AI Vision in Practice: How Machines Interpret Visual Meaning

Unveil the hidden stories behind images using the power of AI vision. In this hands-on course, participants will learn to analyse their own photograph images using visual AI tools such as ChatGPT, Grok, Copilot, and DALL·E—no coding experience required. Through guided exercises involving search tools, prompt engineering, and creative exploration, learners will examine how AI interprets artistic style, composition, symbolism, and cultural context. The course combines classical research methods with interactive AI vision exploration, promoting collaborative learning and critical reflection on AI-generated outputs. Participants will also engage in discussions on the ethical implications of AI-generated content, including bias, authorship, and cultural sensitivity.

• Introduction to visual AI tools (ChatGPT, Grok, Copilot, DALL·E)
• Basics of prompt engineering for visual analysis
• Interpreting AI-generated image insights
• Comparing AI interpretations with real or human-made artwork
• Group-based AI image analysis and critique
• Image generation and prompt refinement
• Ethical issues in AI art analysis (bias, authorship, cultural sensitivity)

On successful completion of this course, learners will be able to:

• Use search tools and AI applications to gather contextual information about images.
• Analyze and evaluate AI-generated content for accuracy and artistic interpretation.
• Identify and address hallucinations and misinformation in AI outputs.
• Reflect on the ethical implications of AI in art, including bias, authorship, and cultural impact.

• Apply prompt engineering techniques to enhance image-based insights.

This course uses an interactive group-based learning approach, combining peer-to-peer feedback, trainer guidance, and collaborative analysis exercises. Participants will receive individual recommendations from the trainer and engage in hands-on activities to troubleshoot prompts and image generation using AI tools. The training is designed to encourage experimentation, critical thinking, and ethical reflection around AI-assisted visual analysis.