How Artificial Intelligence Can Reduce Bias in Public Sector Hiring

October 30, 2019 Michael Heil

First Published on LinkedIn


Historically, public sector hiring practices have relied on a merit system that, in principle, values fairness and consistency. But over time, these practices have become cumbersome, leading to the unintended consequence of candidates feeling like they are treated unfairly or are dissatisfied with the hiring process.

In a recent poll by Aon’s Assessment Solutions, nearly 20% of respondents recognized the potential of AI to mitigate human bias. The public sector, too, is recognizing the power AI has to increase fairness and equity in hiring practices. It is vital for the public workforce to mirror the diversity of the people they serve, and AI-driven assessments can help make that imperative a reality.

AI can support the public sector’s diversity and inclusion goals through the automation of data scoring. When applied to the public sector, AI-driven assessments can significantly decrease the likelihood of bias creeping into the candidate selection process.

Here are three ways government agencies can leverage AI-powered assessments to ensure fair and equitable hiring practices.

Offering Greater Insight Into Data You Already Have

When integrating AI into their assessment processes, most companies face the need for data sourcing as an extra step in the AI conversion process. But this is not the case for the public sector, which already possesses large amounts of workforce data. This existing data can be used by AI and applied towards public sector recruiting.

Sophisticated AI-powered assessment solutions are driving the changes needed to transform talent selection and enable more diverse recruiting. By using machine intelligence to compare candidates’ job specific profiles and behavior competencies with the role specifications and organizational demands, public sector employers can leverage workforce data to consider a much bigger pool of talent and make more objective decisions.

The richness of data both on the workforce and on candidates creates a perfect opportunity for public sector employers to benefit from AI’s ability to create hiring processes that are reliable, efficient and fair.

Ensuring Consistency Across Teams of Recruiters

Combating bias in hiring is a moral and legal imperative. AI can help deliver a consistent selection process across the board. For public sector employers, AI algorithms can be trained to identify job relevant personality- or competency-based constructs with minimal bias. Those constructs can then be implemented consistently across all candidates.

Transparent and appropriate use of AI in hiring can create an assurance that selections will be made according to the specifications you’ve laid out based on job-relevant data.

Employees can go through rigorous training, but humans will still bring bias and inconsistencies into their decisions. By looking for a narrow list of traits in a candidate, such as attending certain universities or past employment at particular firms, recruiters often base their decisions on biases and perceptions of fit. There are also a number of other factors that can lead to errors or inconsistencies: overwork, lack of sleep, miscommunications, and much more.

When you use AI in the selection process, you can help remove those biases and extraneous factors that can occur. Transparent and appropriate use of AI in hiring can create an assurance that selections will be made according to the specifications you’ve laid out based on job-relevant data, helping the public sector move forward in cultivating diversity and ensuring fairness.

Allowing Transparency Into the Hiring Process

This leads to another key issue in public sector hiring: transparency. Aon’s research suggests that the so-called “black box” approach to AI — one that relies on using unclear variables to make assessment decisions — can lead candidates to react unfavorably both to AI itself and to the employers that rely on it. This reaction can taint impressions of a potential employer even among candidates who are offered a job.

With a “glass box” approach, employers can identify exactly what variables the AI scores and how it uses these scores to arrive at a decision.

Public sector employers that want to harness the power of AI in talent assessment must help candidates feel more comfortable with AI in the hiring process, and a key step is a “glass box” approach that emphasizes transparency. With a “glass box” approach, employers can identify exactly what variables the AI scores and how it uses these scores to arrive at a decision.

This transparency shows candidates you have nothing to hide and guards against bias. If bias is introduced into the process, transparent use of AI can help employers intervene more easily to remove it. This helps organizations maintain legal defensibility. Government agencies that take this approach to improve role and organizational fit can benefit from using AI in recruitment while at the same time avoid alienating potential talent.

Download our white paper, Building the Government Workforce of the Future to learn more about how innovative assessment programs can help public sector employers attract and retain top talent now and into the future.


 

About the Author

Michael Heil

Dr. Michael Heil is an Associate Partner with Aon and serves as Project Director for the development, validation, and delivery of both entry level and promotion exams for several federal and local law enforcement entities. In his 20+ years of industrial-organizational psychology experience his primary research activities include selection and validation research, job analysis, test development, competency modeling, program evaluation, and human performance research. He has presented research at national and international conferences on these and other topics, such as organizational commitment, test development and assessment. He is co-editor of a book on Air Traffic Controller Selection.

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