Read time: ≈16 minutes

Happy Autumn!

If you’re at all like me, you might be trying to get AI to take over the tasks you’re not as excited about.

Can’t AI replace my hours of number-crunching for me?

I work as a mixed methods researcher and advisor, but I’m naturally more interested in qualitative work. When I get questions about whether we should use AI to run quantitative analyses, I hesitate a little bit. Because if I’m honest, I’m hoping AI can do most of my quant work soon.

But is that possible, and is that a good approach that I would advise others to follow?

This month, I’ve run some quantitative AI analyses and collected considerations for AI quant work that I think you should know.

On the opposite end of the spectrum from more math-focused research is probably reading humans’ emotions. I repeatedly see arguments made about AI not being on the same level as humans because “AI doesn’t recognize emotions like we do”.

But is that accurate? A recent study on “Emotion AI” has answers…

Plus, a big model update, and some interesting tools.

Here comes the September edition -

In this edition:

1. 🧐 AI Analysis Part II: Quantitative. How much can we trust AI for quant work? My considerations for AI in quantitative analysis tasks.

2. ⏩️ Copy-paste Quantitative Analysis Prompts. A few prompts I used in testing, and that AI suggested I use for better results.

3. 😃 Can AI recognize emotion the way humans can? A recent study suggests that it can.

4. 📊 This AI data analysis study I referenced while testing this month might change your mind about how much we can trust AI for quant tasks.

5. 📰 AI News. Open AI’s latest model can reason better than ever (and apparently better than Ph.D.’s). Learn why that matters.

   Plus…a few tools I’ve been playing with. Keep reading! 👇

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