New Course
Course Curriculum
- Articulate core human-centric AI values and mission
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- Define user well‑being, autonomy, and inclusion objectives
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- Map stakeholders, roles, and rights in AI ecosystems
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- Establish fairness, bias mitigation, and equity criteria
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- Set transparency, explainability, and communication principles
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- Define privacy, consent, and data governance boundaries
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- Design accountability, oversight, and governance structures
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- Create measurable success indicators and ethical KPIs
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- Map stakeholders and user needs for AI projects
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- Translate human-centric goals into technical requirements
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- Design data collection and labeling protocols for fairness
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- Implement human-in-the-loop workflows for key decisions
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- Apply explainability tools to interpret model outputs
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- Run bias, robustness, and performance tests on models
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- Establish consent, privacy, and data minimization practices
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- Integrate usability testing and iterative user feedback
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- Set up monitoring, logging, and post-deployment alerts
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- Document governance, audit trails, and incident response
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Instructor
Cogniroot
Course Instructor
