{"product_id":"building-responsible-ai-algorithms-a-framework-for-transparency-fairness-safety-privacy-and-robustness-9781484293058","title":"Building Responsible AI Algorithms: A Framework for Transparency, Fairness, Safety, Privacy, and Robustness","description":"\u003cp\u003e • Author(s): Toju Duke\u003cbr\u003e • Publisher: Apress\u003cbr\u003e • Publisher Imprint: Apress\u003cbr\u003e • BISAC: Artificial Intelligence - General\u003c\/p\u003e\u003cp\u003eThis book introduces a Responsible AI framework and guides you through processes to apply at each stage of the machine learning (ML) life cycle, from problem definition to deployment, to reduce and mitigate the risks and harms found in artificial intelligence (AI) technologies. AI offers the ability to solve many problems today if implemented correctly and responsibly. This book helps you avoid negative impacts - that in some cases have caused loss of life - and develop models that are fair, transparent, safe, secure, and robust.\u003cbr\u003eThe approach in this book raises your awareness of the missteps that can lead to negative outcomes in AI technologies and provides a Responsible AI framework to deliver responsible and ethical results in ML. It begins with an examination of the foundational elements of responsibility, principles, and data. Next comes guidance on implementation addressing issues such as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eBuild AI\/ML models using Responsible AI frameworks and processes\u003c\/li\u003e\n\u003cli\u003eDocument information on your datasets and improve data quality\u003c\/li\u003e\n\u003cli\u003eMeasure fairness metrics in ML models\u003c\/li\u003e\n\u003cli\u003eIdentify harms and risks per task and run safety evaluations on ML models\u003c\/li\u003e\n\u003cli\u003eCreate transparent AI\/ML models\u003c\/li\u003e\n\u003cli\u003eDevelop Responsible AI principles and organizational guidelines\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003cbr\u003eAI and ML practitioners looking for guidance on building models that are fair, transparent, and ethical; those seeking awareness of the missteps that can lead to unintentional bias and harm from their AI algorithms; policy makers planning to craft laws, policies, and regulations that promote fairness and equity in automated algorithms","brand":"Apress","offers":[{"title":"Paperback","offer_id":45033180004503,"sku":"9781484293058","price":2424.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781484293058.webp?v=1768543081","url":"https:\/\/atlanticbooks.com\/products\/building-responsible-ai-algorithms-a-framework-for-transparency-fairness-safety-privacy-and-robustness-9781484293058","provider":"Atlantic Books","version":"1.0","type":"link"}