Reading: Responsible AI Use in Education

• AI introduces ethical challenges such as bias, misinformation, and privacy concerns. Educators must ensure transparency, fairness, and accountability when integrating AI tools.
• Key principles:
  • Bias Mitigation: AI models can perpetuate stereotypes. Validate outputs and diversify training data sources.
  • Privacy Protection: Avoid sharing sensitive student data with third-party tools.
  • Academic Integrity: Establish clear guidelines for AI-assisted work.
  • Environmental Impact: Large AI models consume significant energy. Opt for efficient tools and limit unnecessary queries.
• Frameworks like UNESCO’s AI Ethics Guidelines and institutional policies should guide practice.

Video: AI Ethics 101: What Educators and Students Should Know

Duration: 5:53
License: Creative Commons
Overview: Covers fairness, transparency, accountability, privacy, and responsible AI use in education. Includes practical questions for reflection.

Case Studies:

• Example 1: AI-generated feedback introducing bias.

• Example 2: Carbon footprint of large-scale AI deployments.