{"version":"1.0","provider_name":"Center for Democracy and Technology","provider_url":"https:\/\/cdt.org","author_name":"Tim Hoagland","author_url":"https:\/\/cdt.org\/author\/thoagland\/","title":"Report \u2013\u00a0Improving Governance Outcomes Through AI Documentation: Bridging Theory and Practice\u00a0","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"ubZTPh4KEe\"><a href=\"https:\/\/cdt.org\/insights\/report-improving-governance-outcomes-through-ai-documentation-bridging-theory-and-practice\/\">Report \u2013\u00a0Improving Governance Outcomes Through AI Documentation: Bridging Theory and Practice\u00a0<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/cdt.org\/insights\/report-improving-governance-outcomes-through-ai-documentation-bridging-theory-and-practice\/embed\/#?secret=ubZTPh4KEe\" width=\"600\" height=\"338\" title=\"&#8220;Report \u2013\u00a0Improving Governance Outcomes Through AI Documentation: Bridging Theory and Practice\u00a0&#8221; &#8212; Center for Democracy and Technology\" data-secret=\"ubZTPh4KEe\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script type=\"text\/javascript\">\n\/* <![CDATA[ *\/\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/* ]]> *\/\n<\/script>\n","thumbnail_url":"https:\/\/cdt.org\/wp-content\/uploads\/2024\/09\/2024-09-24-CDT-AI-Gov-Lab-Foundational-Models-Documentation-report-social-media-191x1-3000x.png","thumbnail_width":3000,"thumbnail_height":1571,"description":"Executive Summary AI documentation is a foundational tool for governing AI systems, via both stakeholders within and outside AI organizations. It offers a range of stakeholders insight into how AI systems are developed, how they function, and what risks they may pose. For example, it might help internal model development, governance, compliance, and quality assurance [&hellip;]"}