Algorithm vs Human Hiring

If you are in the job market feverishly hunting for a position, either fresh out of school or needing to switch job, you will know what I am talking about. Every time you send out a resume with a cover letter, you wonder if it is going down a black hole never to be seen again. On one hand, people make hiring decisions based on similarities that have nothing to do with the job requirements — like whether an applicant has a friend in common, went to the same school or likes the same sports. On the other hand, if this process were to be automated through a web application or software, the computer would not be able to assess human skills such as making conversation and reading social cues. The system is obviously flawed and we need to find a way to make it better. A hybrid of the two sounds like the most reasonable answer here. And data is creating a need for new roles, like diversity consultants who analyze where the data shows a company is lacking and figure out how to fix it. People will also need to make sure the algorithms aren’t just codifying deep-seated biases or, by surfacing applicants who have certain attributes, making workplaces just as homogeneous as they were before.