Why you should study AI even if you’re an ‘AI skeptic’

Do you feel AI is overhyped, overused, or overestimated? That it’s just a bad idea, with issues around copyright, big corporate monopolies, environmental and human impacts, or other concerns? 

Then you should study AI.

“Hang on,” you might be thinking. “Why should I learn about it? I’m not on the AI bandwagon. Shouldn’t I be standing my ground, refusing to touch anything to do with it at all?”

And sure, you could. But here’s why you shouldn’t do that, especially if you believe in making an impact.

1. Not knowing the different kinds of AI limits the conversation

I’ve written about this before, but most people don’t realise how big AI is, at least until they sit down and actively study it. Artificial intelligence means something that can perform a task typically associated with human intelligence, including small tasks. Because of this, a lot of things qualify as AI, like:

• Autocorrect in Microsoft Word

• Your email spam filter

• A fraud detection system in your banking app

• The scripts that make enemies attack you in a game like Minecraft, or your neighbours visit you in The Sims

• Your ebook reader that reads out text to speech

• Netflix recommending your next show

Now, when most individuals say things like “I hate AI, I’d never use it!” or an executive says “I love AI, let’s adopt it in our business!”, they might not be aware that they’re already using AI, usually multiple times a day without realising it. What they’re typically referring to is Generative AI—the bucket that includes chatbots like ChatGPT (which, since release, has made me self-conscious about my love of em-dashes) and image and video generators. 

However, there are many other different kinds of AI: like computer vision, cognitive computing, robotics, and so on. Many of these are legitimate solutions for specific problems! But not knowing the breadth of AI can result in:

• Problems for companies: Rushing to adopt generative AI when there’s a better and/or cheaper AI solution.

• Problems for risk owners: Declaring overly broad bans on AI that can’t practically be enforced and cut out legitimate AI use cases.

• Problems for individuals: Not being able to pitch or discuss AI alternatives to GenAI, avoiding all learning about AI altogether due to thinking it’s all GenAI. 

One example of this is if a government organization had a total AI ban that stopped them from:

• Using computer vision to scan and process tens of thousands of documents.

• Openly recommending free text-to-speech accessibility tools for people who are blind or with low vision.

• Allowing their cybersecurity teams to use machine learning to detect hostile intruders in their IT systems.

Studying AI helps you realise that there are more AI solutions out there than just generative AI.

2. Those with AI knowledge have a greater say in adoption

If you want to have a seat at the table when people are discussing whether to adopt AI (including GenAI) at your organization or not, being knowledgeable greatly increases your odds.

Think about it. There’s a big difference between the person who says: “I don’t think we should adopt AI” - someone who doesn’t have any knowledge or formal qualifications in it…

…and the person who does and can point out, “Hey, I don’t think this type of AI should be used for this business problem. Here’s where, when, and how that type of AI should be used, based on its strengths and weaknesses.”

Put it this way: If you wanted to know about a leaking tap, would you ask a plumber, or someone who’d never picked up a wrench?

By being the one who has studied up on AI, you’re more likely to be the one in those adoption conversations, the person who can stop your organization from adopting it needlessly: or when they do adopt it, stop them from doing it badly. 

3. Learning about AI destroys assumptions and preconceptions

It’s always good to question what you believe about something, because it might not necessarily be true. Studying up on AI, particularly taking courses led by real experts, cuts through the hype and the gloom, and exposes the technology for what it really is.

For instance, you might think AI is universally useless – “Throw it in the garbage!” – but after studying up on it, you discover how it can be used to flag sensitive information in documents before they’re shared outside your company, or how it might detect cancers and fractures doctors might miss. On the flip side, you might find that something you thought AI was the next big thing for is actually a let down. 

4. You can become an AI educator for the organization

When you’ve educated yourself on AI, you can speak from that place of knowledge to educate others, and this offers business value. With that deep expertise, you can talk with authority and in detail about the harms of using AI for facial recognition to flag criminals, or how LLMs like ChatGPT can make up fake legal cases and why people shouldn’t use it for their court prep.

So long as you pick your battles wisely—which is another valuable skill worth nurturing—this helps your organization choose the right path forward and avoid pitfalls, all while sticking to your own values.

Conclusion: Be the most knowledgeable person in the room

Having AI knowledge is not the same as being mindlessly pro-AI (or more specifically, pro-GenAI.) If anything, it’s the opposite. It means you’ve researched the solution, and now you’re speaking from an informed place. 

Be that person with the deep AI knowledge who people listen to. If you love AI, learn about it. If you dislike AI, you should definitely learn about it.

How to become your organization’s AI expert

If you want to drive the conversation, be your organization’s respected voice on AI, and learn about all the different types and use cases for this technology, it’s best to learn from other industry experts. Pluralsight offers a range of beginner, intermediate, and expert AI and ML courses. Since you can sign up for a 10-day free trial with no commitments, it’s a great way to take some professionally authored courses with a set course structure.