The process of hiring is evolving rapidly since there are now applications and software that deal with resumes and even arrange interviews without getting the help of people. Although the new method of hiring data is attractive, it brings along issues as well.
If there is a system that has been silently favoring candidates with specific names, profiles, and applications and nobody raises any questions about it, this might result in problems for employers.
Fairness and trust cannot be gained easily. These are achieved with the help of knowing how and when the data collected by AI should be taken into consideration.
In this article, you will be presented with some recommendations showing how technology can be put to good use when people are involved in the hiring process.
Check What The Machines Are Writing
AI is playing a big role in the creation of job advertisements, screening emails, and interview questions. This is fine in principle, but somebody still must look carefully at the AI-generated results.
One of the easiest practices is to use an AI content checker to evaluate the generated text and look for instances of potential bias, overly typical language, or writing that doesn't reflect the true nature of the position.
One might also find the content checker useful for identifying texts that sound too robotic and may scare away highly-qualified applicants even before they apply.
This checking process can be done very quickly, and using this simple method helps maintain the brand voice.
Companies that skip this step may find out about the problems caused by the inappropriate use of AI only after they are pointed out by some candidate.
Build The Screening Process Slowly
There's a mistake many hiring teams make by attempting to automate everything on the first day. However, the process of building automation systems is best undertaken in stages.
While it is easy to make the mistake of automating everything from the very start, it is much better to start off using automation to perform simple duties such as sorting resumes before performing any actions that will have to do with the final decision.
Then, whenever you find that something is going wrong, do not assume that the automation system has worked perfectly from the very start and simply make the necessary adjustments.
While all this may seem inefficient at the beginning, it will provide recruiters with an opportunity to see the likely problems and build up their confidence before the system will be able to affect the hiring process significantly.
Tell Candidates When AI Is Part Of The Process
Being informed previously that a program contributed to an applicant's professional path is a piece of information that nobody likes to receive. AI disclosure modifies the perception of an applicant of the procedure that he or she was involved in.
The disclosure does not have to be a lengthy disclaimer full of many legal terms and in very small print. A simple couple of sentences where resumes are first screened by a computer, and the shortlisted candidates are reviewed by a human, usually is enough.
Honesty in this regard creates more goodwill than keeping silence does, even if the applicant gets a disappointing response to an application for employment. People are thankful for knowing what happens in this process.
If an applicant knows everything at the beginning, it lessens the probability of feeling confused after receiving a negative response for the application.
Bring In Outside Eyes For Regular Bias Checks
Internal teams quickly adapt to their own technologies, making spotting the bias that exists right in front of their eyes hard. This is why outside auditing is critical.
An independent entity that has nothing to gain from the tool can examine its performance by sex, age, and other traits in order to determine if there are any issues with the results.
The audits don't have to be full-blown productions with lawyers all over the place; even a small review every couple of years can detect potential issues based on real historical data.
The teams that think of audit parameters as a “one-off” survey miss the gradual evolution of the tools that have become less fair over time.
Job demands change, and the applicant pool shifts, and technology working at one point in time may eventually not work at all without an independent check.
Keep A Human Making The Final Call
It is possible for artificial intelligence to reduce over five hundred submissions down to fifty in a matter of minutes, which is indeed an advantage for busy teams involved in recruiting. However, its use should never extend to making hiring decisions.
Having a human being in charge of this last phase allows one to take into account some points overlooked by machines; for example, the gap in the candidate's working experience that is involved in their career path from caregiver to applicant.
It also gives a candidate the opportunity to speak to a human being who is responsible for their situation rather than communicating with an uninformed and impersonal program.
It does not mean completely discarding the information provided by the program. Information provided by the program should be treated as one of the factors affecting the recruiting decision rather than the final one.
Test Tools On Real Candidates Before Going Live
A selection tool that appears impressive in a vendor demonstration may be completely different when confronting real candidates applying to real jobs. Testing turns out to be crucial prior to any organization-wide implementation of the selection tool.
Evaluate the selection in a quiet way, applying it to a previous hiring experience's real but anonymized data, then compare results with what has actually happened to these candidates at the time.
Special attention should be paid to whether specific groups of people received lower scores for reasons related not to qualification or capability.
Conducting this kind of dry run will cost some time in advance but will avoid much larger troubles in the future when real candidates participate in the selection process.
The vendors are expected to present their tools in the best possible light. Therefore, it is necessary that the employer verifies the claims statement made by the vendor.
Be Honest About What Happens To Candidate Data
All resumes, cover letters, and interview recordings which pass through AI represent personal data and candidates have the right to know exactly where they end up. This means that organizations such as job placement agencies should explain whether any data is stored and for how long.
Do not use vague language that will make candidates speculate as to the parties that can have access to their data and how it will be used afterwards. Transparency is imperative here.
The issue is even more serious than it may seem, as it is known that candidates who feel that they are being monitored become unmotivated and do not give answers that reflect their true feelings.
A brief confidentiality note would serve well at the application stage and would be compliant with the law without putting a burden on candidates to understand it.
Teach Recruiters What The Tools Actually Do
A recruiter who is not aware of how a screening system evaluates applicants may also not notice minor errors in the process. It is essential to provide basic instruction before trusting them with the day-to-day utilization of that system.
This requires neither recruiters to be turned into engineers nor to be knowledgeable about data science overnight, but rather to simply gain the necessary understanding to be able to tell when a rating seems odd.
Vendors facilitating the use of such tools usually do not have issues explaining how their systems work, provided they are asked specific questions.
Those teams that treat artificial intelligence solutions as authorities tend to comply with their recommendations even when something seems off. This is actually a bad strategy, as imagination and curiosity must prevail in such situations.
Training recruiters at the very beginning of the process transforms them from passive participants into responsible users overseeing those tools.
Give Candidates A Way To Push Back
It’s important for candidates to have access to a formal means of voicing any concerns they may have, as even the most careful systems can sometimes miscalculate things. An email address to contact if an applicant wants to ask questions about a rejection would suffice.
There is hardly an expectation to analyze an entire process or to understand in detail how a verdict was reached.
Companies that open such channels are, most likely, able to spot errors that they cannot see otherwise, like resulting in wrongly screening out an excellent candidate because of poor formatting of a resume.
Such communication illustrates respect and enables candidates to understand that the employer is open to inquiries instead of relying on algorithms that are impossible to explain. Moreover, setting up such a system doesn’t require lots of investment.
Don't Let Speed Replace Good Judgment
The main advantage of AI is its speed, but this is precisely why hiring teams must be wary of measuring success based on speed alone. Hiring someone quickly does not matter if that person is not the right choice.
Don’t give in to the temptation of measuring success just by time-to-hire or the number of resumes reviewed in a certain period. These figures seem good on paper.
However, they do not address the question of whether the right candidates were selected for the role at hand. There is a significant difference between efficiency and fairness.
Having a moment for a human to check the shortlist will help maintain the balance.
When under constant pressure to speed things up, companies often skip the steps that might come in handy in protecting their reputation.
Final Thoughts
Achieving the right balance of artificial intelligence, fairness, and trust in the process of recruitment means working on establishing patterns of behavior that successfully combine technology and people.
Therefore, even though all of the practices mentioned above involve the need to perform thorough checks of processes and ensure that candidates are literally heard when there is a problem, they do not imply rejection of useful solutions.
It is worth emphasizing the importance of confirmation on the part of the hiring team in order to be sure that the whole automation process remains trustworthy.
Companies that manage to do that acquire valuable assets in the form of candidates who are willing to trust the whole process of hiring.
