<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/270b578484254838a27399f4dd129891&quot; frameborder=&quot;0&quot; width=&quot;1916&quot; height=&quot;1437&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1437</height><width>1916</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1437</thumbnail_height><thumbnail_width>1916</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/270b578484254838a27399f4dd129891-86f75205630db4e2.gif</thumbnail_url><duration>528.343</duration><title>AI Workflow Redesign for Fair Recruiting</title><description>This Loom explains an AI workflow redesign for recruitment at FutureHire focused on cutting recruiter admin while addressing fairness and adoption. It redesigns three workflows, job ad drafting, interview summarization, and hiring manager updates, with the principle that the AI drafts but never screens, ranks, or selects candidates, keeping recruiters in full control. The job ad tool includes an inclusivity check that highlights and changes age coded and gendered language before posting, and interview summarization strips out protected attributes like age to provide evidence-only notes without making hire or reject decisions. Across 24 recruiters, the workflows saved about 60 percent of admin time, reclaiming roughly 1.7 hours per recruiter per week, and the project tracked these benefits.</description></oembed>