HR’s Wake Up Call: Auditing AI Tools After the Workday Bias Case with Katee & Jackye - Episode 155

🎙️ Welcome to The Inclusive AF Podcast! In this must-listen episode, hosts Jackye Clayton and Katee Van Horn dive into one of the hottest and most pressing topics in HR: AI Bias in Recruiting—especially focusing on the landmark Mobley vs. Workday lawsuit. With over 1.1 BILLION applications potentially impacted, what does this mean for your organization and your hiring practices? We break down: - The real risks of bias in AI-powered ATS systems like Workday🧐 - What the Workday lawsuit means for companies (hint: it’s not just about tech, it’s about accountability!) - The practical steps every HR professional and recruiter needs to take NOW to audit and protect their hiring funnel - Why relying solely on AI isn’t enough and how YOU hold the responsibility - The right questions to ask your vendors to avoid being at the center of the next big discrimination case Plus, we keep it real, weaving in candid stories from our careers, a few laughs about 90s Sun-In hair disasters, and our hot takes on the future of compliance. Whether you're in HR, recruiting, or leadership, you can't afford to miss these insights on protecting your company, candidates, and reputation in the age of AI. 👉 Don’t forget to subscribe, like, and share! And keep your eyes peeled for our upcoming Inclusive AF swag store—announced soon! #AIInRecruiting #HRTech #WorkdayLawsuit #InclusiveAF #DiversityHiring #AIBias #HRCompliance #Recruiting #DEI #HumanResources #ATS #WorkplaceEquity #AIAccountability Listen NOW and get ahead of what's coming for HR and recruiting leaders everywhere! 💪 Got questions, comments, or want to share your own story? Drop a comment below—we LOVE hearing from our Inclusive AF family! ATS Vendor Evaluation Questions – Bias Detection & DEIB Alignment Bias Detection & Mitigation - How does your system detect or flag potential bias in candidate screening or selection? - Do you conduct regular audits (internal or third-party) to assess disparate impact in hiring outcomes? - Can you share the results of your most recent bias audit or fairness analysis? - How do you monitor for demographic drop-off or funnel imbalances (e.g., by race, gender, age, disability)? - Do you offer real-time alerts or bias flags during recruiter or hiring manager interactions? Transparency & Explainability - Can your algorithmic decisioning or scoring be explained to end users (e.g., recruiters, candidates)? - Do you provide visibility into how candidate matches, rankings, or scores are calculated? - How can recruiters override or contest algorithmic suggestions? Anonymity & Data Privacy - Does your platform offer blind screening (e.g., redacting names, photos, graduation dates)? - How do you protect candidate PII (personally identifiable information) throughout the hiring process? - Can recruiters be restricted from seeing demographic details to reduce unconscious bias? Analytics & Reporting - What diversity analytics or dashboards do you offer for tracking pipeline health and equity? - Can we track pass-through rates by demographic category across stages (e.g., applied → screened → hired)? - Do you offer any benchmarking to compare our data against industry or peer norms? Compliance & Regulation - How do you support compliance with local and global AI/HR laws (e.g., EEOC guidance, NYC Local Law 144, EU AI Act)? - Do you provide the required disclosures and opt-outs for jurisdictions with AI bias laws? - How do you stay current on regulatory changes impacting algorithmic hiring tools? Commitment to DEIB - How does your tool support our DEIB goals beyond just compliance (e.g., inclusive language checkers, diverse sourcing tools)? - Do you work with DEIB consultants, advisory boards, or audit partners to review your tech? - What ongoing improvements are planned to ensure fairness and accessibility in your platform?