Why Transparency Is Essential for AI-Augmented Talent Assessments

March 24, 2020 Ernie Paskey

First Published on LinkedIn


The state of Illinois’s recent law governing the use of AI-augmented software in hiring processes was implemented to protect candidates’ data privacy and security. A key to making that happen? Being transparent with candidates and employees regarding how we collect and use their data.

AI-augmented talent assessments collect data on each candidate’s abilities, motivations and values. Anytime we collect and store personal data and information, transparency is critical. We have a responsibility to make it easy to understand and explain the processes and technology we use to make decisions about hiring — and why.

Here are three reasons transparency needs to be a priority when you use AI-augmented talent assessments.

Protecting Candidates — And Your Organization

When using AI-augmented talent assessments, transparency refers to sharing what data will be collected and assessed, the basis for assessment and its relation to the job, and how data will be stored and secured.

Even when you don’t have a legal obligation to provide the answers to these questions to the people whose data you are managing, you still have an ethical one. While there are currently no federal laws governing data use in the U.S., you should still actively seek consent from people whose data you collect. Make sure candidates understand:

●      What data you need. This refers to what personal data you’re collecting from candidates, as well as what data you’re assessing.

●      How it will be used. Organizations need to be able to clearly demonstrate how the assessed data relates to the job in question and how it influences the decision to hire or not hire.

●      How it’s secured. Candidates should know how their data is being stored and secured.

When you are transparent with candidates upfront regarding what data you are collecting and how it will be used and stored, you are also protecting your organization from claims of misuse of data. Your transparent process helps provide legal defensibility.

Earning the Trust of Your Stakeholders

In essence, you should take a “glass box” (rather than a “black box”) approach to data use.

Another side of transparency is making clear to candidates and employees how data will be used to make decisions regarding hiring and mobility. Designing and executing these processes in a transparent way is critical to earning their trust.

In essence, you should take a “glass box” (rather than a “black box”) approach to data use.

A black-box approach leaves candidates in the dark as to how the data collected from talent assessments will be used. The glass-box approach, on the other hand, keeps candidates informed at every step. Candidates are told exactly how their data will be used to determine who is selected for the position. There are no surprises or doubts as to how they’re being assessed — it’s as though they’re watching the process as it unfolds.

Preventing the Misuse of Data

Candidates should not feel misrepresented by their data or be concerned about breaches in storage. Take time to review the capabilities of your processes and vendors regularly.

The design and storage processes for AI-augmented talent assessment software should be transparent to everyone whose data is collected. A lack of transparency can contribute to the misuse of data, and these breaches in data use can erode trust in the process, cause damage to the organization’s reputation and lead to legal action.

Candidates should not feel misrepresented by their data or be concerned about breaches in storage. Take time to review the capabilities of your processes and vendors regularly.

Transparency is the key to protecting the data you collect and assess during AI-augmented talent assessments. Openness and honesty are essential to preserving your stakeholders’ dignity. Candidates and employees have the right to control how their data will be collected, used and stored — but they cannot consent until they’ve been informed. Respect your people: practice transparency.

Read our handbook, Emerging Regulations in the Age of AI, to learn how your organization can proactively establish processes to get the most out of AI in talent assessment while staying on the right side of emerging regulations and ethical considerations.

About the Author

Ernie Paskey

Ernie is the North America Assessment Practice Leader and leads talent strategy for Aon’s assessment and selection services. He has extensive experience in both the public and private sectors and is an acknowledged thought leader in assessment and selection practices. He helps clients by providing effective solutions related to selection, employee engagement, succession planning, and leadership development.

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