2015 的文章以及演講，最近冒出來看到的。Google 的 Peter Norvig 提到了用 ML 的方式分析，發現程式競賽的成績與工作品質的負面相關性：「Being good at programming competitions correlates negatively with being good on the job」。
換句話說，程式競賽的成績反而是是個負面指標 (對於 Google 內的情況分析出來的，所以是基於 Google hiring process 的前提過濾過的)。
In this talk, Peter talked about how Google did machine learning and at one point he mentioned that at Google they also applied machine learning to hiring. He said that one thing that was surprising to him was that being a winner at programming contests was a negative factor for performing well on the job.
Peter added that programming contest winners are used to cranking solutions out fast and that you performed better at the job if you were more reflective and went slowly and made sure things were right.
What he's talking about is the fact that several extremely important parts of software engineering are not included in these contests, for example code reusability, maintainability, decomposition of the problem using the OO paradigm, etc. All of these make a good engineer, but are not necessarily needed in competitive programming contests.