The overlap between media literacy, computer science and AI

The increasing prominence of artificial intelligence in education has educators exploring ways to effectively teach AI concepts through established frameworks of media literacy and computer science.

Current landscape: California’s mandate for AI literacy education has prompted educators to develop strategic approaches for teaching AI concepts in K-12 settings.

• Schools are required to integrate AI literacy across various subjects as part of the curriculum
• Many institutions are currently navigating restrictions on AI tools due to data privacy concerns
• Only 5 percent of California high school students currently take computer science classes, highlighting a significant gap in technical education

Core teaching approaches: Educators are emphasizing the fundamental connection between AI literacy, media literacy, and computer science education.

• Teachers can introduce AI concepts at the elementary level without requiring students to log into AI tools
• Media literacy skills help students evaluate AI-generated content critically
• Computer science education provides the technical foundation for understanding how AI systems work and their societal implications

Practical implementation: Several accessible tools are being used to demonstrate AI concepts in classroom settings.

• “Which Face Is Real?” website helps students distinguish between authentic and AI-generated human faces
• Google’s Quick, Draw! demonstrates how AI systems learn from existing data to recognize patterns
• Teachable Machine allows students to create their own AI models for recognizing images, sounds, or poses
• The MagicSchool song generator enables students to experiment with AI-generated music

Educational challenges: IT leaders and educators are working to address various implementation hurdles.

• Many teachers require guidance on data privacy concerns and regulations
• Schools need vetted AI resources that comply with educational standards and privacy requirements
• IT directors are stepping in to provide expertise and recommend appropriate AI tools for classroom use

Addressing bias and ethics: Educators are incorporating discussions about AI bias and ethical considerations into their curriculum.

• The Gender Shades research project is being used to demonstrate AI bias in facial recognition systems
• Students learn to question the credibility and intent behind AI-generated content
• Critical thinking skills are emphasized when evaluating AI outputs and their societal impact

Future implications: The integration of AI literacy into education represents a fundamental shift in how schools prepare students for an AI-enabled future, though significant work remains to ensure comprehensive implementation across all grade levels and subject areas.