AI is often seen as either a new source of hidden bias or a shortcut to fairer outcomes. The reality is that adoption, bias mitigation, and governance all play a key role in whether or not AI works to improve inclusion outcomes. This session examines where AI is actually being used with inclusion in mind, where workers and HR professionals diverge sharply in how much they trust AI versus human judgment to be fair, and how often organizations' AI policies are silent on inclusion even when a policy exists. Additionally, the session explores which mitigation approaches organizations report using — and which ones respondents say would actually build their confidence — including a candid account of where the evidence points to real progress and where it points to unresolved risk.
Adoption, Bias, and Governance: What Worker and HR Data Reveal About AI's Promise and Peril for Workplace Inclusion
Session Type: Breakout Session
Session Tracks: AI Impacts & Opportunities for Inclusion
Learning Outcome 1: Distinguish where AI is being adopted with explicit inclusion intent versus incidental effect, and identify which of these categories best describes their own organization's current AI use.
Learning Outcome 2: Compare worker and HR professional perspectives on AI and bias — including where organizations' AI governance policies do and don't address inclusion — to identify blind spots between stated policy and lived experience.
Learning Outcome 3: Evaluate the bias-mitigation approaches most associated with employee confidence and develop a plan for closing the gap between what their organization currently does and what would build trust.
- Tuesday, Nov 1710:30 AM - 11:30 AM CST
Speakers
VP, Thought Leadership, SHRM