<?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/34b3b464e62e498d974f15ad48c820c7&quot; frameborder=&quot;0&quot; width=&quot;1730&quot; height=&quot;1297&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1297</height><width>1730</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1297</thumbnail_height><thumbnail_width>1730</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/34b3b464e62e498d974f15ad48c820c7-1c19f150e4739796.gif</thumbnail_url><duration>461.101</duration><title>Ensuring Safe AI Communication in Healthcare 🤖</title><description>In this video, I discuss the AI care standard for patient communication and how we can make AI safe for direct interactions with patients. I emphasize the importance of using high-quality training data from peer-reviewed medical journals rather than unreliable internet sources. I encourage AI committees and health system vendors to utilize our evaluation framework available at aicarrastander.com, which includes a series of questions to assess AI tools effectively. By following this framework, you can ensure that your AI systems are ready for deployment or identify areas needing improvement. I urge you to take action by evaluating your AI systems using our tool and sharing the results with your team.</description></oembed>