Quotes About Algorithms

computer science is the study of "the phenomena surrounding computers"—all the phenomena,

thought itself is best understood as planning; even higher forms of thought, such as philosophy, the epitome of disembodied speculation, proceed, they argue, by hijacking algorithms originally developed to help us plan movements.

Computers are famous for being able to do complicated things starting from simple programs.

My fantasy is that there is a new regulatory body that is in charge of algorithmic auditing.

They were innocent people. They could just do things you couldn't imagine. I can see code, do you get it? Algorithms that confound straights are just patterns to me. They come in my dreams. I dream the most beautiful programs never written.

The most important goal I had in mind was to convince people to stop blindly trusting algorithms and assuming that they are inherently fair and objective.

Many businesses . . . become highly skilled at using algorithms to produce outcomes that are reliable, that is, consistent and predictable. . . . Companies that devote all their resources to reliability lack the tools to pursue outcomes that are valid, that is, that produce a desired result.

Computers lack common sense. We can train machine learning algorithms to spot patterns and detect signals, but to date we haven't been able to give them the ability to reason from context.

As long as algorithms determine the distribution of profits, they will also determine what gets published. The

In Google's world, which is the world we enter when we go online, there's little place for the pensive stillness of deep reading or the fuzzy indirection of contemplation. Ambiguity is not an opening for insight but a bug to be fixed. The human brain is just an outdated computer that needs a faster processor and a bigger hard drive—and better algorithms to steer the course of its thought.

Cryptography and security engineers need to know more than how current cryptographic protocols work; they need to know how to use cryptography.

Machine learning tends to be more focused on developing efficient algorithms that scale to large data in order to optimize the predictive model. Statistics generally pays more attention to the probabilistic theory and underlying structure of the model.