Will brains or algorithms be sovereign in the kingdom of science?

Will brains or algorithms be sovereign in the kingdom of science?

David C Krakauer writes:

A schism is emerging in the scientific enterprise. On the one side is the human mind, the source of every story, theory and explanation that our species holds dear. On the other stand the machines, whose algorithms possess astonishing predictive power but whose inner workings remain radically opaque to human observers. As we humans strive to understand the fundamental nature of the world, our machines churn out measurable, practical predictions that seem to extend beyond the limits of thought. While understanding might satisfy our curiosity, with its narratives about cause and effect, prediction satisfies our desires, mapping these mechanisms on to reality. We now face a choice about which kind of knowledge matters more – as well as the question of whether one stands in the way of scientific progress.

Until recently, understanding and prediction were allies against ignorance. Francis Bacon was among the first to bring them together in the early days of the scientific revolution, when he argued that scientists should be out and about in the world, tinkering with their instruments. This approach, he said, would avoid the painful stasis and circularity that characterised scholastic attempts to get to grips with reality. In his Novum Organum (1620), he wrote:

Our new method of discovering the sciences is such as to leave little to the acuteness and strength of wit, and indeed rather to level wit and intellect. For as in the drawing of a straight line, or accurate circle by the hand, much depends on its steadiness and practice, but if a ruler or compass be employed there is little occasion for either; so it is with our method.

Bacon proposed – perfectly reasonably – that human perception and reason should be augmented by tools, and by these means would escape the labyrinth of reflection.

Isaac Newton enthusiastically adopted Bacon’s empirical philosophy. He spent a career developing tools: physical lenses and telescopes, as well as mental aids and mathematical descriptions (known as formalisms), all of which accelerated the pace of scientific discovery. But hidden away in this growing dependence on instruments were the seeds of a disconcerting divergence: between what the human mind could discern about the world’s underlying mechanisms, and what our tools were capable of measuring and modelling. [Continue reading…]

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