Addressing valid concerns in the HR industry about AI, PredictiveHire has released an ethical framework to encourage transparency in the sector
PredictiveHire, an Australian technology company that has pioneered transparent AI-assisted hiring solutions, today announced the global release of its Fair AI for Recruitment (FAIR™) framework to educate HR executives in assessing AI technology for use in their organisations, as well as act as spark conversations for AI developers in the space: https://www.predictivehire.com/fair-ai-recruitment-framework/
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The framework has been released to begin conversations around transparency in HR technology against an explosion of AI solutions in the sector, with many using algorithms that operate in a ‘black box’. The absence of any form of accreditation of vendors, and the fact that regulation is light years behind tech innovation, has meant a lack of collaboration among vendors to champion AI ethics in the sector, something PredictiveHire hopes to help change.
The Fair AI for Recruitment (FAIR™) framework :
– Focuses on establishing a data-driven approach to fairness that provides an objective pathway for evaluating, challenging and enhancing fairness considerations.
– Includes a set of measures and guidelines to implement and maintain fairness in AI based candidate selection tools.
-For hiring managers and organisations, it provides an assurance as well as a template to query fairness related metrics of AI recruitment tools.
-For candidates, FAIR™ ensures that they are using a system built with fairness as a key performance metric.
In launching the framework, PredictiveHire CEO Barb Hyman said: “We have created a framework that we hope can be used as inspiration to ensure that AI is being used to build inclusive teams – something humans are not capable of doing on their own because we cannot subvert our biases.”
“Our mission is to help HR leaders make bias interruption more than rhetoric, which is why we also published this guide to Making inclusion an HR priority, not a PR one“.
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