Human Brain Computer/Machine Interface System Feasibility Study for Independent Core Observer Model Based Artificial General Intelligence Collective Intelligence Systems

2019 ◽  
pp. 193-201
Author(s):  
David J. Kelley ◽  
Kyrtin Atreides
Keyword(s):  
Human Brain ◽  
Feasibility Study ◽  
Collective Intelligence ◽  
General Intelligence ◽  
Artificial General Intelligence ◽  
Model Based ◽  
Interface System ◽  
Machine Interface ◽  
Observer Model

scholarly journals Individualization of Products and Services with Artificial General Intelligence and General Collective Intelligence

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Online Education ◽  
News Media ◽  
Intelligent Agents ◽  
Collective Intelligence ◽  
Online News ◽  
General Intelligence ◽  
Entertainment Media ◽  
Individual User ◽  
Artificial General Intelligence ◽  
The Individual

INTRODUCTION: With advances in big data techniques having already led to search results and advertising being customized to the individual user, the concept of an online education designed solely for an individual, or the concept of online news or entertainment media, or any other virtual service being designed uniquely for each individual, no longer seems as far fetched. However, designing services that maximize user outcomes as opposed to services that maximize outcomes for the corporation owning them, requires modeling user processes and the outcomes they target.OBJECTIVES: To explore the use of Human-Centric Functional Modeling (HCFM) to define functional state spaces within which human processes are well-defined paths, and within which products and services solve specific navigation problems, so that by considering all of any given individual’s desired paths through a given state space, it is possible to automate the customization of those products and services for that individual or to groups of individuals.METHODS: An analysis is performed to assess how and whether intelligent agents based on some subset of functionality required for Artificial General Intelligence (AGI) might be used to optimize for the individual user. And an analysis is performed to determine whether and if so how General Collective Intelligence (GCI) might be used to optimize across all users.RESULTS: AGI and GCI create the possibility to individualize products and services, even shared services such as the Internet, or news services so that every individual sees a different version.CONCLUSION: The conceptual example of customizing a news media website for two individual users of opposite political persuasions suggests that while the overhead of customizing such services might potentially result in massively increased storage and processing overhead, within a network of cooperating services in which this customization reliably creates value, this is potentially a significant opportunity.

scholarly journals AI Safety and General Collective Intelligence

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Collective Intelligence ◽  
The Other ◽  
General Intelligence ◽  
Human Beings ◽  
Artificial General Intelligence ◽  
The Future ◽  
Ai Safety

Considering both current narrow AI, and any Artificial General Intelligence (AGI) that might be implemented in the future, there are two categories of ways such systems might be made safe for the human beings that interact with them. One category consists of mechanisms that are internal to the system, and the other category consists of mechanisms that are external to the system. In either case, the complexity of the behaviours that such systems might be capable of can rise to the point at which such measures cannot be reliably implemented. However, General Collective Intelligence or GCI can exponentially increase the general problem-solving ability of groups, and therefore their ability to manage complexity. This paper explores the specific cases in which AI or AGI safety cannot be reliably assured without GCI.

scholarly journals Estimation of Viewpoint Direction and Viewing Angle Using EOG

2019 ◽  
Keyword(s):  
Eye Movements ◽  
Linear Relationship ◽  
Feasibility Study ◽  
Input Signal ◽  
Viewing Angle ◽  
Machine System ◽  
Interface System ◽  
Machine Interface ◽  
The Relationship ◽  
High Possibility

This paper presents the feasibility study of EOG signal for the input signal of the man-machine system. This research focuses on the relationship between the eye movements and EOG signal. When the trial subjects look right, left, up and down, the EOG signal was measured and compared with the eye movements and later analyzed. We found that there was a linear relationship between the eye movements and EOG signal. The presented method demonstrates the high possibility of using EOG signal for the man-machine interface system.

scholarly journals Does Creating an Artificial General Intelligence Require General Collective Intelligence in Order to be Reliably Achievable?

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Cognitive Functions ◽  
Collective Intelligence ◽  
Functional Model ◽  
General Intelligence ◽  
Artificial General Intelligence ◽  
Exponential Increase ◽  
Group A ◽  
Complete Set

General Collective Intelligence or GCI has been predicted to create the potential for an exponential increase in the problem-solving capacity of the group, as compared to the problem-solving capacity of any individual in the group. A functional model of cognition proposed to represent the complete set of human cognitive functions, and therefore to have the capacity for human-like general problem-solving ability has recently been developed. This functional model suggests a methodical path by which implementing a working Artificial General Intelligence (AGI) or a working General Collective Intelligence might reliably be achievable. This paper explores the claim that there are no other reliable paths to AGI currently known, and explores why this one known path might require an exponential increase in the general problem-solving ability of any group of individuals to be reliably implementable. And why therefore, AGI might require GCI to be reliably achievable.

scholarly journals Using Systems Thinking to Exponentially Increase Impact

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Climate Change ◽  
Problem Solving ◽  
Systems Thinking ◽  
General Problem ◽  
Collective Intelligence ◽  
General Intelligence ◽  
Functional Modeling ◽  
Artificial General Intelligence ◽  
Exponential Increase

This paper explores how Human-Centric Functional Modeling might provide a method of systems thinking that in combination with models of Artificial General Intelligence and General Collective Intelligence developed using the approach, creates the opportunity to exponentially increase impact on targeted outcomes of collective activities, including research in a wide variety of disciplines as well as activities involved in addressing the various existential challenges facing mankind. Whether exponentially increasing the speed and scale of progress in research disciplines such as physics or medicine, or whether exponentially increasing capacity to solve existential challenges such as poverty or climate change, this paper explores why gaining the capacity to reliably solve such challenges might require this exponential increase in general problem-solving ability, why this exponential increase in ability might be reliably achievable through this approach, and why solving our most existential challenges might be reliably unachievable otherwise.

scholarly journals The Case for General Collective Intelligence Rather than Artificial General Intelligence being the Most Important Human Innovation in the History and Future of Mankind

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Economic Impact ◽  
Collective Intelligence ◽  
Human Intelligence ◽  
General Intelligence ◽  
Human Beings ◽  
Artificial General Intelligence ◽  
Proposed Model ◽  
History Of ◽  
Hidden Patterns ◽  
Entire Planet

Artificial General Intelligence, that is an Artificial Intelligence with the ability to redesign itself and other technology on its own, has been called “mankind’s last invention”, since it may not only remove the necessity of any human invention afterwards, but also might design solutions far too complex for human beings to have the ability to contribute to in any case. Because of this, if and when AGI is ever invented, it has been argued by many that it will be the most important innovation in the history of the mankind up to that point. Just as nature’s invention of human intelligence might have transformed the entire planet and generated a greater economic impact than any other innovation in the history of the planet, AGI has been suggested to have the potential for an economic impact larger than that resulting from any other innovation in the history of mankind. This paper explores the case for General Collective Intelligence being a far more important innovation than AGI. General Collective Intelligence has been defined as a solution with the capacity to organize groups of human or artificial intelligences into a single collective intelligence with vastly greater general problem solving ability. A recently proposed model of GCI not only outlines a model for cognition that might also enable AGI, but also identifies hidden patterns in collective outcomes for groups that might make GCI necessary in order to reliably achieve the benefits of AGI while reliably avoiding the potentially catastrophic costs of AGI.

scholarly journals Approximating an Artificial General Intelligence or a General Collective Intelligence

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
Complex Systems ◽  
General Problem ◽  
Collective Intelligence ◽  
Complex Problem ◽  
General Intelligence ◽  
Functional Modeling ◽  
Artificial General Intelligence ◽  
Over Time

Human-Centric Functional Modeling (HCFM) has recently been used to define a model of Artificial General Intelligence (AGI) believed to have the capacity for human-like general problem-solving ability (intelligence), as well as a model of General Collective Intelligence (GCI) with the potential to combine individuals into a single collective intelligence that might have exponentially greater general problem-solving ability than any individual in the group. Functional modeling decouples the components of complex systems like cognition through well-defined interfaces so that they can be implemented separately, thereby breaking down the complex problem of implementing such a system into a number of much simpler problems. This paper explores how a rudimentary AGI and a rudimentary GCI might be implemented through approximating the functions of each, in order to create systems that provide sufficient value to incentivize more sophisticated implementations to be developed over time.

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