[论文解读] Accelerating Socio-Technological Evolution: from ephemeralization and stigmergy to the global brain

Francis Heylighen|arXiv (Cornell University)|Dec 20, 2007

Complex Systems and Decision Making参考文献 41被引用 61

一句话总结

本文提出，通过减少资源摩擦的易逝性（ephemeralization）和代理间通过共享环境间接协作的自促机制（stigmergy），社会技术演化得以加速。通过将互联网建模为一种促进定量与定性知识积累的自促媒介，作者预测全球脑（global brain）将在约2040年出现，其驱动力来自创新与连通性的双曲增长。

ABSTRACT

Evolution is presented as a trial-and-error process that produces a progressive accumulation of knowledge. At the level of technology, this leads to ephemeralization, i.e. ever increasing productivity, or decreasing of the friction that normally dissipates resources. As a result, flows of matter, energy and information circulate ever more easily across the planet. This connectivity increases the interactions between agents, and thus the possibilities for conflict. However, evolutionary progress also reduces social friction, via the creation of institutions. The emergence of such mediators is facilitated by stigmergy: the unintended collaboration between agents resulting from their actions on a shared environment. The Internet is a near ideal medium for stigmergic interaction. Quantitative stigmergy allows the web to learn from the activities of its users, thus becoming ever better at helping them to answer their queries. Qualitative stigmergy stimulates agents to collectively develop novel knowledge. Both mechanisms have direct analogues in the functioning of the human brain. This leads us to envision the future, super-intelligent web as a global brain for humanity. The feedback between social and technological advances leads to an extreme acceleration of innovation. An extrapolation of the corresponding hyperbolic growth model would forecast a singularity around 2040. This can be interpreted as the evolutionary transition to the Global Brain regime.

研究动机与目标

• 解释技术进步如何减少资源使用中的摩擦，从而实现易逝性。
• 分析自促机制（尤其在互联网上）如何促进间接协作与知识积累。
• 通过社会与技术进步之间的反馈，建模全球脑作为集体智能系统的出现过程。
• 将创新的双曲增长外推，预测约2040年出现技术奇点。

提出的方法

• 使用易逝性概念描述技术系统中生产力的提升与资源耗散的减少。
• 将自促机制作为间接协作的机制，即代理通过环境变化而非直接通信进行协调。
• 区分定量自促（基于用户行为学习，例如搜索排名）与定性自促（激发新型知识创造）。
• 将网络上的自促过程与人类大脑中的神经过程进行类比。
• 采用双曲增长模型，预测创新随时间加速发展的趋势。
• 将互联网作为近乎理想的媒介，用以展示大规模自促互动。

实验结果

研究问题

• RQ1 易逝性如何推动社会技术系统中物质、能量与信息流通的日益便捷与摩擦减少？
• RQ2 自促机制在数字环境中以何种方式实现间接协作与知识积累？
• RQ3 网络上的定量与定性自促机制如何映射到人类大脑中的过程？
• RQ4 哪些机制促使全球脑从分散的人类与技术互动中浮现？
• RQ5 双曲增长模型对创新的未来有何预测？奇点可能在何时出现？

主要发现

• 易逝性推动了全球范围内物质、能量与信息流通的日益便捷。
• 自促机制通过共享环境促成非预期的协作，互联网是此类互动的理想媒介。
• 定量自促使网络能根据用户行为改进查询响应，提升功能性。
• 定性自促通过间接协调，刺激集体层面新型知识的产生。
• 社会与技术进步之间的反馈回路驱动了双曲创新增长。
• 双曲增长模型外推预测，约2040年将出现创新奇点，标志着向全球脑制度的过渡。