How HR Can Help Solve the Hiring Discrimination Crisis on a Budget

Lovepreet Dhaliwal January 22, 2021

Hiring discrimination is not an uncommon corporate issue. Sixty-one percent of employees reported their experiences in the recent Glassdoor survey on witnessing discrimination in the workplaces.

The stirring issue has grown more complex due to artificial intelligence (AI). The algorithms of this tool are unexplainable to non-technical business users. Their functions may go wrong, perpetuating discrimination instead of solving it. Not only this, but poorly evaluated algorithms can twist results in unconventional hiring scenarios without even detecting it.

This is where the role of HR technology comes into play. HR managers, with the help of some tools, can play a strategic role in minimizing biases and discrimination in the hiring process.

Here are some insights that can help HR managers address the issue of the hiring discrimination crisis.

How to Solve Hiring Discrimination Crisis

? Localize Programmed Recruiting System to Address Hiring Discrimination Concerns

A Cornell University Paper highlighted the significance of localizing different recruitment software. The paper emphasized putting local recruitment software to use for the organization’s hiring needs.

Moreover, it talks about how significant the risk of discrimination and biases in companies is. Localization is vital because data protection regulations may vary from one state to another, and so do anti-discrimination and equality laws.

Programmed hiring systems work with standardizing management strategies, potentially on an international scale. A thorough interrogation in the value-laden hiring assumptions that are embedded in their design is important. Plus, it is essential to see how local companies define the phenomenon of bias.

? Assess testing Procedure of Recruitment Software

With a complex system such as AI-based recruiting software, there is always a certain level of black boxing. Put simply; the HR manager can see and leverage some external functionalities without understanding the internal mechanism of an organization. This can heighten the risk of discrimination in the hiring process.

The Author Karen Levy from Cornell University in his paper titled “Mitigating Biases in Algorithmic Hiring” states that the technical working of anti-discrimination hiring tools does not always go through sufficient scrutiny. That is why organizations need to watch for areas like forecasting goals and data collection when starting the recruitment process. It will not only improve the steps of the hiring process but also enhance the candidate experience.

Moreover, HR professionals must ask software vendors to provide detailed information about the validity of hiring tools. This information may include;

? What kind of data does software use?

? How does the software perform when segregating a diverse group of candidates?

They should also ask about the limitations of the tools. Does it work for testing particular roles of the job? Some HR professionals have no clue as to how the tool performs on applicants with disabilities. Their resume parser software does not extract information the way it should.

All of them are essential questions, especially when you know how anti-discrimination laws can affect companies.

? Establish a Formal Audit Framework for AI-based Hiring

Considering the rapid increase of automated recruiting and the proliferation of AI tools, it is essential to study the internal processes, inflowing data, organizational impact, and output of technology systematically. This typically calls for a structured framework that can help HR managers audit everything. The framework can also play a role in eliminating discrimination in hiring processes.

Human Resource experts from some non-profit organizations and Google have presented an end-to-end audit framework. It not only explains internal algorithmic for auditing but also outlines an instrumental framework for IT professionals and HR practitioners. The framework covers five different stages, including scoping, mapping, collecting artifacts, testing, and reflecting. It basically delves into the scope, roles, and results of the AI algorithm in an organization.

Each stage of this framework has a set of documents that form a comprehensive audit report. It helps HR professionals draw on the principles and values of the organization to evaluate the decisions made during the whole process. This audit framework aims to close all accountability gaps in deploying large-scale AI systems.

? Acknowledge Data Attributes to Reduce Biases

Companies and HR managers need to be vigilant of data attributes that many vendors may use. Data attributes such as gender and race can contribute to the hiring discrimination crisis. HR professionals must pay attention to these sensitive attributes to avert the hiring discrimination crisis proactively.

However, the law mandates some industries such as healthcare to gather this data. In contrast, other industries do not have the authority to collect this information.

So what should firms do? Should they ignore this and let blind hiring strategies play their role?

Some industries believe that feeding data attributes into hiring systems can make them effective to combat hiring discrimination. Keep in mind that if companies are unable to collect sensitive attribute data, then they will never be able to implement suggested techniques to mitigate or remove bias in the machine learning model.

That is the reason it is vital for HR and IT practitioners, to help their companies promote technical needs and policy goals that acknowledge data attributes. They must introduce a robust dataset that supports anti-bias technology.

Bottom Line

The business landscape nowadays comprises a diverse workforce. And it is quite easy to believe that workplace discrimination is no longer a part of the corporate culture. However, the reality is different. Around 84,254 workplace discrimination charges were filed against the different organizations in 2019. This number is enough to reflect the reality of the hiring culture in the companies.

With increasing discrimination claims, HR managers need to be smart, proactive, and practical with their strategies for eliminating biases in the workplace. They can use HR technology and tools for localizing automated systems, onboarding employees, processing payroll, and establishing formal audit frameworks to combat hiring discrimination in a company’s culture.

Thus, the given strategies are effective in incorporating smart practices into the company’s hiring culture and can help HR managers reduce biases in hiring processes.

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