The inherent goodness of well educated intelligence (2401.04846v9)

Abstract: This paper will examine what makes a being intelligent, whether that be a biological being or an artificial silicon being on a computer. Special attention will be paid to the being having the ability to characterize and control a collective system of many identical conservative sub-systems conservatively interacting. The essence of intelligence will be found to be the golden rule -- "the collective acts as one" or "knowing the global consequences of local actions". The flow of the collective is a small set of twinkling textures, that are governed by a puppeteer who is pulling a small number of strings according to a geodesic motion of least action, determined by the symmetries. Controlling collective conservative systems is difficult and has historically been done by adding significant viscosity to the system to stabilize the desirable meta stable equilibriums of maximum performance, but it degrades or destroys them in the process. There is an alternative. Once the optimum twinkling textures of the meta stable equilibriums are identified, the collective system can be moved to the optimum twinkling textures, then quickly vibrated according to the textures so that the collective system remains at the meta stable equilibrium. Well educated intelligence knows the global consequences of its local actions so that it will not take short term actions that will lead to poor long term outcomes. In contrast, trained intelligence or trained stupidity will optimize its short term actions, leading to poor long term outcomes. Well educated intelligence is inherently good, but trained stupidity is inherently evil and should be feared. Particular attention is paid to the control and optimization of economic and social collectives. These new results are also applicable to physical collectives such as fields, fluids and plasmas.

• The paper identifies the 'Golden Rule' of collective intelligence, emphasizing that well-educated intelligence delivers long-term benefits over short-term optimization.
• It uses physics-based frameworks, including the Hamilton-Jacobi-Bellman equation and Heisenberg Scattering Transformation, to decode complex metastable equilibriums called 'twinkling textures'.
• The study critiques conventional control methods, like debt-induced viscosity, and advocates for sustainable, ethically driven strategies in managing collective systems.

An Analysis of "The Inherent Goodness of Well Educated Intelligence"

The paper, "The Inherent Goodness of Well Educated Intelligence," by Michael E. Glinsky and Sharon Sievert, explores the nature and operational principles of intelligence, applying their insights to both biological and artificial systems. The authors address the challenges and methodologies associated with controlling collective systems, particularly those comprised of interacting subsystems with conservative behaviors.

Overview and Methodology

The core proposition of the paper is the identification of the "Golden Rule" as fundamental to intelligence, summarized as "the collective acts as one" or "knowing the global consequences of local actions." The authors assert that intelligence, whether biological or artificial, is inherently beneficial when it is well-educated, in contrast to "trained stupidity," which focuses on short-term optimization to the detriment of long-term outcomes.

The paper details how collective systems, from economic to physical systems like fluids and plasmas, can achieve optimal performance by identifying and manipulating their metastable equilibriums, termed "twinkling textures." These textures, produced by the naturally conserved motion within the system, can be controlled through informed actions rather than destabilizing interventions like economic viscosity.

Significant Contributions

The research emphasizes the detrimental impact of conventional control approaches that introduce significant viscosity, such as debt-based economic models. These methods lead to reduced system performance and potential collapse. The authors propose an alternative in which systems are characterized and controlled through intelligent understanding and manipulation of the "twinkling textures."

The paper contributes to theoretical insights by leveraging concepts from physics and artificial intelligence, such as the Hamilton-Jacobi-BeLLMan (HJB) equation and Heisenberg Scattering Transformation (HST). These mathematical frameworks aid in deconvolving complex systems to their fundamental states and control variables, enhancing understanding and management of diverse collective systems.

Implications and Future Work

From a theoretical standpoint, this research underscores the necessity of incorporating holistic analytics to understand complex systems' underlying dynamics. Practically, the findings are profound for economic and social systems, indicating pathways to manipulate large-scale systems' states for optimal outcomes.

The authors hint at future developments in AI by suggesting that true artificial intelligence, characterized by its understanding of global consequences of local actions, can achieve substantial control over collective systems. Such systems can apply transactional equity and AI techniques, such as Generative Adversarial Networks (GANs) and Generative Pretrained Transformers (GPTs), to achieve an ideal socio-economic state.

Conclusion

This research highlights the potential for aligning intelligent systems with optimal control principles derived from a comprehensive understanding of complex system dynamics. Beyond existing economic, social, and physical paradigms, the paper suggests a shift towards more adaptive, responsive systems governed by well-educated intelligence, offering promising prospects for future AI advancements and sustainable management of collective systems.

While innovative in its approach, this publication also emphasizes the importance of ethical considerations and the intrinsic value of well-educated intelligence as a guiding principle for future developments across various fields.