Interactive genetic algorithm assisted with collective intelligence from group decision making

Japanese corporate law (the Companies Act) requires that boards have three or more directors, and thus makes group decision making obligatory within firms. But according to some observers, boards of directors are often a mere formality in Japan, especially for non-public and small-to-medium-sized firms. The literature of behavioural science shows that group decision making does not necessarily produce better outcomes than individual decisions. In fact, a model of a group decision making shows that it can cause underinvestment at firms. The three-or-more requirement was formed with path dependency dating back to the late 19th century when Japan transplanted legal systems from overseas, but it was by no means the standard. Giving managers flexibility in organizational design is desirable in that it can accommodate firms’ internal characteristics and tendencies and facilitate the establishment of start-ups, new subsidiaries and joint ventures.

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The Global Response to COVID-19 as an Example of a One-Sided Problem Definition in the Absence of General Collective Intelligence

10.31234/osf.io/emgxc ◽

2020 ◽

Author(s):

Andy E Williams

Keyword(s):

Decision Making ◽

Mathematical Models ◽

Group Decision Making ◽

Group Decision ◽

Collective Intelligence ◽

Well Being ◽

Problem Definition ◽

Negative Outcomes ◽

Global Response ◽

Risk Of Mortality

Problem definitions are defined here as one-sided in the case that while they might take into account one class of negative outcomes, such as those associated with the problem, at the same time they might ignore other classes of negative outcomes, such as those that may be encountered while implementing interventions that try to avoid the problem. An example is amputating all limbs with potentially cancerous moles on them to reduce the risk of mortality due to cancer as much as possible, without considering the increase in mortality due to the amputations. The global response to COVID-19 has been characterized by the availability of mathematical models for the potential mortality due to the spread of the pandemic. However in some cases the researchers guiding the responses of their respective nations with their mathematical models have explicitly pointed out that corresponding mathematical models of the impacts of economic shutdowns or other potential interventions on mortality have not been incorporated, and that there is a critical need to include such models. This paper generalizes this problem of one-sided problem definitions past the COVID-19 response to a wide variety of group problems where the pattern of one-sidedness applies, and explores how in current group decision-making systems one-sided problem definitions might consistently tend to be exploited in a way that is detrimental to collective well-being, as well as how a system of group decision-making meeting the requirements of a General Collective Intelligence solves the problem of one-sidedness to reliably maximize collective well-being.

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COVID-19 and The Hidden Cost of Reduced Civil Liberties

10.31235/osf.io/scnza ◽

2020 ◽

Author(s):

Andy E Williams

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Collective Intelligence ◽

Civil Liberties ◽

Martial Law ◽

Group Outcomes ◽

Hidden Cost ◽

Decision Making System ◽

The Cost

The ongoing COVID-19 outbreak that emerged from Wuhan, China in 2020 has seen unprecedented restrictions on civilian populations in many countries in the attempt to curtail the spread of the pandemic. A recently developed model of general collective intelligence predicts the properties of group decision-making systems that are required to optimize collective outcomes, along with predicting that authoritarian systems of decision-making might tend to be restricted to non-optimal group outcomes in ways that are somewhat hidden in that they require an understanding of this new and relatively unknown model of general collective intelligence. In light of this model of general collective intelligence, the economic restrictions imposed to combat the pandemic take on a new light, since these restrictions have not only resulted in economic lockdowns for some countries, but in some cases have also effectively imposed martial law. The hidden cost of this reduction in civil liberties is explored from the perspective of the cost of an authoritarian decision-making system resulting in non-optimal group outcomes as theorized by this model of general collective intelligence, using models of government inefficiency to assess the cost of those non-optimal group outcomes, and therefore the hidden cost of reduced civil liberties.

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General Collective Intelligence and the Constraints to Group Decision-Making

10.31234/osf.io/6gtcn ◽

2020 ◽

Author(s):

Andy E Williams

Keyword(s):

Decision Making ◽

Problem Solving ◽

Group Decision Making ◽

General Problem ◽

Group Decision ◽

Collective Intelligence ◽

Academic Disciplines ◽

Group Problem ◽

Group Problem Solving ◽

Decision Systems

This paper addresses the question of how current group decision-making systems, including collective intelligence algorithms, might be constrained in ways that prevent them from achieving general problem solving ability. And as a result of those constraints, how some collective issues that pose existential risks such as poverty, the environmental degradation that has linked to climate change, or other sustainable development goals, might not be reliably solvable with current decision-making systems. This paper then addresses the question that assuming specific categories of such existential problems are not currently solvable with any existing group decision-systems, how can decision-systems increase the general problem solving ability of groups so that such issues can reliably be solved? In particular, how might a General Collective Intelligence, defined here to be a system of group decision-making with general problem solving ability, facilitate this increase in group problem-solving ability? The paper then presents some boundary conditions that a framework for modeling general problem solving in groups suggests must be satisfied by any model of General Collective Intelligence. When generalized to apply to all group decision-making, any such constraints on group intelligence, and any such system of General Collective Intelligence capable of removing those constraints, are then applicable to any process that utilizes group problem solving, from design, to manufacturing or any other life-cycle processes of any product or service, or whether research in any field from the arts to the basic sciences. For this reason these questions are important to a wide variety of academic disciplines. And because many of the issues impacted represent existential risks to human civilization, these questions may also be important by to all by definition.

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The Need for General Collective Intelligence in Addressing the Sustainable Development Goals

10.21203/rs.3.rs-18022/v1 ◽

2020 ◽

Author(s):

Andy E Williams

Keyword(s):

Decision Making ◽

Sustainable Development ◽

Group Decision Making ◽

Sustainable Development Goals ◽

Group Decision ◽

Collective Intelligence ◽

Collective Impact ◽

Optimal Solutions ◽

The Sustainable Development ◽

Development Goals

Abstract Background: This study explores the factors constraining group decision-making, where those factors might tend to restrict groups from selecting optimal solutions with regards to sustainability or sustainable development. This study also explores the factors constraining group decision-making from framing problems in the optimal way (choosing the optimal problem to solve), and how together these factors constraining groups from choosing the optimal problem to solve or the optimal solution to solve it with, might tend to bar groups from achieving optimal outcomes. To address the first set of constraints, collective intelligence algorithms aim to use the intelligence of crowds to select optimal solutions. To address the second set of constraints, General Collective Intelligence solutions, as defined in this paper, aim to further improve outcomes by selecting the optimal problem to solve.Results: In the absence of General Collective Intelligence fundamental economic forces are suggested to drive a continual increase in the alignment of group decision-making with the interests of decision-makers rather than with optimizing collective impact. And while sustainability and sustainable development might be achieved locally in the face of this misalignment, globally this misalignment is suggested to compete directly against that achievement. For this reason, maximizing collective outcomes such as impact on sustainability or sustainable development is suggested to require General Collective Intelligence in order to reliably increase the forces driving groups towards prioritizing collective impact until those forces are greater than the forces driving this misalignment. As a result, without General Collective Intelligence this misalignment of group decision-making in a direction other than optimal collective impact is suggested to be a hidden "bug" that may prevent sustainability and sustainable development from being reliably achievable globally through current sustainability or sustainable development programs.Conclusions: General Collective Intelligence is a pattern of biomimicry that potentially replicates the robust and stable multi-cellular cooperation nature has evolved over more than a billion years to enable cells in organisms to cooperate to sustainably achieve outcomes. Platforms organizing groups into such a General Collective Intelligence are suggested to be required in order for sustainability or the sustainable development goals to be reliably achievable globally.

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Transforming Economies and Generating Sustainable “Green” Economic Growth After the COVID-19 Pandemic through General Collective Intelligence

10.31235/osf.io/arw7c ◽

2020 ◽

Author(s):

Andy E Williams

Keyword(s):

Economic Growth ◽

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Collective Intelligence ◽

Well Being ◽

Decision Systems ◽

The Great Depression ◽

Recent Innovation ◽

Human Decision

The lockdown of economic activity in many countries as a measure to stop the spread of the COVID-19 pandemic has led to high levels of unemployment and other indicators of a potentially upcoming economic crisis. As a gauge of the seriousness of these concerns some have suggested that current levels of some of these indicators have not been seen in the US since the time of the great depression. This paper explores how General Collective Intelligence, a recent innovation in group decision-making systems, might reliably generate the economic growth needed to avert such a crisis where not reliably achievable otherwise. Current group decision-making systems, whether choosing a human decision-maker, consensus voting on decisions, or automated decision-systems such as conventional collective intelligence, have been suggested to lack the capacity to maximize more than a very few group outcomes simultaneously due to specific limitations. Since impact on collective well-being is determined by impact on an open (unbounded) set of outcomes, this implies lack of the capacity to maximize the necessary range of impacts on well-being for groups if that range is too broad. If so, the breadth of impact required to achieve sustainable “green” economic development while simultaneously solving hunger, solving the environmental degradation that consensus has linked to climate change, as well as providing maximal access to healthcare, education, and other resources, may not be reliably possible with current decision systems. General Collective Intelligence or GCI replicates the adaptive problem solving mechanisms by which nature has demonstrated the ability to optimally respond to an unlimited set of problems, and by which nature has demonstrated the ability to potentially increase sustainability per unit of resources by orders of magnitude so that life is reliably self-sustaining. This paper explores why GCI can potentially be used to reliably drive self-sustaining economic growth to revive economies in the aftermath of the COVID-19 pandemic, and why GCI has the potential to reliably drive a transformation to sustainable green economies while doing so.

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Applying Visualization and Collective Intelligence for Rapid Group Decision Making

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1541931218621039 ◽

2018 ◽

Vol 62 (1) ◽

pp. 167-171 ◽

Cited By ~ 2

Author(s):

Stephen Dorton ◽

Chris M. Smith ◽

Jason B. Upham

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Group Decision ◽

Collective Intelligence ◽

Lessons Learned ◽

Informed Decision Making ◽

Subjective Data ◽

Group Methods ◽

Collective Group ◽

Future Work

There is a need to rapidly collect subjective data from a diverse group of contributors to facilitate argumentation and group decision making that reflects the breadth and depth of the knowledge of the collective group. Methods currently exist, although they are subject to biases and lack traceability. A method and tool have been developed to apply collective intelligence and visualization concepts to enable such rapid decision making while overcoming the identified weaknesses. A pilot study to select the best technology to solve a Naval mission requirement was performed to assess the ability of the tool to: Enable informed decision making, assess differences in contributor mental models, and identify where there is or is not consensus. The method/tool was useful to these ends, warranting further research. Lessons learned were gathered and the validity of the approach was notionally examined, driving the identification of future work to be performed.

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