The labour market in the context of the knowledge economy is never never-ending crisis. The constantly changing market requires constant innovation from the recruiter’s perspective. The World Economic Forum’s report on “Future of Jobs 2023” emphasizes the urgent need to look into the recruitment process and preparedness of organizations to tackle the impact of technological changes in the labour market and jobs. The report forecasts that 23% of the jobs will change globally in the next 5 years and 69 million new jobs are expected to be created across 45 economies, covering 673 million workers

Pervading recruitment strategy: Current era

Recruitment is the process of generating a pool of qualified candidates for a particular job. After the emergence of artificial intelligence, HR professionals have started utilizing AI to shortlist candidates. Artificial intelligence uses various methods to shortlist candidates. Some of the methods are:

• Keyword shortlisting: These parsers are a type of AI tool that searches for keywords, patterns, and phrases in a CV.

• Based on Grammar: A grammar-based parser attempts to add context to a CV by searching for words and phrases according to set grammatical rules.

• AI Focus: Parsers featuring an AI focus use machine learning algorithms to learn how to read certain types of text more accurately over time.

Is it justifying the cause?

HR professionals heavily rely on AI-Resume shortlisting, as it takes less time to shortlist compared to Human shortlisting. Yet research and domain experts are pointing out “n” number of pain points in this recruitment ideology. The following points briefly touch upon those issues:

• AI shortlisting is based on the premise of prewired data, if the resume of an individual isn’t resonant with the AI’s search engine optimization, then a perfect candidate can also be rejected.

• The data for the shortlisting are programmed by humans, this paves the way for biased data input leading further to improper shortlisting.

• Certain job characteristics can’t be clearly defined like emotional intelligence, creativity, personality, etc… In this scenario, it will be nearly impossible for the AI to read between the lines to understand these hypothetical constructs. In totality this negligence from the AI may lead to the temporally stable phenomenon, that is, “The Principal agent problem”.

To overcome this issue, recruiters are partially focusing on behavioural assessment.

Behavioural assessment a costly panacea:

A behavioural assessment is a pre-employment test that evaluates how well applicants might fit a specific open job position and then behave in the workplace. They evaluate a candidate’s personality traits, motivations, and behavioural habits to predict their likelihood of succeeding on the job.

This behavioural assessment can be used to understand the candidate’s basic disposition, creativity level, leadership skills, etc… By putting them in a situational/ self-report inventory test.

Like every test behavioural assessment also has its limitation. It can be in terms of:

• Reliability and Validity

• Cognitive biases.

Reliability and Validity is an aspect that isn’t in the control of the recruiter. So, in this article, Cognitive biases and their impact on behavioural assessment will be touched upon.

Do biases penetrate behavioural assessment?

Representative heuristics is a mental shortcut that is used by humans to make a quicker decision by comparing with the already existing prototype (that is formed based on prior experience and nurture factors). Whenever a person is put to a situational test, the recruiters might have the tendency to prefer men over women in the context of managerial posts as it is already aligned with their preconceived prototype. This is one of the biases that can be pertinent during the hiring process and there are “n” number of biases still attached to the behavioural assessment.

Do all soft skills have community-wide accepted clear definitions?

No, there are certain constructs like creativity, emotional quotient, intelligence quotient, etc… That doesn’t have a clear-cut definition that is widely accepted in the psychologist’s community. In this context utilizing behavioural assessment will be quite tricky and difficult as there are no obvious measurement criteria. Eg: Sternberg defines creativity differently compared to Osborn’s way of defining creativity.

The two-pronged strategy:

The above-discussed methods are the prevailing ones in the current era, regardless of blatantly ignoring this for future needs. A blend of both with some tweaks can be useful in managing the future hurdles in the changing job and labour market.

• AI- Resume shortlisting can be strictly used to shortlist candidates based on basic qualifications required for the job rather than emphasising more on keywords that match the job description.

• Using the Critical incident techniques to do job analysis and utilizing the similar behavioural traits required for the job to create a simulation. This simulation can be used as a selection tool to understand the candidate’s disposed of behaviour.

• Utilizing marketing principles to enhance the employee value proposition to attract the best talents in the industry.

The above-stated methods aren’t the ideal solutions, but they can be used by experts as a base reference to customize it to their industrial needs.

The future is going to be driven by technology. One of the beneficial things for organizations is the increased productivity fostered through technology. So, rather than solely focusing on the negatives associated with technological growth, firms should invest heavily in R&D to form an effective recruitment strategy to form a virtuous cycle.