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Building Ethical AI in Organizations
Enterprise Program on Operationalizing AI Ethics, Governance, and Responsibility at Scale
Early access to the e-LMS platform is included
About This Course
“Building Ethical AI in Organizations” is a leadership-focused and cross-functional training program designed to operationalize ethical principles of fairness, explainability, privacy, and inclusivity into real-world AI projects and systems.
As enterprises accelerate AI adoption, ethical lapses can lead to public backlash, compliance violations, and loss of trust. This program helps stakeholders design ethics-by-design processes, build AI governance committees, conduct impact assessments, and align with regulatory frameworks such as the EU AI Act, OECD Principles, NIST AI RMF, and corporate ESG standards.
Aim
To guide organizations in developing and embedding ethical AI frameworks, aligning innovation with accountability, transparency, and societal good while reducing regulatory, reputational, and operational risks.
Program Objectives
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Translate AI ethics principles into operational workflows
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Embed responsibility in every phase of the AI lifecycle—from design to deployment
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Mitigate bias, opacity, and harm in enterprise AI models
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Build accountability, documentation, and stakeholder trust
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Support long-term AI resilience aligned with business and social values
Program Structure
Week 1: Foundations of Ethical AI
Module 1: Principles of Ethical AI
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Chapter 1.1: What Is Ethical AI? Core Values and Global Norms
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Chapter 1.2: Common Ethical Challenges in AI Systems
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Chapter 1.3: Human Rights, Justice, and Autonomy in AI Contexts
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Chapter 1.4: Cross-Cultural Perspectives on Fairness and Ethics
Module 2: From Ethics to Action
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Chapter 2.1: Translating Ethical Principles into Organizational Policies
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Chapter 2.2: Avoiding Ethics Washing and Empty Frameworks
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Chapter 2.3: Ethics in Product Lifecycle: Design, Development, and Deployment
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Chapter 2.4: Case Studies of Ethical Failures and Lessons Learned
Week 2: Systems, Roles, and Governance for Ethical AI
Module 3: Building Organizational Structures
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Chapter 3.1: Roles and Responsibilities (Ethics Leads, Review Boards, Committees)
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Chapter 3.2: Creating Cross-Functional Ethics Teams
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Chapter 3.3: Integrating Ethics into Product Development and ML Ops
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Chapter 3.4: Internal Training and Ethical Capacity-Building
Module 4: Tools and Frameworks for Responsible AI
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Chapter 4.1: Impact Assessments (Algorithmic, Human Rights, Environmental)
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Chapter 4.2: Transparency and Explainability in Practice
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Chapter 4.3: Auditing, Monitoring, and Documentation Tools
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Chapter 4.4: Governance Frameworks: OECD, ISO 42001, NIST AI RMF
Week 3: Accountability, Culture, and Continuous Improvement
Module 5: Accountability and Escalation Paths
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Chapter 5.1: Incident Management and Red Flags in AI Systems
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Chapter 5.2: Whistleblower Protections and Ethical Dissent Channels
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Chapter 5.3: Reporting to Leadership, Boards, and the Public
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Chapter 5.4: Aligning Ethical AI with Legal Compliance and Risk
Module 6: Culture, Strategy, and Long-Term Impact
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Chapter 6.1: Shaping Organizational Culture Around Responsible Innovation
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Chapter 6.2: Communicating Ethical Commitments to Stakeholders
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Chapter 6.3: Metrics, KPIs, and Incentives for Ethical Performance
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Chapter 6.4: Capstone: Draft an Ethical AI Strategy for Your Organization
Who Should Enrol?
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CXOs, VPs, and Directors overseeing AI and data strategy
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AI/ML engineers and product managers
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HR, legal, and compliance officers
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ESG and risk management professionals
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Ethics officers and data governance leads
Program Outcomes
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Design and institutionalize AI ethics policies and governance systems
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Conduct algorithmic risk assessments and ethical impact audits
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Build internal capacity through training and change management
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Align AI practices with global regulatory and sustainability frameworks
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Earn a certification in “Organizational AI Ethics & Governance”
Fee Structure
Discounted: ₹21499 | $249
We accept 20+ global currencies. View list →
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- One-on-one project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
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