Responsible AI & Tech Governance: 1 Day Workshop in Detroit, MI

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Duration: 1 Full Day (9:00 AM – 5:00 PM)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, beverages, and light snacks included

This workshop provides a practical and structured understanding of how to design, manage, and govern AI systems responsibly. Participants will explore ethical frameworks, accountability structures, bias awareness, regulatory implications, and transparency practices to ensure AI systems align with human values. Through guided discussions and scenario-based activities, attendees will learn how to make ethical decisions, reduce harm, and integrate governance controls into real-world AI development and deployment.

Learning Objectives

• Understand ethical risks and human impact of AI systems
• Detect and mitigate algorithmic bias and fairness issues
• Apply governance frameworks to AI development workflows
• Navigate emerging global AI regulations and compliance requirements
• Create transparent, accountable, and responsible AI processes
• Develop a practical ethical AI implementation plan

Target Audience

• AI & Technology Leaders
• Compliance, Legal & Risk Professionals
• Policymakers and Public Sector Advisors
• Product Managers and Innovation Teams
• Organizational Governance & Strategy Stakeholders

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AI is rapidly shaping business, policy, and society — yet many organizations struggle to implement governance frameworks that ensure fairness, safety, and accountability. This program translates complex ethical concepts into simple, practical tools that professionals can apply immediately.

📧 Contact us today to schedule a customized in-house, face-to-face session: [email protected]

Info: • Key principles of ethical AI development
• Human-centered values in AI design
• Understanding societal impact and responsibility
• Icebreaker Activity

Info: • How bias enters AI systems
• Techniques to increase fairness and explain ability
• Impact of data sources on model behavior
• Activity

Info: • Accountability models for AI decision-making
• Roles of ethics boards and governance teams
• Designing responsibility into workflows and approvals
• Role Play

Info: • Overview of global AI regulatory trends
• The EU AI Act and regional compliance duties
• Aligning internal policy with external expectations
• Case Study

Info: • Risk assessment and mitigation planning
• Monitoring and auditing AI behavior post-launch
• Communicating AI system outputs transparently
• Simulation

Info: • Cultural context and inclusivity in AI systems
• Stakeholder engagement and community impact
• Balancing innovation with care and trust
• Group Brainstorm Activity

Info: • Creating your ethical AI governance roadmap
• Setting measurable oversight and accountability goals
• Sustaining responsible AI practice long-term
• Action Plan Review

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