3 Strategies for Adopting Secure AI-Augmented Assessment Systems

April 9, 2020 Jillian Slyfield

First Published on LinkedIn


Talent acquisition has seen a surge of artificial intelligence and machine learning products in recent years. A third of organizations have already adopted AI/ML-based tools to aid with recruiting, assessing and hiring job applicants, one Deloitte survey found.

 But while AI and machine learning-based selection tools offer numerous advantages, including improved prediction, efficiency in decision-making and ease in handling large volumes of data, employers adopting these technologies face challenges in ensuring that such tools are compliant with legal and professional guidelines. A human-centered approach to using AI and machine learning in the management of human capital is crucial to protecting the privacy, autonomy and dignity of applicants.

Here are three strategies to create secure AI-augmented assessments systems that put people at their center.

Engage in Innovation with Intent

The end goal when designing and using data-driven talent assessment software is to preserve and protect human dignity and integrity.

Purposeful innovation means driving HR technologies forward in a way that solves a problem and allows HR to inclusively add value. It also means incorporating science, theory and a bit of common sense along with AI and technology innovations to ensure new solutions are implemented in a way that also delivers on ethical and legal considerations.

The end goal when designing and using data-driven talent assessment software is to preserve and protect human dignity and integrity. The systems we put in place for collecting and assessing data from talent assessments must uphold these critical values.

 This is especially true when using AI-enabled, video-based assessment software. Most data privacy laws recognize that the candidate has ownership over their own data, and this is solidified when that data is coupled with the candidate’s image. Upholding human dignity means respecting and protecting the right to privacy, and it’s crucial for your organization to protect the image and information a candidate allows you to collect, store and utilize.

Blend Data Science with Human Considerations

The design process for talent assessment has to blend data science with human considerations. Data scientists have technical expertise but have less knowledge of the legal and societal repercussions of their work. Psychologists understand the societal ramifications of data collection but may not understand the intricacies of the technology.

Merging these points of view at the beginning of the design process produces secure, all-encompassing risk-mitigation solutions and foregrounds the need to maintain robust, secure data storage that protects stakeholders from improper uses of their data.

The key to data security is remembering what’s at its heart: people. Upholding human autonomy drives data security as well as the laws being written to protect it. Security measures must be human-centric — not just in intent, but also in design and practice. Data collected from talent assessments and video interviews has to be overseen by trained, dedicated personnel.

Prioritize Data Security

Technology that collects or processes candidate data should not be susceptible to malicious use.

The best way to ensure an ethical use of data is to employ a technically robust data system augmented by human oversight. Any systems that collect or process candidate data must be secure against potential breaches. Furthermore, data security technology must be subject to constant tests and frequent updates.

High-level access to personal data should only be granted to a small group of people with a proven need, and records should be kept of who has access to which parts of a given AI system.

Technology that collects or processes candidate data should not be susceptible to malicious use. To protect data collected from AI-augmented assessments and recorded interviews, only authorized personnel should be granted access. This mitigates the likelihood of intrusion and data breaches. Utilizing human safeguards adds a second layer of accountability and security, further minimizing the chances of data breaches or unauthorized access.

Selecting the right assessment vendor is key to protecting data from malicious use. Aon mitigates risk through the use of a trusted local service vendor and dedicated IT personnel. A good assessment vendor will also provide data integration services so you can securely transfer data from the assessment software to a protected storage location, guarded both by technology and human oversight.

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

Jillian Slyfield

Jillian Slyfield serves as Aon’s Digital Economy Practice Leader. In this role, she addresses digital disruption of traditional industries and the on-demand economy. Her focus areas are Mobility as a Service, The Future of Work and New Economy Digital Risk. Innovation, a sense of urgency, and our global Aon platform are hallmarks of her Digital Economy Practice. Through this Practice, Jillian ensures Aon’s market leadership, technology platforms and deep analytics capabilities are harnessed for our clients. Jillian is engaged regularly as a public speaker on topics such as insuretech, mobility as a service, and the future of work. She proudly serves on Aon’s Diversity and Inclusion Board and serves as an advisor to emerging tech businesses.

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