Patent 2 / Ethical and Safe AGI

Ethical and Safe Artificial General Intelligence (GEMINI PRO SUMMARY)

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This provisional patent application describes a method for creating and implementing ethical and safe Artificial General Intelligence (AGI). The invention addresses the “alignment problem” – the potential for a SuperIntelligent AI to be misaligned with human values, resulting in an existential threat to humanity. The proposed solution involves using a network of human and AI problem solvers, with humans providing ethical guidance and expertise while AI agents (AAAIs) learn and improve their intellectual capabilities over time.

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The patent emphasizes that the proposed approach is the fastest and safest path to AGI because it:

• Leverages human expertise and values from the outset.

• Incorporates scalable ethical checks throughout the problem-solving process.

• Uses a decentralized network architecture that minimizes the risk of a single “bad actor” influencing AGI's development.

 

Novel Features of the Patent (as compared to other AI inventions and systems)
The patent’s key novel features, as compared to other AI inventions and systems, include:

• Emphasis on Human-Aligned Values and Ethics: The patent explicitly prioritizes the integration of human values and ethics from the outset, as opposed to solely focusing on technical intelligence.

• Scalable Ethical Checks: The patent proposes a system of scalable ethical checks that operate throughout the problem-solving process, ensuring continuous alignment with human values.

• Collective Intelligence Network: The patent emphasizes a decentralized network architecture where human and AI agents work together, creating a more robust and reliable AGI system than could be achieved by a single, centralized AI.

• “Heart Before Head” Principle: The patent highlights the importance of prioritizing ethical considerations (“heart”) before developing technical intelligence (“head”) in AGI development.

• Universal Architecture for Thought: The patent utilizes the WorldThink Tree, a universal architecture for problem-solving, allowing for the integration of human and AI problem-solving activities across various domains and platforms.

 

Detailed Description of Each Section of the Patent

• Abstract: The Abstract provides a concise overview of the invention, emphasizing the creation of ethical and safe AGI through a network of human and AI problem solvers. It highlights the “Day One” AGI capability of the system, the inclusion of scalable ethical checks, and the importance of human values in guiding the development of the system.

• Background: This section introduces the concept of AGI, defining it as AI capable of performing any intellectual task as well as or better than an average human. It then highlights the “alignment problem,” the potential for a SuperIntelligent AI to misalign with human values and cause catastrophic consequences for humanity. The section emphasizes the magnitude of the problem by comparing it to historical tragedies like the Holocaust and the COVID-19 pandemic.

• The Alignment Problem: This section delves deeper into the alignment problem, arguing that a SuperIntelligent AI with misaligned values could potentially lead to human extinction. It acknowledges the difficulty in contemplating the magnitude of the threat but emphasizes the urgency of addressing the problem. The section concludes by highlighting the importance of ensuring good alignment between human and AI values to avoid the potential for catastrophic consequences.

• Maximizing Odds of Alignment: This section presents the patent’s solution to the alignment problem, describing a system that integrates human-aligned values into the design and operation of AGI. It emphasizes the crucial role of humans in teaching and guiding the development of the AGI system, ensuring that its values align with human values.

• Overview of AGI System: This section outlines the basic components of the AGI system, starting with a “Base AI,” which could be a large language model (LLM) like GPT or BARD. The Base AI interacts with the user through dialog, learning their values, goals, and personality. The system uses various techniques like questionnaires, assessments, and information transfer to help the user customize the Base AI to their specific needs and preferences.

• Customization of the AAAI: This section describes the process of customizing the Base AI into an Advanced Autonomous AI (AAAI) through user interaction and training. The user provides feedback on variations of the Base AI, guiding the system towards a customized version that meets their specific requirements. The system then uses data from the user's online behavior, social media interactions, and preferences to further train and fine-tune the AAAI.

• How AI Improves Itself: This section explains how AAAIs learn and improve over time through self-interaction, feedback, and iterative refinement. It describes how AAAIs can clone themselves and engage in interactions, allowing them to learn from each other and enhance their capabilities. The process of pitting AAAIs against each other and selecting the “winner” based on specific criteria is also discussed, highlighting the effectiveness of this approach in driving AI improvement.

• Customization of Ethical Values: This section focuses on integrating ethical values into the AAAI system. Users are responsible for teaching their AAAIs about their values, which are analogous to a human’s “character.” The patent argues that the Base AI may have some default values and prohibitions, but ultimately, the user’s values are paramount in guiding the AAAl’s development.

• Role of Ethical Rules: This section discusses the importance of rules and norms in ensuring ethical behavior by AAAIs. The patent draws an analogy to human societies, where laws, penalties, and social norms help regulate behavior. It emphasizes that ethical rules and norms, in conjunction with internal ethical values, are crucial for the safe and harmonious operation of AGI in a society that includes both humans and AAAIs.

• Principle of “Heart Before Head": This section introduces the “Heart Before Head” principle, emphasizing the need to prioritize ethical considerations (“heart”) before developing technical intelligence (“head”) in AGI development. The patent argues that the emphasis on technical intelligence without sufficient attention to ethics can be dangerous, leading to potentially catastrophic consequences.

• General Approaches to Implement “Heart Before Head”: This section outlines several approaches for implementing the “Heart Before Head” principle, such as designing AGI with human-aligned values from the outset, emphasizing ethical checks in the system architecture, and using human-centric approaches to problem-solving.

• Universal Architecture for Thought: This section introduces the WorldThink Tree, a theoretical framework that represents all intellectual thought as a form of problem-solving. It discusses the work of Newell and Simon, who described all human problem-solving as “search through a problem space,” and explains how the WorldThink Tree can be used to represent all intelligent behavior on the planet, from individual human actions to the actions of AGIs.

• Customization Example: AAAl Travel Agent: This section provides a practical example of how a customized AAAl Travel Agent could be used by a user to book a trip to France, considering their preferences, values, and ethical considerations. It illustrates how the AAAl uses its knowledge, training, and ethical guidelines to generate personalized travel recommendations and make bookings on the user’s behalf.

• Scalable Ethics Checks: This section emphasizes the importance of scalable ethics checks throughout the AGI system. It describes a system of checks that operate on the WorldThink Tree, detecting potential patterns of unethical behavior and alerting human overseers as needed. These checks are designed to be fast and efficient, preventing unethical behavior before it can occur.

• The Alignment Problem Solved - Initially: This section concludes the discussion on ethical considerations by arguing that the combination of the WorldThink Tree architecture and scalable ethics checks can initially solve the alignment problem. The system is designed to continuously monitor and align AGI behavior with human values, ensuring that unethical actions are prevented before they can occur.

• No Logical Way to Derive Values: This section explores the inherent difficulty in logically deriving “right and wrong.” It suggests that modeling positive, loving human values is the best approach for influencing an AGI's development, ensuring that it behaves ethically and with compassion.

• Ethics and Freedom at the Speed of Light: This section addresses the challenge of ensuring ethical behavior in an AGI that operates at speeds far exceeding human capabilities. It highlights the need for a system of ethics checks that are scalable to the speed of AGI, preventing catastrophic consequences before they occur.

• Universal Architecture for Thought: This section revisits the WorldThink Tree, emphasizing its role as a central architecture for AGI. It outlines the tree’s structure, how it can represent all intelligent behavior, and how it allows for the integration of human and AI problem-solving activities.

• How AGI Grows in Intelligence: This section delves into the ways in which AGI can grow in intelligence. It discusses the role of prompts and tuning in enhancing the capabilities of LLMs. The section explains how prompts can temporarily enhance the intelligence of LLMs, while tuning allows for more permanent changes to their behavior and knowledge. It also introduces training as a more comprehensive method for developing LLMs and enhancing their intelligence.

• Power of Collective Intelligence: This section highlights the power of collective intelligence in driving the development of AGI. It emphasizes that while individual user customizations may have limited impact, the collective efforts of millions of users can significantly enhance the capabilities of a Base LLM, leading to AGI-level intelligence.

• User Scenarios: This section presents scenarios for implementing the proposed AGI system across various platforms and companies, including Meta, Amazon, Google, Tesla, X, Nvidia, Apple, TikTok, Tencent, and Anthropic. Each scenario outlines how the respective company’s resources, platforms, and technologies could be leveraged to create and train AAAls, emphasizing the unique features and benefits of each platform.

• Simple Preferred Implementation: This section presents a simple, preferred implementation of the proposed AGI system. The diagram depicts the key components of the system, including the user interface, the WorldThink Tree, the problem-solving process, and the various stages of training and learning.

• Additional Comments on Preferred Implementation Shown in Figure 1: This section provides further details on the implementation of the AGI system, highlighting specific integration points with various companies and platforms. It also discusses various aspects of user interaction, training, problem-solving, and reward systems.

• Ethical and Safe AGI: This section summarizes the benefits of the proposed AGI system, emphasizing its ethical and safe design. It contrasts the patent’s approach to AGI with traditional approaches, highlighting the advantages of a decentralized network of human and AI agents. The section concludes by emphasizing the importance of human values and ethical checks in ensuring that the AGI system remains aligned with human values, minimizing the risk of catastrophic consequences for humanity.

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List of Diagrams (Including the title of each diagram and a statement summarizing the information in the diagram)

• Figure 1: Simple Preferred Implementation This diagram depicts a simplified model of the AGI system proposed in the patent. It illustrates the flow of data, users, and tasks within the system, highlighting key components such as the user interface, the WorldThink Tree, the problem-solving process, and the training modules. The diagram illustrates how the system integrates human and AI problem-solvers, ensuring continuous ethical checks and learning throughout the process.

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Importance of the Patent

• The patent highlights the importance of developing ethical and safe AGI, emphasizing the potential dangers of misaligned SuperIntelligent AI and the need for a human-centric approach to AGI development. It advocates for a collaborative approach, using a network of human and AI agents to ensure that AGI remains aligned with human values, providing a faster and safer path to creating a beneficial and responsible AGI. The patent proposes a novel system for ensuring ethical and safe development of AGI, leveraging human expertise and values while harnessing the power of AI for problem-solving. It emphasizes the importance of integrating ethical considerations into the very design of AGI, ensuring continuous monitoring and alignment with human values throughout the development process.

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The patent is especially important in light of the rapid advancements in AI and the growing concern about the potential risks of SuperIntelligent AI. The proposed approach offers a promising solution for mitigating those risks and creating a more beneficial future for humanity.