The Road to Artificial SuperIntelligence: A Comprehensive Survey of Superalignment

2024-12-21

AI Summary

This paper addresses the alignment challenge in the era of Artificial Superintelligence (ASI), focusing on the core problem of achieving scalable supervision and robust governance of human values at superintelligent scales. Methodologically, it introduces the first theoretical framework for “superalignment,” grounded in two pillars—scalable supervision and robust governance—and systematically integrates state-of-the-art approaches including process-based oversight, interpretability modeling, verification of recursive self-improvement, and AI-assisted alignment evaluation. It critically analyzes limitations of existing alignment paradigms, proposes the first taxonomy of superalignment methods, identifies key bottlenecks—such as value generalization failure and supervisory signal decay—and outlines a systematic pathway for ASI’s sustained safe evolution. The work establishes foundational theoretical grounding and strategic direction for ASI safety research.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Learning Human Values and Preferences
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation

Abstract

The emergence of large language models (LLMs) has sparked the possibility of about Artificial Superintelligence (ASI), a hypothetical AI system surpassing human intelligence. However, existing alignment paradigms struggle to guide such advanced AI systems. Superalignment, the alignment of AI systems with human values and safety requirements at superhuman levels of capability aims to addresses two primary goals -- scalability in supervision to provide high-quality guidance signals and robust governance to ensure alignment with human values. In this survey, we examine scalable oversight methods and potential solutions for superalignment. Specifically, we explore the concept of ASI, the challenges it poses, and the limitations of current alignment paradigms in addressing the superalignment problem. Then we review scalable oversight methods for superalignment. Finally, we discuss the key challenges and propose pathways for the safe and continual improvement of ASI systems. By comprehensively reviewing the current literature, our goal is provide a systematical introduction of existing methods, analyze their strengths and limitations, and discuss potential future directions.

Problem

• Artificial Superintelligence
• Value Alignment
• Ethical Oversight

Innovation

• Super Alignment
• Artificial Superintelligence Supervision
• Human Value Alignment