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Ensuring Explainability in HR AI Systems - Transparent Decisions

Lesson Content

Putting AI Ethics into Practice at SAP

Learn about the importance of transparency and explainability in HR AI systems with SAP's AI ethics governance. Discover how SAP Fieldglass's resume assessment system ensures fair and objective hiring processes.<br><br># This description was auto-generated #

SAP_MOOC_aie2_Lesson_5_TRANSP_Video.mp4

Hello, my name is Khawla Mallat and I'm a member of the Corporate Sustainability Team, where I'm contributing to SAP's AI ethics governance. I present to you the lesson Ensuring Explainability in HR AI Systems Transparent Decisions. We will start by first introducing the HR use case we will be dealing with in this lesson. The selected use case is provided by SAP Fieldglass, and it consists of a resume assessment system that evaluates candidates' resumes according to how well they match the job description, focusing on skills, relevant work, and industry experience. And that's in order to assist recruiters and hiring managers in optimizing their search for the ideal candidate. The benefits of using this AI-driven approach are many. It saves time and resources, allowing recruitment teams to efficiently manage large volume of applications. It also can unlock hidden talent by ensuring that qualified candidates who may have been overlooked are given due consideration. Also, this use case supports more objective hiring processes by reducing human bias and fostering data-driven recommendations. As with any AI use case at SAP, FeePlus's resume assessment undermined our AI ethics impact assessment process, which takes into account various aspects to determine the risk level of a use case. Let me walk you through these aspects one by one. First, this use case involves processing resumes, which naturally include personal data and often even sensitive personal information. However, it's important to note that in this instance, the use case does not involve any automated decision making. The AI system is used to recommend the most suitable candidates for a given job description, but the final decision is always made the hiring manager. Now moving to the fourth aspect, the potential of this use case to negatively impact individuals is significant. Even though the AI doesn't make the final decision, its role in the hiring process means that any errors or biases could directly affect someone's employment opportunities. Lastly, because this is an HR-related application, it falls within a high-risk sector due to its direct impact on people livelihoods. All of these considerations combined led to the high-risk classification of this use case. After a thorough review, the AI Ethics Steering Committee ultimately approved the resume assessment use case. However, they highlighted the critical importance of transparency and explainability, as well as the need for careful bias assessment and mitigation within the AI system. We'll now look at the efforts that have been put in place to make the Reservoir Assessment process more transparent and explainable. In the next lesson though, we'll cover how bias was assessed and mitigated. Transparency in this context is meant to ensure that users are aware that they are interacting with an AI system, and have a clear understanding of how the underlying algorithm works. To achieve this, several measures have been implemented. First, an AI disclaimer would pop to inform the user that the resume assessment feature uses AI technology. Then an about dialogue has been included within the application to provide a comprehensive description of how the resume assessment functions, including an overview of the different possible scores a candidate could receive based on their skills and experience. Additionally, an info note is provided to inform users that assessment is only based on matching the candidate's skills with the job requirements. The product documentation available in SAP Help also offers more detailed information on how the AI system operates and how the different scores are computed. This approach ensures that users are fully informed and can trust the process behind the AI-driven resume assessment. Now, when it comes to explainability, the resume assessment system should be equipped to provide the necessary information to answer the question, why is Mary Jones identified as a great match for this job? Among the efforts to achieve explainability, the application has been designed to show Mary's skills matching scores with the job requirements and the rate by which her experience aligns with the requirements. It is also possible to inspect the specific skills and experience information that contributed to these matching scores with the appropriate labels. This level of detail helps users not only to trust the AI system recommendations, but also to clearly see why a candidate might be an excellent fit for the job. As we conclude this lesson, let's recap what we've covered. According to SAP's AI Use-Case Impact Assessment, the Resume Assessment and Skill Matching Use Case in SAP FeePlus was classified as high-risk. We examined the key areas emphasized by the AI Ethics Steering Committee, particularly the importance of transparency and explainability. And we reviewed the measures implemented to achieve these goals. These efforts are crucial for building trust in the system and ensuring it operates responsibly. With that, we have reached the end of our lesson. Thank you and goodbye.