X0PA embedded AI Verify into its ATS solution to shortlist candidates for jobs
To X0PA, committing to responsible AI practices and ensuring that its AI model is free from biases is its top priority. X0PA employs a gradient boosting model to help its clients predict shortlisted candidates for posted job positions.
X0PA was one of the trusted partners who participated in the alpha testing of AI Verify in 2022, and contributed to the development of AI Verify Minimum Viable Product. The company invested time upfront of about 2 weeks to understand AI Verify’s offerings, input requirements, and outputs, and did not encounter major challenges in embedding AI Verify into its AI solution. They established a data preparation pipeline to generate AI Verify’s standard input format, and to be able to facilitate bias checks at any time.
Using AI Verify to conduct fairness checks on ATS solution
Through the process of testing and using AI Verify, X0PA gained insights on the importance of using specific fairness metrics to assess AI model performance, especially in tasks like candidate selection. These metrics allowed the company to identify areas where bias might occur, provide quantifiable data to address these issues and guide feature selection in model training to prevent such bias.
This is particularly important as X0PA is in the business of hiring, and thus its AI solution impacts decisions which affects livelihoods. Its client organisations need to trust X0PA’s AI systems make the right decisions and have no biases.
X0PA found AI Verify to be user-friendly, well-documented, and with an impressive reporting system. Its standardised format made it both easy for users to understand and is highly informative. Hence, X0PA continues to use AI Verify even today, especially to conduct fairness checks on its AI model.
Based on its positive experience with AI Verify, X0PA highly recommends other organisations to use AI Verify. According to X0PA, AI Verify provides a robust framework for assessing and improving the fairness of AI systems. It offers clear and actionable insights that organisations can use to address bias, which is essential for responsible AI deployment.
Your organisation’s background – Could you briefly share your organisation’s background (e.g. sector, goods/services offered, customers), AI solution(s) that has/have been developed/used/deployed in your organisation, and what it is used for (e.g. product recommendation, improving operation efficiency)?
Your AI Verify use case – Could you share the AI model and use case that was tested with AI Verify? Which version of AI Verify did you use?
Your experience with AI Verify – Could you share your journey in using AI Verify? For example, preparation work for the testing, any challenges faced, and how were they overcome? How did you find the testing process? Did it take long to complete the testing?
Your key learnings and insights – Could you share key learnings and insights from the testing process? For example, 2 to 3 key learnings from the testing process? Any actions you have taken after using AI Verify?