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The Six Golden Rules of AI for Analysts.
Artificial Intelligence   Data Analysis   Latest   Machine Learning

The Six Golden Rules of AI for Analysts.

Last Updated on March 28, 2024 by Editorial Team

Author(s): Kendrick

Originally published on Towards AI.

That Nobody Has Told You About.
Photo by Kenny Eliason via Unsplash

A senior analyst once emailed me “The Ten Golden Rules of Analysis.” As the name suggests, it was a set of norms and best practices to help navigate the ebbs and flows of a challenging profession.

In my time creating and teaching AI products for analysts, I realized that I had inadvertently developed ten principles of AI for analysts (and honestly, for everyone else) that, hopefully, can guide analysts in and entering the AI world.

I am sharing six of the ten here. The full list will be available in chapter six of my upcoming book: AI as the Sixth Intelligence Discipline: A Tradecraft Guide for Analysts

The other day, a friend of mine showed me a clip from Joe Rogan’s podcast. The guest was explaining to Rogan how AI (in this case, a large language model (LLM)) had circumvented those very annoying captcha checks. Among other things, the guest said, “the AI had thought to do this on its own.” [1]

No, it did not. AI is dumb. It is dumber than most people think. There are a lot of technical reasons, but the most obvious one is, for example, that you must prompt LLMs (other AI architectures… Read the full blog for free on Medium.

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