Graduate Certificate in AI Ethics for Educational Technology Integration
-- viewing nowArtificial Intelligence (AI) Ethics is a rapidly evolving field that requires careful consideration of technology's impact on society. This Graduate Certificate in AI Ethics for Educational Technology Integration is designed for educators, instructional designers, and technologists who want to develop the skills to integrate AI in a responsible and ethical manner.
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AI Ethics Fundamentals: This unit introduces students to the principles and concepts of AI ethics, including fairness, transparency, and accountability, and their application in educational technology. •
Machine Learning and Bias: This unit explores the relationship between machine learning algorithms and bias, including data bias, algorithmic bias, and the impact on educational technology. •
Human-Centered Design for AI: This unit focuses on designing AI systems that prioritize human values, needs, and well-being, and how to integrate human-centered design principles into educational technology development. •
AI and Education: This unit examines the role of AI in education, including its potential benefits and challenges, and how to integrate AI in a way that supports student learning and teacher effectiveness. •
AI Explainability and Transparency: This unit discusses the importance of explainability and transparency in AI systems, including techniques for interpreting and understanding AI decision-making processes. •
AI and Diversity, Equity, and Inclusion: This unit explores the relationship between AI and diversity, equity, and inclusion, including how AI can perpetuate or challenge existing biases and inequalities in education. •
AI Governance and Policy: This unit introduces students to the governance and policy frameworks surrounding AI, including regulatory frameworks, industry standards, and best practices for AI development and deployment in education. •
AI and Teacher Professional Development: This unit examines the need for teacher professional development in AI, including how to integrate AI into teaching practices, and how to support teachers in developing AI literacy. •
AI and Student Well-being: This unit discusses the impact of AI on student well-being, including the potential benefits and risks of AI use in education, and how to design AI systems that support student mental health and well-being. •
AI and Data Protection: This unit introduces students to the principles of data protection and privacy in AI, including how to design AI systems that respect student data rights and comply with relevant regulations.
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