Algorithms are a hot topic right now and whether we like it or not they play a huge part of our lives

Algorithms are essentially a way a computer processes data.  Algorithms detail specific instructions for a computer to perform in a specific order – much like following a recipe.  

Companies may use hiring algorithms to

  • Attract certain types candidates
  • Be present on certain platforms
  • Highlight passive candidates for recruitment.
  • Score CVs
  • Assess candidate competencies

Algorithms present a point of contention between technology and human judgement. Recruiting is the result of a series of decisions and algorithms play an important part in this process (listed above).

Algorithms are used by companies to speed up the recruitment process and to prevent bias. Studies have demonstrated companies end up with employees that are more productive and have higher employee retention rates.  However, while many argue algorithms help hiring managers avoid their own prejudices by adding consistency to the hiring process, algorithms introduce new risks of their own.

As we have seen in the last week with the upset in ‘A’ level scoring, it is important to avoid institutional and historical biases.  Even if algorithms remove some subjectivity from the recruiting process, humans are still very much involved in hiring decisions. Unfortunately, most algorithms will drift toward bias. That said, their potential shouldn’t be discounted – companies successfully use algorithms to boost hiring quality and aid the functional shortlisting process.

The two key areas are

  1. Candidate Pool: During the “sourcing” stage, technologies help to advertise job openings, notify jobseekers about potentially suitable positions, and resurface prospective candidates to recruiters. To attract applicants, many employers use algorithmic ad platforms and job boards to reach the most “relevant” job seekers.
  2. Shortlisting: With a good flow of applicants, employers will want to focus on the most suitable candidates. Screening algorithms are used at this stage as decision aids and automatically reject a significant proportion of candidates. Some of these screening algorithms are simply ‘qualification questions’ to establish whether candidates are minimally qualified; chatbots and cv searching tools can easily perform this task.

Algorithmic candidate selection promises a more effective recruitment process for all concerned. However, if the data is polluted by bias (sexism racism etc), The algorithm struggles to deliver the process. Or worse, undermines it by producing the same results they were designed to eliminate.