Applying AI merged with multiple data matrixes for optimizing & atomizing the recruitment process.

Offentlig prosjektsammendrag

How organizations assess candidates in a recruitment projects differs greatly. Research show that too often, decisions are made on first impressions, confirmation- and similarity bias as well as gut feeling. It does not mean that one cannot be satisfied with previous hires. Even blind chicken can find corn. The question is not what you have, but what you potentially missed out on in terms of achievements from the selected candidate. By applying artificial intelligence combined with high level of automation we aim at creating an efficient digital recruitment platform where it all boils down to numbers and subjectivity is removed. The online tool will measure and combine scores of factors such as skills, personality, ability and motivation to create a predictive scoring model of matching. The tool will enable a more efficient recruitment process and higher quality of matching candidates with specific organizational requirements. It will provide a quantitative basis for comparison between candidates and interviewers. It will offer the opportunity to evaluate candidates in an objective manner, opening our understanding of what is actually important to measure during the assessment of candidate. It will provide codified and structured data for why we select one from the other, and then post recruitment collect actual data of matching quality in order to improve the predictive models further.