For every hiring manager and recruiter, one of the biggest challenges is to ascertain the authenticity of a candidate, particularly their qualifications and ability to fulfill a job requirement. And let’s admit it, a resume can never be taken on its face value. As unpleasant as it sounds, the fact is, most candidates fudge their technical skills. And with hundreds of resumes to screen and sort, it is almost impossible for hiring managers to verify the authenticity of every candidate’s skills. Hence, AI-based assessment tools.
Machine learning has evolved leaps and bounds giving scientifically generated, data-driven results. By using AI-based pre-employment assessment, gaps in the hiring process can be easily filled.
Lately, there has been an increase in pre-employment assessment tests that integrate AI. These tests not only make the screening process convenient but also offer candidates organized and holistic recruitment experience.
That being said, it is important to ensure that these AI-based testing tools also render the right results and give you a fool-proof assessment of your candidates, especially their technical skills.
How do AI assessment tools ensure authenticity?
HR tools integrated with AI have redefined the entire process of screening and shortlisting of candidates.
The predictive analytics of machine learning is used to read micro data points in a candidate’s application through algorithms, thus deriving a completely scientific result.
The tools allow you to compare the applicant’s skills against an “ideal” candidate as predetermined by the system. Some tools are designed with the capability to analyze the tone and language of an application, which reflects their personalities and professional capacity while being tested.
For technical assessment, it is extremely important to understand the validity of the candidate’s existing skills, or as mentioned in their resume/initial application.
Software with tools like Global Code Verification System can evaluate codes written by applicants in their pre-employment tests. It measures the test code’s reliability, quality, scalability, and similar parameters against best practices. By analyzing test cases, it can then estimate the candidate’s potential as a tech professional and capability to fulfill the job role. Once done, the software then generates a score for the tested candidate for further selection.
At the pre-employment level, it is often a concern if candidates plagiarize or violate test instructions. And such concern is valid. When conducting tests on a large scale, there are always chances of cheating and it is not possible to manually cross-check and verify each test result. But, with proctoring tools, the assessment software can closely monitor any suspicious activity and flag instances of violation.
With AI-run proctoring tools, testing software does a pre-test check of the candidate and the testing environment (considering they complete these tests in their personal space and time). The tools run a background check by verifying the candidate’s identity.
In a protected testing environment (virtual) candidates do not have access to external sources. The AI tools help gauge the authenticity of their tests through the movement of face, eyes, and other actions.
Post the test, results are automatically generated by the software and put together in a detailed, analytical report in a customized format as desired by the hiring manager.
AI-based assessment tools can reduce bias
It is also important to ensure that an assessment is done without bias. And let’s face it, wherever there is human interaction involved, there will be discretion, true to our nature. And personal opinions hinder the key objective of a clean, balanced test result. With AI-based tools, it is easy to avoid such emotional interference in a candidate’s test assessment and arrive at results driven by only hard data and nothing else.
Along with assessing key competencies and soft skills, AI-based assessment tools also ensure quality hires and improve the overall performance of the HR. When choosing an AI-based assessment software, make sure it meets all your recruitment goals and includes all tools necessary to evaluate your candidates in the best possible way.
- Big Challenges Facing Tech Teams and How to Tackle Them - November 15, 2022
- Protect Test Integrity in Remote Assessments with AI - November 7, 2022
- Skill Gaps in Software Development: How to Identify and Close Them? - October 31, 2022