Saturday, May 18, 2019

reading review - deep thinking (change, progress, and innovation)

One of the major themes in Garry Kasparov’s Deep Thinking was the way society struggles to find the right pace for change. It’s a struggle most noticeable anytime we lament technology taking on our work – in other words, it is a constant and ever-present protest about what has been among the most basic and repeated stories from the history of civilization.

Perhaps this speaks to the mere power of the status quo, especially for those who would benefit from keeping things unchanged. As Kasparov points out, a gravedigger would have selfish reasons for worrying about new breakthroughs in medicine just as a mosquito net manufacturer surely does better business in the absence of a malaria cure. There is also a good example from the book about how the status quo can excuse us from facing a certain fear – until a 1945 work stoppage by elevator operators forced many to scale skyscrapers by foot, the general mood in society was apprehensive toward riding in an elevator alone. Therefore, the last true obstacle to the full adoption of automatic elevators was the public's reluctance to make the change.

The right pace for change is a dilemma that defines the implementation of any new innovation. The four decades it took for automatic elevators to catch on is perhaps a bit long in hindsight but there is always good reason to be skeptical about how much can change right away. There is a reality Bill Gates once pointed out that applies to almost all new technologies - progress forecasts for the first couple of years are almost always exaggerated while the potential benefits of what might happen as new users adopt the technology are rarely given full weight. The struggle between idea and breakthrough then is finding the balance between the champions who overestimate short-term progress and the opponents who underestimate the long-term gains.

Of course, moving slowly isn’t a guarantee of anything. Those who only rely on optimization to bring on improvement can obscure the need for a more thorough rebuilding or rewriting of the existing method. If the rate of change is too slow, the potential of creation through destruction is exchanged for the surefire but perhaps limited improvements that might come about from a committed optimization method – evolution is, after all, merely change, and no guarantee of improvement.