Technology forecasting and social change have become integral parts. The effect of technology innovation has become profound on social transformation. Once the current wave of our work and way of getting things done starts declining, while the next wave starts growing around emerging technology, we all start experiencing the effect of change. However, such change is inevitable for our continued progression. Hence, we need to focus on technology forecasting for managing social transformation with less pain.
With the given rapid transformation, it’s a burning need to look at technology forecasting and social change. How many jobs will be lost or created over the next 20 or 30 years? What kind of education, skills, or degrees will be relevant? How will goods and services change, and what would be the customers’ responses to them? Of course, nobody can exactly answer those questions. They are many predictions and numbers, with wide variations. Hence, we cannot rely on any one of them. But they are essential for everybody to know. Answers to those questions are crucial for deciding about education, career, and investment—among others.
By the way, why are they difficult for us to answer? This is due to the fact that technological change will empower ideas to bring transformation in goods and services. It will also affect the competence needed in making, distributing, and consuming those products. No one exactly knows how technology will be amenable to growth, and innovators succeed in unfolding the change. Hence, no one can predict the future. But everyone should take decisions upon taking into consideration of the likely unfolding future. Thus, technology forecasting and social change have been the agenda of everyone.
The decisions we make today will determine the outcome in our life after 10 or 15 years. Therefore, to succeed in the future, our understanding of the like future matters. We have to create a map to the future for looking at the big areas of opportunity and also transformation. By the way, what tools do we have to help systematically think about the future and develop foresight to decide smarter today?
Debunk technology heroism—make technology forecasting and social change community affair
As technology innovation dynamics affect everybody’s life, we can no longer rely on technology heroism. Innovation is too important to be left to a few individuals’ business interests or investment banks as a magical show. Consequentially, we cannot live in a highly uncertain world. Hence, we should focus on figuring out how technology innovation grows, declines, and transforms society. If we look at individual waves of technology innovations, they appear to be random, innovation magic. But once we look at them at the interconnection between technologies and society, and economics and organizations, we succeed in comprehending big, complex transformations. This systematic thinking about the future is absolutely essential for making better choices today. Whether we are an individual or a member of an educational institution, investor, startup, or government organization, it matters.
Lack of data about the future makes technology forecasting and social change daunting
There is no data for the future–all the data are about the past. Based on historical data, we can continue planning and acting along the same trajectory. That is fairly easy! Unfortunately, that is the recipe for failure in the age of rapid transformation due to technology innovation. Hence, instead of extrapolating data, we need to analyze them in detecting patterns for theorizing the underlying technology innovation dynamics so that we can detect unfolding trends and discontinuity.
Two waves keep transforming: underlying complexity of technology forecasting and social change
We live in a world where the dynamic of two waves transforms the world around us. The first wave belongs to existing products and jobs in making them. They offer us the means to serve our purposes. Due to the progression of the underlying technology core, this wave has been rising. The availability of complementary technologies also keeps adding momentum to this wave by adding or improving features. For example, the internal combustion engine-based automobile has been the current wave. However, due to the maturity of the underlying technology core, the current wave starts showing signs of saturation. Hence, it creates the opportunity of offering an alternative.
Aspiring innovators take this opportunity to change the technology core. However, invariably, the change of technology core leads to the primitive emergence of alternative, thereby forming the new wave. Due to the high amenability of the emerging technology core to growth, the new wave keeps growing. Subsequently, the mature wave’s appeal or demand keeps declining, while that of the emerging wave keeps growing. However, nobody knows exactly when the next wave will start. Even after the start, at what rate that will grow is not known. Moreover, will the next wave take over the previous wave is also very difficult to predict.
For example, the wave of changing the horse with ICE started in the 1880s. Upon completing the journey of taking over the previous wave by the 1920s, the ICE-based automobile has been still growing. In the 1990s, there was an attempt to chance ICE with fuel cells. But, it did not grow rapidly to take over ICE. However, at the dawn of the 21st century, lithium-ion battery growth encouraged innovators to chance the ICE with the electric battery. Despite hope, the electric vehicle wave has yet to grow to take over petroleum-based automobiles.
Technology forecasting helps in predicting the dynamics of change
The large-scale transformation occurs due to the descending of the curve on which we live now and the ascending of the next. The descending curve is the one on which we have been living for a long time. Our jobs and demands for education and skills are for operating this curve. We have rules, regulations, and usage patterns for this curve. We know how to live this way. Of course, the decline of this curve and rising of the next transforms all these. Hence, we need to predict for coping up and leveraging.
However, the fuel of the ascending curve is the emerging technology core. This technology core should have enough potential to offer better substitutions, preferably at a lower cost, than those goods and services that we are using today. Hence, the likely transformation depends on the growth of the technology core. Therefore, the growth pattern and forecasting of the technology offer us an indication of the scale, scope, and speed of the likely transformation. For example, whether the next wave will serve the pockets or take over the whole market will vary. Similarly, the speed of transformation will also depend on the amenability of the growth of technology.
Examples of the role of technology in affecting the transformation
In the 1980s, renewable energy technology started showing the potential to take over the polluting fossil fuel. But due to the slow growth of the underlying technology core, it has not succeeded even after 40 years of its emergence. On the other hand, the digital camera took over the film-based ones in just over 20 years. Similarly, PC-based word-processing succeeded to destroy the demand for typewriters and millions of jobs in making and using typewriters just over 15 years. On the other hand, both fuel cell and battery-based electric vehicles still have been struggling to take over gasoline-powered vehicles. Hence, we should look into the growth dynamics of the underlying technology cores to predict both scale, scope, and transformation speed.
Look back at the past for technology forecasting and social change
In order to understand the like trend shaping the future, we should look back in detecting patterns. For example, will Tesla be able to monopolize the automobile industry by pursuing the software business model? To draw a lesson, we should look back at the way Microsoft or Apple did. We need to detect patterns, and it’s likely reoccurrence in making technology forecasts and social change. We should look back past three industrial revolutions in detecting patterns for detecting the trend likely to grow and unfold during the fourth industrial revolution. However, technology innovation is about creating a new future. Well, why do you look back at the past? In fact, the future is not the repetition of the past. But there are larger patterns–which keep repeating around different technology cores in shaping ideas of getting the job done better–forming the future.
Detect signal and patterns in predicting the trend shaping the future
Do we detect signals indicating the likely future transformation? In some cases, we do. For example, people prefer to have an online transaction. Does it mean that we are moving towards a cashless society? As opposed to standing in the line to check out luggage, people prefer to have self-service. Does it mean that people like less human intervention to get jobs done? If technology makes less human contact also a cheaper means, are we not supposed to see fewer and fewer jobs in service? On the other hand, human presence in production is a source of contamination and errors. If machines can perform those activities, causing less contamination and making fewer errors, and if it becomes a cheaper option, should we not expect increasing machines’ roles in production?
Many such signals are all around us. It’s time to detect the underlying trend for anticipating likely transformation. To make long-term decisions, we need not be exactly correct about the rate at which those transformations will occur. Often, detecting signals in assessing the trend is good enough to be on the right side.
Engage the community to make technology forecasting and social change everybody’s agenda
Well, this job of detecting signals, observing underlying patterns, and identifying the trend or tide, should not be the job of a few futurists. We should all get involved in the discourse to increase accuracy and figure out the future we want. If the trend is moving towards the direction what most of us do not like, we should respond collectively. However, a collective response will be an independent decision taken by each individual, family, firm, and Government agency. Hence, each of the actors should have adequate understanding to be on the right lane collectively.