Thinking - Deepstash




  • Most sciences in the modern era—say, after the Second World War—are so technical, indeed esoteric, that their deeper comprehension remains largely limited to the specialists, the community of those sciences’ practitioners. Think, for example, of the modern physics of fundamental particles. At best, when relevant, their implications are revealed to the larger public by way of technological consequences.
  • Yet there are some sciences that touch the imagination of those outside the specialists by way of the compelling nature of their central ideas. The theory of evolution is one such instance from the realm of the natural sciences. Its tentacles of influence have extended into the reaches of sociology, psychology, economics, and even computer science, fields of thought having nothing to do with genes or natural selection.
  • Among the sciences of the artificial, computer science manifests a similar characteristic. I am not referring to the ubiquitous and ‘in your face’ technological tools which have colonized the social world. I am referring, rather, to the emergence of a certain mentality.
  • This mentality, or at least its promise, was articulated passionately and eloquently by one of the pioneers of artificial intelligence, Seymour Papert, in his book Mindstorms (1980).
  • Papert’s vision, rather, was the inculcation of a mentality that would guide, shape, and influence the ways in which a person would think about, perceive, and respond to, aspects of the world— one’s inner world and the world outside—which prima facie have no apparent connection to computing—perhaps by way of analogy, metaphor, and imagination.
  • Over a quarter of a century after Papert’s manifesto, computer scientist Jeanette Wing gave this mentality a name: computational thinking.
  • But Wing’s vision is perhaps more prosaic than was Papert’s. Computational thinking, she wrote in 2008, entails approaches to such activities as problem solving, designing, and making sense of intelligent behaviour that draws on fundamental concepts of computing. Yet computational thinking cannot be an island of its own. In the realm of problem solving it would be akin to mathematical thinking; in the domain of design it would share features with the engineering mentality; and in understanding intelligent systems (including, of course, the mind) it might find common ground with scientific thinking.
  • Like Papert, Wing disassociated the mentality of computational thinking from the physical computer itself: one can think computationally without the presence of a computer.



Breaking down complicated problems into basic elements and then reassemble them from the ground up.

It’s one of the best ways to learn to think for yourself, unlock your creative potential, and move from linear to non-linear results.

This approach was used by the philosopher Aristotle and is used now by Elon Musk and Charlie Munger.