How to Write Creative Prompts for Multiple Perspectives | AI Prompt Tips

Enhanced Prompt to Encourage AI Models to Consider Topics from Multiple Perspectives

Objective:
To craft creative AI prompts that effectively encourage language models to explore, analyze, and present information from diverse perspectives, ensuring a comprehensive and balanced understanding of the topic. This involves designing prompts that align with professional standards, optimize AI performance, and meet the user's quality expectations.

Deliverables:

1. A structured template for writing prompts that elicit multiple perspectives (e.g., historical, cultural, scientific, moral/ethical, and creative perspectives).
2. A clear methodology for evaluating the effectiveness of these prompts, including metrics such as:
   • Coverage of perspectives (quantified as a percentage of perspectives addressed).
   • Consistency with industry standards (e.g., alignment with established frameworks or best practices).
   • Readability and clarity for the AI model.
   • The ability to generate coherent, well-organized, and diverse responses.
3. Best practices for refining prompts based on user feedback and performance analysis.

Industry Best Practices and Standards:

• Incorporate Cognitive Load Theory to avoid overwhelming the AI model with too many perspectives.
• Use Contrastive Reasoning to highlight differences between perspectives.
• Apply ** frames** (e.g., dewey's experiential learning theory) to ensure a well-rounded understanding.
• Employ Systematic Analysis by breaking down the topic into hierarchical components (e.g., macro-level, meso-level, micro-level).
• Leverage Ethical AI Frameworks such as the AI Safety Grid to ensure responsible and diverse perspectives.
• Utilize Data-Driven Approaches by incorporating diverse datasets and examples.

Quality Expectations:

• Prompts should be well-documented with rationale and references.
• Responsive to user feedback and often requires iterative refinement.
• Adherence to ethical guidelines, including avoiding bias, misinformation, and sensitive topics.
• Consistency across different AI models and configurations.
• Meets performance benchmarks set by the organization or industry standard.

Technical Considerations:

1. Prompt Structure:
   • Use topic headers (e.g., "What are the historical perspectives on...?").
   • Incorporate call-to-action instructions for the AI model (e.g., "Provide five distinct perspectives").
   • Use templates (e.g., "Consider the perspectives of [..., ..., ...] when addressing [...]." ).
2. Parameter Tuning: