There is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively [1, 2]. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas.
Walking intrigues the deskbound. We romanticize it, but do we do it justice? Do we walk properly? Can one walk improperly and, if so, what happens when the walk is corrected?
This talk centered on Hamming's observations and research on the question "Why do so few scientists make significant contributions and so many are forgotten in the long run?"
How do we know what’s the right direction [for computers to take]?
Ultimately it comes down to taste. It comes down to trying to expose yourself to the best things that humans have done, and then trying to bring those things in to what you’re doing.
Picasso had a saying: “Good artists copy, great artists steal.” And we (at Apple) have always been shameless about stealing great ideas. And I think part of what made Macintosh great was that the people working on it were musicians and poets and artists and zoologists and historians who also happened to have been the best computer scientists in the world. But if it hasn’t been for computer science, these people would all be doing amazing things in life in other fields. And they brought with them — we all brought to this effort — a very liberal arts air, a very liberal arts attitude, that we wanted to pull in the best we saw in these other fields into ours.