The Case for More Transparent Algorithms

Algorithms are now used to sort information, estimate outcomes and rank options. A single score can be convenient, but it may hide the assumptions that produced it.

A transparent system states which inputs matter, what a score is designed to predict and how uncertainty changes the result. It also provides ways to question or correct erroneous input.

From idea to everyday practice

The need for explanation is especially important when users compare prices, investments or potential risks. Historical patterns are not guarantees of future results.

A good algorithm should help people ask better questions. Its confidence should be earned by testing, not just by a polished interface.