Artificial General Intelligence

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.

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Artificial General Intelligence: A New Perspective, with Application to Scientific Discovery

10.31224/osf.io/duz8g ◽

2019 ◽

Author(s):

A. M. Khalili

Keyword(s):

Problem Solving ◽

Scientific Discovery ◽

General Intelligence ◽

Discovery Process ◽

Artificial General Intelligence ◽

Alternative Perspective ◽

New Knowledge ◽

New Perspective ◽

High Level ◽

Open The Doors

The dream of building machines that have human-level intelligence has inspired scientists for decades. Remarkable advances have been made recently; however, we are still far from achieving this goal. In this paper, I propose an alternative perspective on how these machines might be built focusing on the scientific discovery process which represents one of our highest abilities that requires a high level of reasoning and remarkable problem-solving ability. By trying to replicate the procedures followed by many scientists, the basic idea of the proposed approach is to use a set of principles to solve problems and discover new knowledge. These principles are extracted from different historical examples of scientific discoveries. Building machines that fully incorporate these principles in an automated way might open the doors for many advancements.

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