May 1, 2023 Author: Matthew Renze

Why should I learn about AI?

In my previous article in this series on Getting Started with AI, we discuss the 8 main steps involved.

In this article, we’ll begin to drill down into each main step to learn more.

If you want to get started with AI, the first question you need to ask yourself is, “why”?

Why do I want to learn about AI? Why is it important to me to have AI skills?

There are various reasons why someone might want to learn about AI these days.

Depending on your specific reason, you will need to learn a different set of skills.

So, to help you decide your “why”, here are the top reasons why you should learn about AI.

To Be More Productive

The main benefit of using AI tools is to be more productive. AI tools allow us to automate a wide variety of tasks that we perform in our day-to-day jobs. If we can perform those tasks automatically and 10, 100, or 1,000 times faster, we will inherently be more productive at our jobs.

As software developers, we can use AI tools like GitHub Copilot to write better code, faster. As authors, we can use tools like ChatGPT to iterate on new ideas for articles quickly. As creative professionals, we can use AI tools like DALL-E 2 and Stable Diffusion to generate images thousands of times faster than creating digital art by hand.

To Increase Employability

Automation with AI will likely cause tremendous disruption to our labor economy. As AI continues to automate more manual tasks and knowledge work, there will be increased competition for these remaining jobs and new jobs available that don’t currently exist today.

If you want to remain employable, you need to learn how to work with AI rather than fight against it. AI-assisted individuals will easily outperform human-only employees performing the same job. Also, those who can build AI systems to automate these tasks will be in high demand. Learning AI skills is a great way to stay highly employable throughout the AI technology revolution and beyond.

To Solve Complex Problems

For a software developer or IT professional, there are a limited set of problems that we can solve via explicit programming. For example, imagine trying to write a computer program by hand to identify a person’s face in an image. It would be extremely difficult, if not impossible.

However, for machine learning and deep learning, this is a trivial problem to solve. ML and other AI technologies allow us to create models with much more powerful capabilities. As a result, we can now solve a much wider array of problems than a traditional software developer who can only explicitly program a computer. Learning AI skills will significantly increase the number and types of problems you can solve.

To Automate Manual Tasks

AI’s ability to solve more complex problems than traditional programming allows us to automate a much wider variety of tasks. For example, predicting engine failure from sensor data, identifying credit card fraud, and automatically generating product descriptions for a website.

If you want to be able to automate complex tasks like this, you will need to learn about artificial intelligence and machine learning. This is a very different set of skills and techniques than automating manual tasks and knowledge work with traditional software. It requires collecting, cleaning, and analyzing data in addition to training, verifying, deploying, and maintaining ML models.

To Advance The State of AI

We are beginning to enter the next technological revolution in human history — the AI revolution. Our lives, our work, and our world are changing rapidly. Many of us out there get very excited about the prospect of being on the cutting edge of this new technology revolution.

These advances result from Computer Scientists, Data Scientists, and Computational Neuroscientists pushing the boundaries of what is possible through AI research. If you want to advance the state of the art in AI, you might consider becoming an AI researcher. This path will likely require either a Master’s degree or Ph.D. in an applicable field. However, for the best and brightest, it can be a very rewarding career.

To Choose Your Own Adventure!

Based on which of the reasons listed above you identify with most, there’s a career path for you.

First, if you’re interested in being more productive with AI or remaining employable with AI, you just need to learn basic AI literacy and how to use AI-enabled tools. The following articles in this series on Getting Started with AI can teach you how to achieve these goals.

Next, if you want to solve complex problems and automate manual tasks with AI, you will likely need a 4-year degree, practical AI skills, and lots of practice. I’ve included articles in this series to help those of you who want to become AI Developers, ML Specialists, or Robotics Engineers.

Finally, if you want to advance the state of the art in AI, then you will need to get a Master’s or Ph.D. in Computer Science, Data Science, or Artificial Intelligence to become an AI researcher. I also have articles in this series on this career path as well.


To learn more, please read the next article in this series: Choosing a Career in AI

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