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@ -5,6 +5,15 @@ Category: AI, Data
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Tags: ai, python
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Slug: when-to-use-ai
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Authors: Andrew Ridgway
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Summary: Should we be using AI for ALL THE THINGS!?
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# Human Introduction
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Well.. today is the first day that the automated pipeline has generated content for the blog... still a bit of work to do including
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1. establishing a permanent vectordb solution (chromadb? pg_vector?)
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2. Notification to Matrix that something has happened
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3. Updating Trilium so that the note is marked as blog_written=true
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## The Great AI Debate: When to Trust the Machine vs. When to Stick to Your Brain
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@ -47,5 +56,21 @@ While AI shouldn't be trusted to run calculations, it can be helpful in suggesti
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AI is good at *finding connections* and *handling ambiguity*, but it’s *not good at precision*. When you need to ensure that a calculation is accurate, or that a mapping is flawless, AI is not the best choice. And that’s where humans shine. We’re good at *seeing* the connection between two things, even if it’s not obvious. We’re good at *precision* and *accuracy*.
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> *“I was given a list of work types that could be grouped into 1 of 2 categories exclusively.”*
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> *“The problem was… the ‘work types’ and work requests were at best tangentially related.”*
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| Scenario | AI? | Reason |
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|---|---|---|
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| Ambiguous data | ❌ | AI struggles with context |
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| Repetitive tasks | ✅ | AI handles math and logic |
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| Creative decisions | ❌ | AI lacks the ability to think creatively |
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So I had to manually read each work type and map it to a work request. It was a *shudder-inducing* task.
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## The Final Thought
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So, in summary:
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* **AI is not the best choice** when you need precision, accuracy, or a human touch.
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* **AI is the best choice** when you need to handle ambiguity, find connections, or automate repetitive tasks.
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And that’s why I’m a journalist, a developer, and a DevOps expert. I know when to trust the machine and when to rely on my brain.
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> *“When in doubt, just do it.”*
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