EAGER: Understanding Technological Change from the Map of Capabilities

技术进步是经济增长和发展的核心。此外，解决地球上许多最紧迫的挑战——经济复苏、减贫、气候变化、可持续发展——需要大量增加社会的技术工具包。然而，我们定量建模和预测技术变革的能力是不够的。在经济学和管理学中，关于技术变革的最常见观点——认为它是对技术可能性空间的探索——更多的是一种隐喻，而不是一个建模框架。对特定创新的大量案例研究并不能形成一个正式的、定量的和可预测的理论。该项目开发了一种正式的方法，通过对跨越220年的美国专利数据进行系统的比较分析，来描述技术可能性的空间，这些数据在最基本的层面上明确地说明了技术的相互依赖性。该项目的一个主要成果是技术能力的详细“地图”，其中潜在的创新途径在视觉和数学上都得到了阐明。该项目通过利用和开发数学、物理、生物和计算机科学的工具，以网络表示的形式对该地图进行数学形式化和统计分析。这种定量和系统的方法是提高我们开发预测模型的能力的关键，该模型可以为公共政策决策提供信息。该项目回答的基本问题包括：(1)理解发明活动所需的技术能力的适当“量子”（基本分析单位）是什么？(2)我们如何才能最好地构建一个技术“地图”，以说明这些量子之间复杂的相互依存关系，并从微观尺度动力学到宏观尺度模式之间架起一座桥梁？(3)根据“关键”（通用）技术能力在生态系统中的地位，哪些特征定义了它们？更广泛的影响：项目制作的技术地图将提供给公众和政策制定者。这些信息提高了我们建立技术预测预测模型的能力，并提高了美国专利商标局对专利活动模式进行索引和监控的能力。

Technology's advance is central to economic growth and development. Furthermore, solutions for many of the planet's most pressing challenges --economic recovery, poverty reduction, climate change, sustainability-- require significant additions to society's technological toolkit. Yet, our ability to quantitatively model and forecast technological change is insufficient. The most common perspective on technological change in economics and management science--that it is a search on a space of technological possibilities--is more of a metaphor than a modeling framework. And the numerous case studies of particular innovations do not amount to a formal, quantitative and predictive theory. The project develops a formal methodology for describing the space of technological possibilities using a systematic, comparative analysis of U.S. Patent data spanning 220 years that explicitly accounts for the interdependencies of technologies at the most basic level. A major outcome of the project is a detailed "map" of technological capabilities in which potential innovation pathways are illuminated both visually and mathematically. The project mathematically formalizes and statistically analyzes this map in a form of network representation by utilizing and developing tools from mathematics, physics, biology and computer science. This quantitative and systematic approach is key to improving our ability to develop a predictive model that can inform decisions on public policy.Among the fundamentalquestions the project answers are: (1) What is the appropriate "quantum" (fundamental unit of analysis) of technological capability required to understand invention activities? (2) How can we best construct a technology "map" that illustrates the complex interdependencies of these quanta, and that bridges from micro-scale dynamics to macro-scale patterns? (3) What characteristics define "keystone" (general purpose) technological capabilities in terms of their position within the ecosystem? Broader impacts: The technology maps produced by the project will be available to the public and to policy makers. This information advances our ability to build a predictive model for technology forecasting and improves the ability of the US Patent and Trademark Office to index and monitor patterns in patent activities through time.