1. The process of knowledge formation in a sociotechnical system.
When you are on a quest to find the answer to a particular question, you might find what you think suffices as an informational explanation to your inquiry. However, Edwards says the ultimate question to ask yourself repeatedly when desiring accurate knowledge is, “How do you know?” Before you know it, you are on a fact-finding mission that will hopefully lead you to the source of evidence. Moreover, inserting the five W’s (who, what, where, why, when) will refine your results further to the point of defining evidence itself! In his book, Edwards utilizes the “How do you know?” process to analyze climate change and the various assumptions regarding global warming. There are many variables associated with collecting weather data from the past and the present including differences in instruments, varying observation hours, and alternate calculations. Attempting to eliminate all the different variables is part of the knowledge purification process. Edwards describes his book as an “historical account of climate science as a global knowledge infrastructure.” (Edwards, pg 8) Many people argue that global warming is based on model predictions, and therefore void of sound evidence. Climate models are used in his book to show that you can arrive at a conclusive reality for global warming and even project future trends from simulation models. The presence of technology among intricate relationships between complex infrastructures and human behavior can be optimized through strategic organization (infrastructure). If we are to arrive at knowledge formation more concrete than probabilistic predictions, the existence of infrastructures and models is essential. After all, “Without models, there are no data.” (Edwards) On the other hand, the more data you have, the better your models.
2. The concept of "vast machine" and knowledge infrastructure.
Edwards defines “a vast machine” as “a sociotechnical system that collects data, models physical processes, tests theories, and ultimately generates a widely shared understanding of climate and climate change.” (Edwards, pg. 8) So what is the difference between a technical system and a sociotechnical system? Mainly the foundation of a sociotechnical system is rooted in social elements, meaning networks of people, places, and things. It is within these networks that knowledge is created and shared as a communal effort.
In the book, the Large Technical Systems (LTS) model addresses the different phases in which infrastructure is formed:
1. Invention
2. Development and innovation
3. Technology transfer, growth, and competition
4. Consolidation
5. Splintering or fragmentation
6. Decline
Some of the systems that evolve during these stages are eliminated in a process similar to survival of the fittest. Other systems that survive the stages can be linked together to serve a greater need. The most important thing to remember is that infrastructures are networks, meaning they come with their own set of management difficulties or “tensions.” (Edwards, pg 12) With regards to climate infrastructures, scientists established an international network designated to collect weather data from all parts of the world. The challenge was coordinating all the different weather data systems into a single global climate information infrastructure (or observing system).
3. The basis of scientific knowledge.
Edwards proposes on page 16 that in order to understand knowledge, one must understand:
How data gets moved around
How they get created
How they are transformed into reliable information
How that information becomes knowledge
Producing and cultivating scientific knowledge requires not only tools for research and media to share it but enough connectedness to warrant informational legitimacy. Data itself is not necessarily the basis of scientific knowledge, just like instrument readings are not the foundation of weather forecasting. Preliminary data is definitely utilized when generating forecasts, but models (specifically computer models) are largely responsible for predictions. To accommodate for the revision of models over time, climatologists use “reanalysis,” which reconciles data taken over long periods of time. Any sort of discrepancy is discarded or adjusted according to the analysis model. Once again, infrastructure is the basis of scientific knowledge, and without it, knowledge would be unreliable and erratic.
4. The concept of globalist information.
The notion of globalist information begins with the conceptualization of earth as a permeable, mutually interdependent community comprised of a collection of information about the whole world. In this sense, the world is full of systems of conducting information around the world as well as systems generating information about the world. These network systems evolved from journalism and postal mail to global environmental monitoring. Edwards decides to concentrate on the oldest globalist information system, the weather data network. Basically climate knowledge infrastructure is an excellent model to predict other types of knowledge infrastructures, especially since global data is knowledge created through an infrastructure. It is important to build a long-lasting network that produces enduring information about the world that can be used for multiple purposes such as forecasting.
