December 19: Seeking Input over Output

Finding Meaning with AI

Today we're taking a moment to explore two thought-provoking perspectives that challenge how we think about AI integration. Ethan Mollick, a leading voice on the practical use of AI, has written an insightful piece that captures a balanced, nuanced view of how AI can best support our expertise. His article, linked below, outlines scenarios where AI shines and where it falls short. This isn’t just a "how-to"; it’s a guide for thinking differently about AI. Meanwhile, Rhea Purohit encourages us to move beyond mere efficiency to find deeper meaning in our AI interactions. Their insights feel especially relevant now that we've spent time experimenting with various AI tools and techniques. Take some time today to read these pieces and reflect on how they might reshape your approach to AI partnership.

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🎯 Objective:
Explore expert perspectives on effective AI collaboration and consider how to use AI not just as a tool for efficiency, but as a partner in creating more meaningful and thoughtful work.

🔍 Part 1: Resource Review

Read both articles, noting how they compliment each other:

• “When to Use AI - And When Not To” by Ethan Mollick
• "You're Probably Using AI Wrong" by Rhea Purohit

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💡A Helpful Mindset Shift:
When using AI, try focusing on seeking input over output. Instead of just asking AI to produce something for you, use it to:

• Double-check your thought process
• Identify blind spots
• Get a quick second opinion
• Explore opposing viewpoints

This shift can help you enhance the quality of your work without compromising your expertise.

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Part 2: Meaningful Input Exercise

Choose one piece of work you've created recently (an essay, presentation, code, analysis, etc.) and use AI to gather input in these ways:

1. Finding Your Value and Purpose:
   • What aspects of this work do you find most meaningful?
   • Which parts do you "cherish" (as Purohit puts it)?
   • Where could AI help with the parts you don't enjoy?
   • What elements of your expertise are most crucial to preserve?
   • How could AI enhance rather than replace your creative process?
2. Thoughtful Partnership and Perspective:
   • "Let's explore this from multiple angles - what perspectives am I missing?"
   • "Can you play devil's advocate and challenge my main assumptions?"
   • "What would experts from different fields say about this approach?"
   • "Help me brainstorm 10 different ways to tackle this challenge"
   • "What questions should I be asking that I haven't thought of?"
3. Quality Enhancement and Blind Spots:
   • "What potential weaknesses should I address in my argument?"
   • "Where could this be clearer or more precise for my audience?"
   • "What relevant context or evidence would strengthen this?"
   • "Are there any counterarguments I should consider?"
   • "What connections or patterns might I be overlooking?"

✨ Bonus Challenge:

Have a conversation with an AI about your workflow, similar to Purohit's example in her article. Start a dialogue asking it to help you identify:

• Which parts of your work bring you the most meaning
• Where AI could help enhance (not replace) those meaningful aspects
• How to use AI to handle the parts you find less engaging
• What patterns it notices in what you find most fulfilling

The key is to treat this as a real conversation - respond naturally to the AI's questions and let it help you explore your thoughts and preferences.

🤔 Reflection Questions:

• How might shifting from "output-first" to "input-first" change your relationship with AI?
• What parts of your work do you want to protect and enhance rather than automate?
• How could AI help you spend more time on what matters most to you?