For me, the first challenge for computing science is to discover how to maintain order in a finite, but very large, discrete universe that is intricately intertwined. And a second, but not less important challenge is how to mould what you have achieved in solving the first problem, into a teachable discipline: it does not suffice to hone your own intellect (that will join you in your grave), you must teach others how to hone theirs. The more you concentrate on these two challenges, the clearer you will see that they are only two sides of the same coin: teaching yourself is discovering what is teachable.

The important thing is not allowing those challenges to distract you.

I think that it's extraordinarily important that we in computer science keep fun in computing. When it started out, it was an awful lot of fun. Of course, the paying customers got shafted every now and then, and after a while we began to take their complaints seriously. We began to feel as if we really were responsible for the successful, error-free perfect use of these machines. I don't think we are. I think we're responsible for stretching them, setting them off in new directions, and keeping fun in the house. I hope the field of computer science never loses its sense of fun. Above all, I hope we don't become missionaries. Don't feel as if you're Bible salesmen. The world has too many of those already. What you know about computing other people will learn. Don't feel as if the key to successful computing is only in your hands. What's in your hands, I think and hope, is intelligence: the ability to see the machine as more than when you were first led up to it, that you can make it more.

We struggle to manage complexity every day. We follow intricate diets to lose weight, juggle multiple remotes to operate our home entertainment systems, face proliferating data at the office, and hack through thickets of regulation at tax time. But complexity isn’t destiny. Sull and Eisenhardt argue there’s a better way: By developing a few simple yet effective rules, you can tackle even the most complex problems.

A scientist ought to have a healthy disregard for coincidences.

A scientist's aim in a discussion with his colleagues is not to persuade, but to clarify.

A scientist's aim in a discussion with his colleagues is not to persuade, but to clarify.

If I have learned anything as a scientist it is that one should not make things complicated when a simple explanation will do.

The greatest danger to good computer science research today may be excessive relevance. Evidence for the worldwide fascination with computers is everywhere, from the articles on the financial, and even the front pages of the newspapers, to the difficulties that even the most prestigious universities experience in finding and keeping faculty in computer science. The best professors, instead of teaching bright students, join start-up companies.

A real scientist solves problems, not wails that they are unsolvable.

The competent programmer is fully aware of the strictly limited size of his own skull; therefore he approaches the programming task in full humility, and among other things he avoids clever tricks like the plague.

Honestly, the biggest challenge is just my own brain.

No sociologist, for instance, should think himself too good, even in his old age, to make tens of thousands of quite trivial computations in his head and perhaps for months at a time

I’m complicated, not confused.