age, wealth, education, career path, scientific specialization, culture, religion, countries, languages, economic philosophy, and political perspective.
A technology may not be immediately recognized by a group or community as disruptive for a number of reasons, including an early judgement that it is not likely to be successful, an initially slow rate of adoption, or a lack of imagination. Numerous academic papers propose lack of imagination as the primary reason for disruption. To various degrees, lack of imagination contributes to most forms of bias or ignorance but appears to be particularly acute in groups or communities who by definition may assemble because of similar viewpoints and who may accordingly be less willing to consider others’ views. For the same reason, ignorance may also be due to lack of knowledge. According to Faber and colleagues, another cause of communal ignorance is that “there is no information available to society concerning this event. By research, however, it would be possible to obtain this information” (Faber et al., 1992b, p. 85). According to the Aspen Global Change Institute’s Elements of Change report, communal ignorance can be overcome through the acquisition of new knowledge achieved “through research, broadly within existing scientific concepts, ideas, and disciplines” (Schneider and Turner, 1995, p. 8).
Many forecasts are generated by a relatively small group of similar individuals (e.g., of the same age group, educational background, culture, or native language). A persistent forecasting system should reduce communal ignorance by including a broader set of communities and viewpoints, such as an open system that encourages global participation. With the advent of the Internet, it is now easy to create Web-based systems that allow individuals anywhere to collaborate on virtually any topic at any time. By leveraging communities of interest and public domain sources of information, open collaboration systems may be used to envision a broader range of possible disruptions.
The persistent forecasting system should utilize processes such as scenario methods and gaming to “imagine the unimaginable” and develop multiple views of potential futures in areas identified as key priorities. Importantly, these techniques must encourage and capture fringe or extreme thoughts from individuals who might be expected to come up with early signals of potential disruptions.
When participation from individuals or groups representing certain viewpoints is insufficient, system designers will need to find ways to encourage greater participation. If the sources of such viewpoints are not available or accessible, proxies may need to be created to replicate the viewpoints. Red teaming and adversary simulations are time-tested methods of creating proxies.
Jesus Ramos-Martin suggests that novelty ignorance can stem from the inability to anticipate and prepare for external factors (shocks) or internal factors such as “changes in preferences, technologies, or institutions” (Ramos-Martin, 2003, p. 7). Natural disasters and resource crises such as limited water, energy, or food are examples of external shocks that might cause novelty ignorance.
While it is difficult, if not impossible, to forecast the exact timing of external shocks, decision makers can benefit from the simulation and gaming of alternative futures to gain better insight into the impact of various shocks under different scenarios. These insights can be used to mitigate the impact of surprise by encouraging the allocation of resources before the surprise occurs.
Surprise may also be caused when information is available but insufficient tools are available to analyze the data. Thus, interrelationships, hidden dependencies, feedback loops, and other factors that impact system stability may remain hidden. This special type of challenge is called complexity ignorance.
Our world is comprised of many complex adaptive systems (CASs), such as those found in nature, financial markets, and society at large. While personal and communal ignorance can be mitigated, ignorance coming from