Research Shows Automation Can Make Recruitment More Human

New insights from Aptitude Research suggests AI can play a much greater role in talent acquisition than just improving efficiency for hiring managers, it can also make the interview process more human for candidates, something PredictiveHire has long advocated

MELBOURNE, Australia, Feb. 2, 2021 /PRNewswire/ — Aptitude Research has published a new paper showing  that when you shift the focus  in automated Talent Acquisition from an employer-driven view to a candidate-first then it is possible to reduce bias in hiring, at the same time improving the overall human element of recruitment.

The research, sponsored by PredictiveHire, an Australian technology company that has pioneered transparent AI-assisted hiring solutions, shows that  humanistic automation creates personal connection at scale, and works to reduce bias, something no other technology or even human-centred solution can deliver.

Madeline Laurano, CEO of Aptitude comments “The misperception that candidates do not want automation and prefer to keep the current talent acquisition is one of the most significant misperceptions in talent acquisition. Candidates want a fair recruitment process, and consistency in communication. Automation can support all of these initiatives and enhance the humanity of the experience.”

There are four main ways that talent acquisition is made more human with automation when the candidate is the focus, rather than  simply moving candidates through the process:

1. Automation can understand what candidates want: AI considers the unique expectations and experiences of candidates and adapts to them as it learns. Collecting feedback about the recruitment  experience and continually improving the candidate journey can help candidates feel connected and heard.
2. The correct data can interrupt bias early in the process: By creating a consistent and fair experience for candidates early in the  process, and not relying on CV data as the determinate of job suitability,  companies are more successful at reducing bias and increasing inclusivity.
3. Trust can be built through transparent data: Both employers and candidates need to trust the data and methodologies for the  technology that they are using, something that can be achieved through transparency. Companies looking at automation should consider providers that will partner with them and provide transparency.
4. Provide feedback to every candidate: Though natural language processing every candidate receives  personalized feedback and messaging. Leaving unsuccessful candidates feedback they can use for future job searches is empowering and a big leap from ‘ghosting’ or a standard rejection email.