{"id":41628,"date":"2025-09-25T01:48:01","date_gmt":"2025-09-24T23:48:01","guid":{"rendered":"https:\/\/2b-advice.com\/glossary\/modellkarte\/"},"modified":"2025-09-25T19:47:02","modified_gmt":"2025-09-25T17:47:02","slug":"model-map","status":"publish","type":"glossary","link":"https:\/\/2b-advice.com\/en\/glossary\/modellkarte\/","title":{"rendered":"Model map"},"content":{"rendered":"<h1>Model Card<\/h1>\n<h2>Definition<\/h2>\n<p>Model cards are structured documents that provide key information about an AI model, similar to a nutrition label. They describe the purpose, area of application, performance values and limits of a model in order to create transparency and trust. In AI governance, model cards serve as binding proof of design, testing procedures and responsible use of a model. They help developers, business leaders and regulators to understand the strengths and weaknesses of a model and assess risks. A model map summarizes data provenance, performance measurements and known risks to promote accountability in development and document compliance with the EU AI Regulation.<\/p>\n<h2>Why is a model map important?<\/h2>\n<ul>\n<li>Promotes transparency and trust through clear documentation of purpose, data and performance.<\/li>\n<li>Supports compliance with legal requirements (e.g. EU AI Regulation) and internal guidelines.<\/li>\n<li>Helps developers and stakeholders to recognize and address risks and bias.<\/li>\n<\/ul>\n<h2>Components of a model map<\/h2>\n<ul>\n<li><strong>Name and version:<\/strong> Clearly identifies the model.<\/li>\n<li><strong>Purpose and use cases:<\/strong> Describes what the model is intended for and in which situations it may be used.<\/li>\n<li><strong>Training data and performance metrics:<\/strong> Explains what data was used and how well the model performs.<\/li>\n<li><strong>Restrictions and risks:<\/strong> Indicates known weaknesses, bias or situations in which the model is unreliable.<\/li>\n<\/ul>\n<h2>How model maps support AI governance<\/h2>\n<ul>\n<li>Ensure that each model is documented in a traceable manner.<\/li>\n<li>Facilitate audits and compliance checks.<\/li>\n<li>Create a basis for responsible decisions on the use or withdrawal of a model.<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Model maps document the purpose, performance and limits of an AI model, create transparency and support AI governance and compliance.<\/p>","protected":false},"author":1,"featured_media":0,"menu_order":0,"template":"","meta":{"footnotes":""},"class_list":["post-41628","glossary","type-glossary","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Modellkarte - Ailance<\/title>\n<meta name=\"description\" content=\"Modellkarten: Wie ein N\u00e4hrwertetikett f\u00fcr KI \u2013 dokumentieren Zweck, Trainingsdaten, Performance und Grenzen; 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