Artificial Data Intelligence

The Rise of Artificial Intelligence: the Good, the Bad, and the Ugly

How Data Scientists can best leverage AI

Leihua Ye, PhD
5 min readNov 26, 2023

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Photo by Markus Winkler on Unsplash

Authors:

Introduction

Print(“Hello World!”)

This is the first line of code every programmer learns to write. The tradition dates back to 1974 when Brian Kernighan and Dennis Ritchie introduced it in the book “C Programming Language.”

There are several reasons for its wide adoption:

  1. Simplicity: it’s so simple that novice programmers can write.
  2. Tradition: it has been used in many textbooks and tutorials.
  3. Instant Gratification: seeing the result instantly brings gratification to new programmers.

OK, let’s reveal the behind-the-scene story:

I asked ChatGPT about the history of Print(“Hello World!”), and it returned the above answer.

As AI becomes increasingly powerful, the question “will AI replace tech workers?” becomes a when not an if. Being replaced is a legitimate concern, considering how AI learns and iterates. It has outperformed human programmers in many aspects, starting from writing code.

Well, AI is more than writing better code and doing it faster; it can do much more. As of today (Nov 2023), OpenAI has released a new version of GPT that supports a multi-modal capacity. It now supports voice and image as information input (https://openai.com/blog/chatgpt-can-now-see-hear-and-speak). We have officially entered a new era of Human-Computer Interaction!

In such a dynamic time, those who do not incorporate AI into their workflow have fallen behind and will be replaced eventually. This is not an exaggeration, as some design companies have already laid off a significant number of average designers. Don’t be average in an era of AI; AI is the best average person (I’ll explain later).

With the rise of AI, tech workers need to adapt and treat it as an effective tool and learn to leverage it to our advantage. To document my own learning…

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Leihua Ye, PhD

Senior Data Scientist @ Walmart; PhD @ University of California. Data Science | A/B Test & Causal Inference | Career www.linkedin.com/in/leihuaye