2024年驾驭人工智能前沿_人工智能代理（AI+Agent）的演进和影响白皮书（英文版）_28页_3mb

This white paper examines AI agents, defined as autonomous systems that sense and act on their environment to achieve goals. It traces their evolution from simple rule-based systems to advanced models using machine learning, deep learning, and large language/multimodal models, capable of complex decision-making and collaboration in multi-agent systems. Various types of AI agents are discussed, including simple reflex, model-based reflex, goal-based, and utility-based agents, each with specific applications. Benefits include productivity gains, specialized support, and efficiency improvements in sectors like healthcare, finance, and education. However, risks such as ethical concerns, safety issues, and socioeconomic impacts, including potential misalignment and malicious use, are highlighted. Addressing these challenges requires governance frameworks, transparency measures, and ethical guidelines to ensure responsible development and deployment. The paper concludes that AI agents have transformative potential but demands careful management to mitigate risks and foster positive societal impact.