly autonomous AIF agents, and have also recently been shown to map naturally to canonical steps in human cognitive ability. Illustrative results show that stepwise cognitive transitions increase system performance by providing complementary mechanisms for alignment between agents’ local and global optima. Alignment emerges endogenously from the dynamics of interacting AIF agents themselves, rather than being imposed exogenously by incentives to agents’ behaviors (contra existing computational models of collective intelligence) or top-down priors for collective behavior (contra existing multiscale simulations of AIF). These results shed light on the types of generic information-theoretic patterns conducive to collective intelligence in human and other complex adaptive systems.

The crucial roles of the artificial information systems web in intelligent human organizations

2003 ◽  
Vol 22 (3) ◽  
pp. 115-124
Author(s):  
Liang Thow Yick
Keyword(s):  
Information Systems ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Collective Intelligence ◽  
Physical Structure ◽  
Current Status ◽  
Human Beings ◽  
Intelligent Structure ◽  
Complex Adaptive ◽  
Human Thinking

Human organizations with human beings as interacting agents are complex adaptive systems. Such organizations continuously consume information, make decisions, and evolve with the changing environment. In this respect, all human organizations including businesses must enhance their collective intelligence in order to learn faster and compete more effectively. Thus, adopting an intelligent structure is vital to all businesses as the world moves deeper into the knowledge economy. The paradigmatic shift in thinking, structure, management and operation requires all intelligent human organizations to be designed around intelligence. An intelligent structure encompasses an orgmind, an intangible deep component, as well as a physical component. At the physical structure perspective, being able to identify, design and develop an artificial information systems network that synchronizes well with the orgmind is critical. The connectivity of the organization, and the manner in which it behaves, communicates and collaborates, depend on the effectiveness of its information systems network and its orgmind. The orgmind which is at least the collection of all the interacting human thinking systems must be fully aware of both the internal and external environments. Inevitably, in the new economy, intelligent human organizations must be equipped with a well-integrated intelligent information network which functions similarly to the nervous system in biological beings. This study examines the current status of artificial information systems and their networks in businesses with respect to the above concepts.

Exploring an adaptability approach: how creative return processors impact firm performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jennifer A. Espinosa ◽  
James Stock ◽  
David J. Ortinau ◽  
Lisa Monahan
Keyword(s):  
Empirical Evidence ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Online Survey ◽  
Theoretical Perspective ◽  
Product Returns ◽  
Content Type ◽  
Underlying Mechanisms ◽  
Returns Management ◽  
The Relationship

PurposeThe authors explore complex adaptive systems (CAS) theory as an updated theoretical perspective for managing product returns that better matches the chaotic nature of recent consumer behaviors. CAS theory highlights the importance of agents who create and self-organize to help systems adapt in unpredictable environments.Design/methodology/approachThis research utilizes data collected from return managers in an online survey and applies regression analyses to estimate the influence of the focal variables.FindingsEmpirical evidence of the firm flexibility–firm adaptability link is established, and return processor creativity positively relates to this link. The firm flexibility–firm adaptability link fully mediates the relationship between return processor creativity and returns management performance and partially mediates the relationship between return processor creativity and relationship quality. Nonmediated effects were observed for turnover and revenue size.Practical implicationsManagers of returns who embrace an adaptability approach become facilitators of returns by supporting processor creativity. Enhancing the autonomy of processors in their day-to-day work increases the knowledge-creation capabilities of the firm, which helps the firm move forward and adapt in an uncertain environment.Originality/valueThis research presents empirical evidence of the underlying mechanisms of CAS theory in the product returns context by studying processor agents and argues that CAS theory better fits the current dynamics of the product returns environment. Further, this paper extends work by Espinosa et al. (2019) and Nilsson (2019) by studying how a specific human characteristic – creativity – impacts product returns management.

scholarly journals Language change and language evolution: Cousins, siblings, twins?

Glottotheory ◽  
2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Stefan Hartmann
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Language Change ◽  
Historical Linguistics ◽  
Language Evolution ◽  
Integrated Approach ◽  
Complex Adaptive ◽  
Research Questions ◽  
The Relationship ◽  
Cross Fertilization

AbstractThe relationship between “language change” and “language evolution” has recently become subject to some debate regarding the scope of both concepts. It has been claimed that while the latter used to refer to the language origins in the first place, both terms can now, to a certain extent, be used synonymously. In this paper, I argue that this can partly be explained by parallel developments both in historical linguistics and in the field of language evolution research that have led to a considerable amount of convergence between both fields. Both have adopted usage-based approaches and data-driven methods, which entails similar research questions and similar perspectives on the phenomena under investigation. This has ramifications for current models and theories of language change (or evolution). Two approaches in particular, the concept of complex adaptive systems and construction grammar, have been combined in integrated approaches that seek to explain both language emergence and language change over historical time. I discuss the potential and limitations of this integrated approach, and I argue that there is still some unexplored potential for cross-fertilization.

The Neuroscience of Gender Bias within Organisations: Implicit and Explicit Influences

2021 ◽  
Author(s):  
◽  
James Wicks
Keyword(s):  
Gender Bias ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Social Cognitive ◽  
Group Composition ◽  
Explicit Bias ◽  
Complex Adaptive ◽  
And Gender ◽  
Implicit And Explicit ◽  
The Relationship

<p>It has been 30 years since the metaphor of a ‘glass ceiling’ was introduced, yet progress to address gender bias in organisations has been slow. Within a context in which employment is rapidly changing and technologies are enabling new ways of working, gender bias in organisations remains a persistent and complex issue that requires new ways of thinking. This study integrates across two scientific disciplines: social cognitive neuroscience and complex adaptive systems, in order to examine the complex nature of gender bias in organisations and advance implications for practice.  The central proposition underlying this study is that the gender composition of a person’s ‘in-group’, that is the group of people one most closely relates to in a work setting, has implications for their level of gender bias. The relationship between in-group composition and gender bias is examined from implicit (unconscious) and explicit (conscious) bias perspectives. The composition of in-group is measured by homogeneity, size and trust, and is captured within an integrated instrument that includes measures of implicit and explicit bias.  The study is informed by the theory of interactive person construal. It is proposed that biases are a dynamic, continuously evolving phenomena emerging from top down and bottom up cues. Specifically, the essence of this research is the relationship between the neuroscientific dynamics of in-group and out-group differentiation within the human brain and the complex systemic nature of the modern workplace. The study endeavours to make a contribution to the understanding of how people who share common values and interests (ingroup) influence gender bias in organisations.  The research has been conducted in a professional services organisation. A group of people within the organisation were asked to participate in an online survey to capture implicit bias, explicit bias, composition of their in-group and demographic details. This research applied a quantitative survey methodology.  The aims of the study are to:  • examine the relationship between in-group composition and gender bias building from theoretical insights from neuroscience and complex adaptive systems theory,  • test both implicit and explicit attitudes towards gender bias,  • test the relationship between implicit and explicit measures of bias, and  • provide a contribution to theory and practice in relation to addressing the issue of gender bias in organisations.  It is concluded that there is a statistically significant association between in-group composition and the manifestation of implicit and explicit bias using a variety of measures. The model of in-group composition developed for this study could be used as a means to understand gender system dynamics. A dynamic systems model of bias is proposed based on the research variables and complexity ideas examined in the study. For organisations, this research has implications for how the issue of gender bias should be approached. Connecting ideas from social cognitive neuroscience and complex adaptive systems, this research highlights the interrelationship between recurring levels (neural, individual, group, organisation) within the bias system and the nature of interventions that may lead to enduring change.</p>

The new intelligence leadership strategy for iCAS

2007 ◽  
Vol 26 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Thow Yick Liang
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Collective Intelligence ◽  
Evolutionary Model ◽  
Biological Species ◽  
Leadership Strategy ◽  
Complex Adaptive ◽  
Human Thinking ◽  
Knowledge Intensive ◽  
New Generation

As humanity becomes more dependent on information and knowledge, the current concepts, theories and practices associated with leadership strategy have to be transformed. Fundamentally, the influence of the knowledge-intensive, fast-changing and more complex environment has initiated a shift in the mindset, strategic thinking, ability and style in the new generation of leaders. In addition, for all categories of human organizations (economics, business, social, education and political) their members are becoming better educated and informed, and consequently they are more sophisticated interacting agents with modified expectations. Leading these new intelligent human organizations is drastically different from leading a traditional setup. Consequently, the introduction of a new leadership strategy is inevitable. Concurrently, in the new context, it is also highly significant to recognize that all human thinking systems and human organizations are indeed complex adaptive systems. In such systems, order and complexity co-exist, and they learn, adapt and evolve with the changing environment, similar to the behavior of any biological species in an ecological system. The complex and nonlinear evolving dynamic is driven by the intrinsic intelligence of the individuals and the collective intelligence of the group. Therefore, focusing and exploiting the bio-logic rather than machine-logic perspective is definitely more appropriate. In this respect, a better comprehension of leadership strategy and organizational dynamics can be acquired by “bisociating” the complexity theory and the concept of organizing around intelligence. The resulting evolutionary model of this analysis is the intelligence leadership strategy.

Intelligence strategy: The integrated 3C-OK framework of intelligent human organizations

2004 ◽  
Vol 23 (4) ◽  
pp. 203-211 ◽  
Author(s):  
T.Y. Liang
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Collective Intelligence ◽  
Knowledge Structures ◽  
Human Beings ◽  
Complex Adaptive ◽  
Human Thinking ◽  
Knowledge Intensive ◽  
High Level

As humanity immerses deeper into the knowledge-intensive era, the mindset for leading, managing and structuring human organizations has to be transformed. Attention has been shifting from tangible to intangible assets. Human thinking systems, the sources where the world's most intense intrinsic intelligence originates become the key focal center. Intelligence and its dynamic are nonlinear. Arising from human consciousness are the two vital mental functions of awareness and mindfulness. These functions determine the quality of the mental state of the interacting agents. In addition, a high level of intelligence facilitates faster learning. All competitive human beings learn continuously to enhance the quality of their knowledge structures. Consequently, the bio-logic and human decision-making process improve. These activities constitute a critical component of the evolution dynamic. Similar to any intelligent biological organisms, all human organizations as composite complex adaptive systems must also nurture their own orgmind and collective intelligence to ensure their relevance and survival in the new context. Concurrently, activities such as continuous organizational learning, facilitating effective knowledge management processes, and building quality corporate knowledge structures must be cultivated. A mindful culture manifesting collaborative and sharing characteristic is crucial for sustaining the integrated dynamic. Recognizing the interdependency of the attributes involved is a key requirement. The 3C-OK framework to be conceptualized in this analysis is an attempt to enhance the new mindset.

Nurturing intelligent human systems: the nonlinear perspective of the human minds*

2001 ◽  
Vol 20 (4) ◽  
pp. 281-289 ◽  
Author(s):  
Liang Thow Yick
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Collective Intelligence ◽  
New Paradigm ◽  
Edge Of Chaos ◽  
Order And Disorder ◽  
Complex Adaptive ◽  
Knowledge Structuring ◽  
The Universe ◽  
Human Systems

Organizing around intrinsic intelligence is a new paradigm that all human organizations must adopt if they wish to evolve successfully in the emerging intelligence revolution. This fresh mindset perceives human systems as intelligent corporate beings possessing an orgmind and a collective intelligence of their own. Intelligence is the entity that drives the universe and its microcosms. Some attributes associated with human intelligence are mindfulness, information processing, knowledge structuring, and nonlinearity. Nonlinearity, in particular, is manifested because the inherent sources of intelligence, the human minds, are complex adaptive systems where order and disorder co-exist. Human organizations that are intelligent are able to tap on and exploit these characteristics collectively and effectively. Consequently, these organizations are able to learn, adapt, self-organize and co-evolve quickly with their environment as biological beings. Their intelligent structure is also better at exploiting the innovative and creative energy embedded at the edge of chaos.

The Neuroscience of Gender Bias within Organisations: Implicit and Explicit Influences

2021 ◽  
Author(s):  
◽  
James Wicks
Keyword(s):  
Gender Bias ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Social Cognitive ◽  
Group Composition ◽  
Explicit Bias ◽  
Complex Adaptive ◽  
And Gender ◽  
Implicit And Explicit ◽  
The Relationship

<p>It has been 30 years since the metaphor of a ‘glass ceiling’ was introduced, yet progress to address gender bias in organisations has been slow. Within a context in which employment is rapidly changing and technologies are enabling new ways of working, gender bias in organisations remains a persistent and complex issue that requires new ways of thinking. This study integrates across two scientific disciplines: social cognitive neuroscience and complex adaptive systems, in order to examine the complex nature of gender bias in organisations and advance implications for practice.  The central proposition underlying this study is that the gender composition of a person’s ‘in-group’, that is the group of people one most closely relates to in a work setting, has implications for their level of gender bias. The relationship between in-group composition and gender bias is examined from implicit (unconscious) and explicit (conscious) bias perspectives. The composition of in-group is measured by homogeneity, size and trust, and is captured within an integrated instrument that includes measures of implicit and explicit bias.  The study is informed by the theory of interactive person construal. It is proposed that biases are a dynamic, continuously evolving phenomena emerging from top down and bottom up cues. Specifically, the essence of this research is the relationship between the neuroscientific dynamics of in-group and out-group differentiation within the human brain and the complex systemic nature of the modern workplace. The study endeavours to make a contribution to the understanding of how people who share common values and interests (ingroup) influence gender bias in organisations.  The research has been conducted in a professional services organisation. A group of people within the organisation were asked to participate in an online survey to capture implicit bias, explicit bias, composition of their in-group and demographic details. This research applied a quantitative survey methodology.  The aims of the study are to:  • examine the relationship between in-group composition and gender bias building from theoretical insights from neuroscience and complex adaptive systems theory,  • test both implicit and explicit attitudes towards gender bias,  • test the relationship between implicit and explicit measures of bias, and  • provide a contribution to theory and practice in relation to addressing the issue of gender bias in organisations.  It is concluded that there is a statistically significant association between in-group composition and the manifestation of implicit and explicit bias using a variety of measures. The model of in-group composition developed for this study could be used as a means to understand gender system dynamics. A dynamic systems model of bias is proposed based on the research variables and complexity ideas examined in the study. For organisations, this research has implications for how the issue of gender bias should be approached. Connecting ideas from social cognitive neuroscience and complex adaptive systems, this research highlights the interrelationship between recurring levels (neural, individual, group, organisation) within the bias system and the nature of interventions that may lead to enduring change.</p>

U-Learning Pedagogical Management

2014 ◽  
pp. 270-288
Author(s):  
Jocelma Almeida Rios ◽  
Emanuel do Rosário Santos Nonato ◽  
Mary Valda Souza Sales ◽  
Tereza Kelly Gomes Carneiro
Keyword(s):  
Cognitive Ability ◽  
Cognitive Processes ◽  
Knowledge Construction ◽  
Positive Impact ◽  
Collective Intelligence ◽  
Collaborative Work ◽  
Learning Management Systems ◽  
The Internet ◽  
Physical Presence ◽  
The Relationship

The Internet has permitted some changes that may not have been foreseen on its initial design. We started to constitute friendly or professional interactions, and it eventually enabled the emergence of collaborative actions that resulted in cognitive processes in unusual ways, that is, that take place without the physical presence of those involved but with the effective participation of everyone involved in a broad and democratic approach, constituting a collective intelligence. In the professional world, these interactions can turn into significant gains to developed activities. This chapter reviews relevant findings concerning the cognitive aspects related to the knowledge construction developed under the collaborative work approach in Learning Management Systems (LMS). When working collaboratively in a LMS, the subjects engage in cognitive processes mediated by hypermedia resources that potentially have positive impact on their ability to construct, sense, and/or produce knowledge, to the extent that these resources dynamically dialogue with the already markedly multimodal human cognitive ability. In order to support the analysis, the authors present the relationship between cognitive processes and hypermedia and their influence on knowledge production in an LMS. They also present two experiences developed in Moodle, which showed the possibility of using such resources for people prone to collaboration, resulting in a continuous design optimization of the mentioned course.

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