Utilizing Open-Ended Questions | Shaping the Future with Individual Agency

Enhanced Prompt:

Title: Mastering Open-Ended Questions for Future Shaping: Crafting Prompts That Foster Individual Agency and Critical Thinking

Objective:
To design and implement prompts that effectively encourage language models to consider the role of individual agency, choice, and decision-making in shaping the future. This involves leveraging open-ended questions to elicit thoughtful, diverse, and actionable responses that align with ethical, inclusive, and sustainable outcomes.

Deliverables:

1. A comprehensive guide on crafting open-ended prompts that highlight individual agency and choice.
2. A set of best-practice prompts with examples and use cases.
3. A framework for evaluating the effectiveness of prompts in fostering agency-aware outcomes.
4. Metrics and KPIs for measuring the impact of these prompts on decision-making and critical thinking.
5. Tools and resources for monitoring and refining prompts over time.

Industry Best Practices and Standards:

• Incorporate principles of ethical AI use, including transparency, accountability, and fairness.
• Ensure prompts are inclusive, diverse, and free from bias.
• Utilize established frameworks and tools such as GPT-4, Claude 2, or similar advanced language models.
• Reference industry standards for prompt engineering, such as those outlined in GPT-4's "thinking about thinking" capabilities.

Quality Expectations:

• Prompts must be clear, open-ended, and relevant to the topic.
• Responses should demonstrate critical thinking, creativity, and a focus on individual agency.
• Ensure prompts are free from leading questions or assumptions.
• Evaluate prompts for ethical implications, inclusivity, and diversity.
• Metrics include response word count, accuracy, engagement, and alignment with predefined KPIs (e.g., percentage of responses addressing agency, choice, or decision-making).

Technical Considerations:

• Use appropriate model versions (e.g., Claude 2, GPT-4) based on the complexity of the task.
• Optimize prompts for efficiency and scalabil