The Inventions

Resume / CV

United States · Early 20th century · Early 20th century
The resume is not a neutral record of what someone has done. It is a format that determines what counts as relevant experience and what does not, compressing a life into categories that the hiring system recognizes.

Before the twentieth century, seeking employment was largely a matter of personal connection, apprenticeship within a trade, or direct demonstration of skill. Letters of introduction served a similar function to modern cover letters, but they were personal recommendations, not standardized documents. The concept of summarizing one's qualifications on paper for a stranger to evaluate was unfamiliar to most workers.

The rise of large-scale industrial and corporate organizations in the early twentieth century created a need for standardized hiring processes. Personnel departments, which emerged in the 1910s and 1920s, needed a way to compare candidates who had no personal connection to the organization. The resume filled this function, providing a compressed, scannable summary of education and experience that could be evaluated quickly by a hiring manager who had never met the applicant.

The resume's format conventions consolidated over the mid-twentieth century. Reverse chronological order became standard, emphasizing the most recent position. Education and experience were separated into distinct sections. Length was constrained, typically to one page for entry-level candidates and two for experienced professionals. These conventions reflected the hiring system's preference for efficiency and pattern recognition over nuance.

By the late twentieth century, applicant tracking systems introduced automated screening of resumes using keyword matching. A 2019 study by Preptel found that approximately 75 percent of resumes submitted to large companies were rejected by automated systems before a human reviewer ever saw them. The document that was supposed to represent a person's professional identity had become a text to be parsed by algorithms optimized for speed rather than understanding.