| There are a few problems with resumes: - Job candidates are often not good at building resumes that market themselves to a specific role. - Job candidates have an incentive to write the boldest resume, while still being technically honest. - Resumes are typically 1 or 2 pages and are missing a lot of data about work histories that span years to decades. On the other hand, the academic world has a similar, but much more interesting dataset: - There is a very narrow culture that defines what a good CV is. - CVs are filled with verifiable accomplishments like publications. The existence of the publication can be verified with a Google search, and a publication's usefulness can be approximated by the number of citations proportional to similar papers. - CVs are much longer than an industry resume, giving more data for an algorithm to parse. I think there is potential for academic jobs to programmatically find candidates based on analyzing CVs and publications for qualified job candidates... but the academic world is also small enough that automation may not be necessary. For industry jobs, I think programmatically-administered work-sample tests are the future, even if candidates hate them. Senior candidates have the bargaining power to avoid work-sample tests, but everybody starts off as a junior candidate. Everybody may end up taking work sample tests for their first job in industry--much like (nearly) everybody takes a standardized test for undergraduate college admissions. |