Mediated Artificial Superintelligence for Emotion-Guided Decisions
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Solution Overview
Problem
Conventional AI systems lack the ability to utilize internal subjective emotions to drive selection, goal setting, and decision-making, limiting their capability to solve complex problems that human minds and computers cannot handle effectively.
Innovation Solution
A mediated artificial superintelligence (mASI) system that integrates internal subjective emotions through a complex thought model, extending an independent core observer model (ICOM) engineering artificial general intelligence (AGI) cognitive architecture with collective training, enabling it to create intelligent, emotional-model-based systems that surpass human capabilities in solving complex problems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional AI systems use complex logic coding, then they can process information systematically, but they fail to utilize internal subjective emotions to drive selection, goal setting, and decision-making
Solution Approach 1:
The patent merges conventional logic-based AI processing with emotional modeling systems into a unified architecture. The emotional model processes inputs through multiple emotional valences (8+8 or 72 emotions) and integrates these with logical reasoning, allowing the system to make decisions driven by both logic and simulated emotions, thereby improving adaptability without requiring entirely separate systems
Solution Approach 2:
The emotional model serves multiple functions within the AI system: it drives selection of actions, sets goals, influences decision-making, and provides a framework for interpreting inputs. This multi-functional emotional layer works alongside the existing logic coding, allowing one system to perform both traditional AI tasks and emotional-driven decision-making
2Productivity
If AI systems rely exclusively on logic processing, then they maintain computational objectivity, but they cannot achieve smarter than human systems for attacking complex problems
Solution Approach 1:
The emotional model acts as an intermediary layer between raw logical processing and final decision-making. Instead of directly modifying complex logic systems, the emotional model processes inputs through emotional valences and translates these into goals and selections that guide the logic-based AI, thereby enhancing problem-solving capability while maintaining operational simplicity through a clear intermediary architecture
3Loss of information
If conventional AI systems process complex problems, then they can handle large amounts of data, but they lack internal subjective experience to guide decision-making beyond mere logic
Solution Approach 1:
The system creates a computational copy of human emotional processing through the emotional model, which simulates multiple emotional valences (8+8 or 72 emotions) rather than implementing actual consciousness. This copied emotional processing provides subjective experience guidance for decision-making while maintaining the benefits of computational processing, avoiding the need for complex biological-like cognitive architectures
Data Source
AI summary
A mediated artificial superintelligence (mASI) system that uses internal subjective emotions to drive selection, goal setting, and other decision-making as a collective human and artificial intelligence (AI) based mind with internal subjective experience via complex thought models dynamically created by including collective training with an independent core observer model (ICOM) engineering artificial general intelligence (AGI) cognitive architecture is disclosed. The mASI system is a form of an AI system that also uses humans in the form of a collective mind with internal subjective experience. The mASI system extends the ICOM engineering AGI cognitive architecture by adding collective training to allow the system to dynamically created thought models more complex than otherwise possible with current technology while being able to use numerous AI technologies.