Among the trends of 2022 are certainly diversity and inclusion, and a company today that does not move in the direction of embracing differences and guaranteeing everyone the same opportunities through inclusive actions and policies seems almost anachronistic. Not only that, not considering diversity in the workplace can be counterproductive in the long run. But how can Artificial Intelligence help in this regard? Let us look at it in this article.

SOMMARIO

• Increasing diversity and reducing bias in recruiting
• The contribution of AI in recruiting
• Can artificial intelligence be neutral and objective?
• Diversity workplace: creating an inclusive environment in the company with AI

Artificial Intelligence helps, from a recruiting point of view, by avoiding discrimination and generational and gender gaps, increasing diversity and removing all cognitive biases that may exist during a search and selection process.

These are all fundamental aspects because they allow not only for a recruiting process to be successful but also for talented people to be genuinely valued and for this to be done more quickly and effectively, thereby increasing the likelihood of growing in the market, finding new business opportunities and entering new markets. In addition, hiring people with different backgrounds and cultural backgrounds, perhaps matured in cross-border contexts, brings new perspectives to the company, new points of view and consequently more innovation as well as different ways of dealing with problems. Let us see how Artificial Intelligence can help in this regard.

Increasing diversity and reducing bias in recruiting

First of all, thanks to AI, it is possible to reduce bias in recruiting. This makes it possible to make significant steps toward diversity & inclusion. Blind recruiting also helps a lot in this respect.

What is this? It is a process that HR professionals carry out to eliminate personal information about candidates that could influence a hiring decision or, even before that, the success of an interview. Blind recruiting eliminates cognitive bias, i.e. the distortions that every person, even unintentionally, has.
Knowing that, for example, a candidate has lived in a specific country, or that he/she comes from a specific family, or that he/she is no longer so ‘young’ can influence his/her selection.

With blind recruiting, the risk is not taken because some sensitive information is hidden and you help to create a work environment that is truly inclusive.

The contribution of AI in recruiting

In all of this, a considerable contribution comes from Artificial Intelligence, which not only makes it possible to anonymise CVs by focusing on skills but also to automate the screening of CVs and assess job matching, i.e. the match between what the candidate has to offer and what the company is looking for. Let us look at all aspects in detail.

Assessing skills with anonymous CVs

.An anonymous or anonymised CV, as we have mentioned, is a CV that conceals personal information that can negatively influence selection without enhancing diversity. This is for all the reasons we have discussed so far related to the conscious and unconscious prejudices that each person may have.

By obscuring specific data, on the other hand, HR can focus on the skills and professional experience that the candidate has had up to that moment, trying to understand if this is what the company is looking for and decide which aspects to address in an initial phone call or cognitive interview.

All this is possible thanks to Artificial Intelligence: with Inda, for example, it is possible, using the Anonymous Resume/CV system, to anonymize any digital document, be it a CV, a cover letter or a portfolio. And this is regardless of the format:, starting from the original version of the document, with Inda, it is possible to create an anonymous copy in real-time, essentially the same, but without the sensitive information.

Automating CV screening

Artificial Intelligence can then improve application times and transfer large amounts of data. Thanks to Inda’s Information Extraction and Résumé Parsing techniques, it is possible to speed up the extraction of information and automate the filling in of application forms by storing data in the database. All this facilitates both the recruiter and the candidate.

On the recruiter’s side, there is certainly a considerable saving of time, allowing applications to be handled more quickly and not to miss out on people potentially suited to the profile being sought. In addition, data mining makes it possible to enrich and update the database by really gathering all the most important information and highlighting the most ‘diverse’ candidates.

It also benefits candidates: automation at the application stage improves the candidate experience and reduces the drop-out rate during the delicate application phase.

As we know, it only takes one detail not working or making this process particularly complex for a person to abandon the site or platform to apply. This goes in the opposite direction to inclusion: only those who are perhaps ‘geeky’ or patient manage to complete a complicated application while most people leave.

Furthermore, Artificial Intelligence can help include candidates with disabilities: technology can be simplified to facilitate their access, as well as writing job advertisements and designing an experience that meets their needs.

Analysing job matching for more accurate selections

Artificial Intelligence also has another critical task: facilitating the matching between the skills required and those provided by a candidate. In a word, matching can occur both before an advertisement is posted and afterwards.

Among Inda’s functionalities, there is the possibility of doing a sort of preliminary matching. Before publishing the advertisement, it is checked whether there is a match between what is sought and what you already have, i.e. between the profiles already in the database. Mind you, they can be people who were previously recruited but did not make it to the recruitment or people who already work in the company. Perhaps some people are interested in a particular position or who, over the years, have acquired new skills: why not consider them? This is undoubtedly an essential step from the inclusion and welcoming diversity perspective.

Then, there is the job matching phase: in this case, after the advertisement has been published, the match between the candidates and the position sought is verified.
How does this happen? In the case of Inda, semantic matching is carried out on job title, experience level, studies conducted, skills and so on. And thanks to the Evidence system, it is possible to check how compatible the candidate is for that position or not.

All this saves hiring time but also goes towards candidate satisfaction: the recruited person can play all his cards because his profile matches what is sought.

Can artificial intelligence be neutral and objective?

To think that Artificial Intelligence in recruiting can solve all prejudices to promote diversity and inclusion in the workplace is undoubtedly an optimistic vision, but some aspects must be considered.

AI only goes so far so it can guarantee, for what is required of it and for what is its ‘space’, a selection that can be as objective as possible.

But let’s remember that recruiting, as it should be, is entrusted to the people in charge of human resources, so it is up to them to know how to customise the tools they use and make the most of them. Let’s take an example: if I manage through blind recruiting to make an objective selection while hiding sensitive data, the performance of the selection will then depend on how I behave during the interview and how I carry out the selection.

Another aspect to consider is that artificial Intelligence for recruiting is only one part of having – and keeping – diversity in the company.

Furthermore, according to a report published by Russell Reynold, only 35% of Chief Digital Officers take diversity data into account. Therefore, if an organisation does not keep track of it, it is challenging to check whether it is moving in that direction and activating policies later.
This is why AI must be put in a much broader context and not only linked to recruitment altogether.

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Everything we have just said goes toward creating a more inclusive work environment by attracting people with disabilities, for example, people from different geographical origins, cultural backgrounds and so on.
This can lead to reshaping the way of thinking of both employers and employees themselves, creating a changing mindset ready to innovate. And also influencing a corporate culture that aims at diversity and inclusion in a stable way, thus creating long-term change.

Aiming at diversity and inclusion does not mean ‘striving’ to implement policies in this sense but making these aspects structural so that they permeate the work environment. In this, Artificial Intelligence can make an enormous contribution, as we have seen, provided that it is not thought of as the only way but perhaps one of the starting points.