Kahneman’s book, Thinking: Fast and Slow, spread to a broad audience the cognitive psychological research findings that humans have capabilities to make very quick decisions based on superficial review of the merits of alternatives. These decisions rest on generalization of past experience to a specific newly-encountered phenomenon. These fast decisions serve us well, except when the new phenomenon exhibits key differences, which, upon deeper and slower reflection, dominate the tradeoff decision.
The book seems to have an analog in societal-level decision making. Over the past few years “fast” seems to dominate over “slow.” Our communications and information flow are faster than ever before — texts, instant messaging, news alerts, an hourly news cycle, digital platforms disrupting the print media. The length of the communicated message tends to be shorter than before; book-length writing is a smaller portion of the communication volume. The speed of technological change seems breathless at times, far outpacing the typical density of change based on basic research. The private sector touts “failing fast,” and moving on to a new challenge if the old isn’t achieved. CEOs of publicly-traded firms feel the pressure of quarterly profits much more than pressure on the health of the firm 10 to 20 years out.
Some of the increased pace is wonderful and has produced positive change for individuals and societies throughout the world. But increasingly, I begin to worry about what innovation, what improvements, such a culture might not support.
Last week, as part of my National Science Board duties, I visited the Laser Interferometer Gravitational-Wave Observatory (LIGO) facility outside of Baton Rouge. This facility was key in detecting gravitational waves from colliding black holes in 2015 and from the collision of two neutron stars more recently. It was connected with the awarding of Nobel Prizes recently. It exemplifies the opposite of “fast” in one important sense. The vision of LIGO was set before the 1980’s, with initial funding. There was, as with all breakthrough ideas, with all deeply reflective thinking, opposition. The project was high risk. Once built, the facility detected nothing at all of consequence for seven full years. Consistent attention to improving the quality of the measurement yielded success in 2015, nearly 30 years after inception of the idea. Far from fast.
Another example: In 2002, the idea of building longitudinal data sets, based on student records, that would allow researchers to track the experiences of children in school was formed. Better understanding of the drivers of performance was sought by studying the progress of students over years, seeing whether it varied greatly by different teachers and schools, and measuring their job experiences after they left school. The US Department of Education sponsored the construction of such longitudinal record systems, creating a data infrastructure, taking many years and millions of dollars. Now the states and the country have data resources to answer questions about the performance of educational institutions they never had before.
A final example: Data infrastructure is not unlike physical infrastructure. In the 1950’s the plan for the interstate highway system was a vast investment, building capacity that was not fully needed at the time, but the infrastructure led to vast economic and social changes in the country. A decision was made by people, some of whom would not be alive when the benefits of the decision were achieved.
In short, one of the distinctions between fast and slow payoff often centers around who will benefit. The impact of technology on the speed of much human activity may be making it more difficult to gain support for common good activities whose payoff may be years away. The examples above make the case that some benefits require patient, consistent, adaptive effort over many years. Their benefits to human society, however, seem so important that they deserve our stopping and reflecting about how much time we spend on the immediate and how much time we focus on the long term.