Are your recruitment process socially mobilized?

Research has shown that a diverse workforce enhances organizational outcomes in terms of higher productivity, more opinions, and inputs into decision making, and an overall tendency for the organizations to actualize a fulfilling workplace. Thus, it is important for organizations to have a more diverse workforce and considering the fact that recruitment is the first step towards a diverse workforce, it is important for the recruitment processes to reflect the priorities of diversifying the workforce. This can take the form of using technology to enhance the quality of the recruitment process by removing biases and other recognized and unrecognized attributes that human recruiters are prone to when parsing, selecting, and forwarding the resumes.

Indeed, many HR (Human Resources) experts believe that human driven recruitment can lead to biases in terms of selecting those resumes that are of the recruiters liking, be it gender, race, ethnicity, or belonging to the same location or attended the same school or college as the recruiter. In addition, there are other more harmful aspects such as backdoor entry and selecting the resumes based on personal preferences as well as reciprocity for material and nonmaterial gains.

This is where an AI or Artificial Intelligence powered recruitment tools such as Sniper AI can help wherein the AI driven software can be used for color blind recruitment as well as gender neutral and other discriminatory biases that can be eliminated or at the least reduced. In other words, using technology to drive the recruitment process actualizes outcomes that are free from the errors and biases that human driven recruitment is known to have. In addition, AI can be used to enhance the quality of the recruitment process wherein it can drive mass parsing of resumes and synergistic driving of the recruitment process by eliminating the need for human factors to creep into the recruitment process.

How this works is when AI powered recruitment tools are used, the software can parse through any number of resumes at a fraction of the cost that human driven parsing and matching of the resumes with the requirements are concerned thereby creating efficiencies from the economies of scale. In addition, when the entire recruitment process is automated and AI tools are used, synergies accrue from the integration of the entire process that is also free from human biases as well as minimizing the aspect of selecting employees according to racial, gender, ethnicity, or geographical considerations.

Some experts believe that AI can also help from the initial stages of the recruitment process since the posting of job descriptions can be done after screening them for catchwords and phrases that are discriminatory in nature. In addition, AI can also help in reaching out to a platform of potentially infinite number of prospective applicants. Apart from this, AI can help in parsing the social media profiles of the prospective applicants to ensure greater conformity to the organizational requirements as well as alignment of the profiles of the applicants with the job descriptions.

Having said that, it is not always the case that AI tools can lead to reduction and elimination of biases. Indeed, recent research has shown that some tools are known to go haywire at some stages of the recruitment process since the programmed instructions by ill intentioned programmers and even the recruitment specialists can lead to the AI becoming a bit like the humans who have programmed it. This can lead to the biases reappearing and hence, this is something that some experts believe should be avoided or if possible, eliminated.

Of course, the fact that if the human machine interface of the AI tools are programmed or coded to be neutral, then such tools can be effective in gendering and diversifying the workforce. As mentioned earlier, synergies from the integration of human decision making with the capabilities of the AI tools can indeed accrue when one takes the entirety of the recruitment process. For instance, even the decision to hire the candidate at the last stage of the recruitment process can be enhanced by combining the suggestions made by the AI software with that of the human decision making as to the selection stage.

A key consideration for many organizations is the matching of organizational requirements in terms of personality profiles and the desired personality traits. This is typically a highly human centered stage of the recruitment process where the ultimate decision maker has to decide based on a number of factors including gut feeling and plain common sense. While the available AI tools are still reaching these capabilities, tools such as Sniper AI can indeed help by providing data about the personality profiles of the applicants as parsed from the resumes, the personality tests that are again automated and the results of which can be fed into the final loop of decision making stages.

Lastly, while some of this sounds like science fiction, it is indeed the case that many organizations worldwide are already experimenting with wholly or partially AI driven recruitment processes in an attempt to free the recruitment process from selection biases and human preferences as well as to align the diversity requirements with the overall selection process to actualize a gendered and a diverse workforce. To conclude, while machines have not yet started interviewing the candidates or taking them for coffee or lunch for personal interviews, we are getting there where one day the entire process can be AI driven.

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