{"id":4203,"date":"2026-09-11T18:55:27","date_gmt":"2026-09-11T16:55:27","guid":{"rendered":"https:\/\/trainitnow.com\/nl\/product\/ai-ethics-fundamentals-elearning\/"},"modified":"2026-10-02T16:17:49","modified_gmt":"2026-10-02T14:17:49","slug":"ai-ethics-fundamentals-elearning","status":"publish","type":"product","link":"https:\/\/trainitnow.com\/nl\/product\/ai-ethics-fundamentals-elearning\/","title":{"rendered":"AI+ Ethics Fundamentals\u2122 eLearning"},"content":{"rendered":"<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Ethics Professionals<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>:<\/strong>Enhance your <\/span><span>expertise<\/span><span> in AI ethics to guide responsible AI deployment.<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>AI &amp; Data Enthusiasts<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>:<\/strong>Learn how to apply ethical frameworks in AI decision-making processes.<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Compliance Officers<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>:<\/strong>Ensure AI technologies <\/span><span>comply with<\/span><span> legal and ethical standards to mitigate risks.<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Technology Leaders<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>:<\/strong>Drive ethical AI strategies and lead responsible AI initiatives within organizations.<\/span><\/span><span>&nbsp;<\/span><\/p>\n<p><strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span>Students &amp; New Graduates<\/span><\/span><\/strong><span lang=\"EN-US\" xml:lang=\"EN-US\"><span><strong>:<\/strong>Gain a competitive edge in the rapidly growing field of AI ethics.<\/span><\/span><span>&nbsp;<\/span><\/p>\n<ul>\n<li><strong>In-Depth Ethical Understanding:<\/strong>Understand ethical considerations and social impacts of AI for responsible decision-making.<\/li>\n<li><strong>Bias Mitigation and Fairness:<\/strong>Learn strategies to identify and prevent biases in AI systems, ensuring fairness and transparency.<\/li>\n<li><strong>Privacy and Security Assurance:<\/strong>Explore strategies to safeguard privacy and secure AI systems and data.<\/li>\n<li><strong>Legal and Regulatory Compliance:<\/strong>Understand global AI regulations to ensure compliance with legal and ethical standards.<\/li>\n<\/ul>\n<div>Course Overview<\/div>\n<ul>\n<li>Course Introduction <a href=\"https:\/\/www.youtube.com\/watch?v=HZk2x7nP5DQ\">Preview<\/a><\/li>\n<\/ul>\n<div>Module 1: Foundations of AI Ethics and Responsible AI<\/div>\n<ul>\n<li>1.1 Understanding AI in a Modern Ethics Context<\/li>\n<li>1.2 The Societal Impact of AI Technologies<\/li>\n<li>1.3 Core Principles and Stakeholders<\/li>\n<li>1.4 Building AI Literacy for the Workplace<\/li>\n<li>1.5 Human Rights, Democracy, and AI Ethics<\/li>\n<li>1.6 Case Studies<\/li>\n<\/ul>\n<div>Module 2: Bias, Fairness, and Inclusion in AI<\/div>\n<ul>\n<li>2.1 Where Bias Enters AI Systems<\/li>\n<li>2.2 Fairness Concepts and Practical Evaluation<\/li>\n<li>2.3 Mitigation and Inclusive Design<\/li>\n<li>2.4 Applied Fairness Cases<\/li>\n<li>2.5 Case Studies<\/li>\n<\/ul>\n<div>Module 3: Transparency, Explainability, and Documentation<\/div>\n<ul>\n<li>3.1 Why Transparency Matters<\/li>\n<li>3.2 Explainability Methods and Documentation Standards<\/li>\n<li>3.3 Communicating AI Decisions Responsibly<\/li>\n<li>3.4 Transparency, Documentation, and Governance Practices<\/li>\n<li>3.5 Case Studies<\/li>\n<\/ul>\n<div>Module 4: Privacy, Security, and AI Data Governance<\/div>\n<ul>\n<li>4.1 Privacy Principles in AI<\/li>\n<li>4.2 AI Data Governance and Data Quality<\/li>\n<li>4.3 Security Risks in AI Systems<\/li>\n<li>4.4 Privacy-Preserving AI Techniques<\/li>\n<li>4.5 Content Authenticity, Provenance, and Trust<\/li>\n<li>4.6 Real World Case Studies<\/li>\n<\/ul>\n<div> Module 5: Accountability, Oversight, and AI Governance<\/div>\n<ul>\n<li>5.1 Accountability Across the AI Lifecycle<\/li>\n<li>5.2 Human Oversight and Control<\/li>\n<li>5.3 Risk Management and Assurance<\/li>\n<li>5.4 Red Teaming and Safety Testing<\/li>\n<li>5.5 Governance Operating Model<\/li>\n<li>5.6 Grievance and Remedy Processes<\/li>\n<li>5.7 System Retirement and Decommissioning<\/li>\n<li>5.8 Applied Case Studies<\/li>\n<\/ul>\n<div> Module 6: Legal, Regulatory, and Standards Landscape<\/div>\n<ul>\n<li>6.1 International Principles and Treaties<\/li>\n<li>6.2 Management and Technical Standards<\/li>\n<li>6.3 Binding Regional Laws<\/li>\n<li>6.4 National Guidance and Voluntary Frameworks<\/li>\n<li>6.5 Sector-Specific and Cross-Border Compliance<\/li>\n<li>6.6 Case Studies<\/li>\n<\/ul>\n<div>Module 7: Generative AI, Agentic AI, and Responsible Deployment<\/div>\n<ul>\n<li>7.1 How Modern Generative and Agentic AI Systems Work<\/li>\n<li>7.2 New Risks Introduced by Generative AI<\/li>\n<li>7.3 Agentic AI Risks and Governance<\/li>\n<li>7.4 Evaluation and Safe Deployment<\/li>\n<li>7.5 Responsible Use Cases and Boundaries<\/li>\n<\/ul>\n<div>Module 8: Capstone &#8211; AI Ethics Impact Assessment and Governance Plan<\/div>\n<ul>\n<li>8.1 Select an AI Use Case<\/li>\n<li>8.2 Perform an Ethics and Risk Assessment<\/li>\n<li>8.3 Develop an AI Governance Package Using the NIST AI RMF<\/li>\n<li>8.4 Final Capstone Deliverable<\/li>\n<li>8.5 Review and Reflection<\/li>\n<\/ul>\n<div>Optional Module: AI Agents for Ethics<\/div>\n<ul>\n<li>1.1 What Are AI Agents?<\/li>\n<li>1.2 Applications and Trends of AI Agents for Ethics<\/li>\n<li>1.3 How Does an AI Agent Work?<\/li>\n<li>1.4 Core Characteristics of AI Agents<\/li>\n<li>1.5 Importance of AI Agents<\/li>\n<li>1.6 Types of AI Agents<\/li>\n<\/ul>\n<div>Tools you will explore<\/div>\n<ul>\n<li>AI4People (Atomium &#8211; European Institute for Science, Media, and Democracy)<\/li>\n<li>IBM &#8211; AI Fairness 360<\/li>\n<li>IBM &#8211; AI Explainability 360<\/li>\n<li>European Commission High-Level Expert Group on AI<\/li>\n<\/ul>\n<p> Instructor-led OR Self-paced course + Official exam + Digital badge <\/p>\n<p>Online proctored exam included, with one free retake.<br \/>Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam<\/p>\n<p>Access to all materials and exams is provided for 365 days after delivery.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Formerly known as AI+ Ethics&trade; <\/p>\n<p> Navigate the Intersection of AI and Ethics in Business Landscape<\/p>\n<ul>\n<li><b><span>Responsible AI Focus:<\/span><\/b><span> Master ethical AI use aligned with business and societal values<\/span><\/li>\n<\/ul>\n<ul>\n<li><b><span>Risk Mitigation:<\/span><\/b><span> Learn to manage compliance, transparency, and AI decision-making<\/span><\/li>\n<\/ul>\n<ul>\n<li><b><span>Strategic Guidance:<\/span><\/b><span> Integrate ethical practices into AI adoption and leadership<\/span><\/li>\n<\/ul>\n<ul>\n<li><b><span>Reputation Builder:<\/span><\/b><span> Build organisational trust and credibility in AI deployments<\/span><\/li>\n<\/ul>\n<p><span>&nbsp;<\/span><\/p>\n","protected":false},"featured_media":1084,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false},"product_brand":[],"product_cat":[499],"product_tag":[722,725,724,723],"class_list":["post-4203","product","type-product","status-publish","has-post-thumbnail","product_cat-cb-elearning","product_tag-cb-ai4people-atomiumeuropean-institute-for-science-media-and-democracy","product_tag-cb-european-commission-high-level-expert-group-on-ai","product_tag-cb-ibmai-explainability-360","product_tag-cb-ibmai-fairness-360","first","instock","taxable","shipping-taxable","purchasable","product-type-simple"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI+ Ethics Fundamentals\u2122<\/title>\n<meta name=\"description\" content=\"Use AI ethically and responsibly, focusing on bias, transparency, privacy 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