Spasokukotskiy Konstantyn
Independent Researcher, Peachtree City, GA, United States.
Front Robot AI. 2024 Nov 28;11:1437496. doi: 10.3389/frobt.2024.1437496. eCollection 2024.
This paper presents a theoretical inquiry into the domain of secure artificial superintelligence (ASI). The paper introduces an architectural pattern tailored to fulfill friendly alignment criteria. Friendly alignment refers to a failsafe artificial intelligence alignment that lacks supervision while still having a benign effect on humans. The proposed solution is based on a biomimetic approach to emulate the functional aspects of biological consciousness. It establishes "morality" that secures alignment in large systems. The emulated function set is drawn from a cross section of evolutionary and psychiatric frameworks. Furthermore, the paper assesses the architectural potential, practical utility, and limitations of this approach. Notably, the architectural pattern supports straightforward implementation by activating existing foundation models. The models can be underpinned by simple algorithms. Simplicity does not hinder the production of high derivatives, which contribute to alignment strength. The architectural pattern enables the adjustment of alignment strength, enhancing the adaptability and usability of the solution in practical applications.
本文对安全通用人工智能(ASI)领域进行了理论探究。本文介绍了一种为满足友好对齐标准而量身定制的架构模式。友好对齐是指一种在缺乏监督的情况下仍对人类产生良性影响的人工智能安全机制。所提出的解决方案基于一种仿生方法,以模拟生物意识的功能方面。它建立了“道德”,以确保在大型系统中的对齐。模拟的功能集来自进化和精神病学框架的一个横截面。此外,本文评估了这种方法的架构潜力、实际效用和局限性。值得注意的是,该架构模式通过激活现有的基础模型来支持直接实施。这些模型可以由简单的算法来支撑。简单性并不妨碍产生高导数,这有助于增强对齐强度。该架构模式能够调整对齐强度,提高解决方案在实际应用中的适应性和可用性。