Artificial intelligence (AI) isn’t a new term. But the buzz around it has exploded lately, thanks in large part to the popularity of content generation tools like ChatGPT and DALL-E. With their ability to quickly generate custom answers, stories, illustrations, and more by simply typing out a short description, it’s no wonder they’ve enticed so many people to play with this new wave of AI technology. And while they may have caught people’s attention as a novelty, these tools have also inspired many to consider how they might fit into the world of work as well.
For those of us in tech-driven fields like e-learning, the signs are clear—AI will increasingly intersect with our world over the next few years. What’s less clear, though, are the specifics of how.
If you’re new to this technology and find that ambiguity confusing or stressful, this article is here to help! You’ll explore what AI is, how e-learning professionals are using it in their work right now, and how you can guide your organization on using this technology strategically.
1. What exactly is AI?
The term “artificial intelligence” dates back to at least the 1950s, and its definition is broad—the ability for machines to perform tasks we typically associate with human intelligence, like problem-solving and decision-making.
Does this mean AI tools are intelligent in the same way as people? No. But they can fake it reasonably well in very specific situations. For instance, an AI-powered chess system like Deep Blue can play that one game exceptionally well. But unlike humans, it can’t apply those same problem-solving skills in other contexts.
2. How does AI work?
Have you ever typed a few characters into a website search window only to have it automatically fill out the rest of the product name you were looking for? Or have you ever started working on a text and had your phone suggest logical options for the next word in your sentence? Then congratulations! You’ve interacted with AI—even if you may not have realized it!
These predictive AI approaches use information from large pools of data to make educated guesses about the future. They can’t create anything new, but they can be useful in situations where patterns from the past provide good clues about choices or behavior in the future.
Today’s AI buzz, though, is more focused on a different category—generative AI. This approach also analyzes massive amounts of data to look for patterns and common responses. But then it uses the connections it finds to generate new content—such as text, images, video, or code. What does this difference mean in the real world? Predictive AI approaches can auto-complete the word ”cake” after you type “chocolate” or tell an online store that people who buy chocolate cake mix are also likely to buy eggs. But generative AI can create a new chocolate cake recipe for you based on all the recipes it’s seen before. People often find generative AI intriguing because it’s easy to use and creates content fast. But it has limitations too, since it relies so heavily on large data pools and averages.
Want to go even deeper into how generative AI works? Try this short explainer video.
Regardless of which type of AI you’re working with, it’s important to note that while these tools may appear to comprehend information the way humans do, they actually don’t. They simply look for data patterns to determine the most probable answer to requests. For instance, if you ask ChatGPT what to serve at your kid’s birthday party and it recommends pizza and ice cream, that’s not because it knows they’re delicious—or even understands what a birthday party is. It’s just noticed the words “pizza” and “ice cream” are often associated with the words “kid’s birthday party.” This pattern recognition can do a lot, but it can still make mistakes and unknowingly share incorrect information. So it’s a good practice to always double-check AI-generated content for inaccuracies.
3. Is AI going to steal my job?
Now let’s address the elephant in the room. Is AI going to steal your job? For most people in e-learning, the answer is probably not. At first glance, the speed at which today’s AI tools can generate content seems like a possible threat. But the reality is that course creators like you do much more than just produce and then distribute content. Designing effective e-learning means ensuring raw content is transformed into engaging learning experiences. That’s the kind of creative work that can only be informed by your e-learning expertise and a deep understanding of the needs of your learners and organization.
That said, business partners and clients aren’t always aware of the intricacies that go into designing meaningful e-learning. So even if they understand the limitations of today’s AI technology, they may not realize how many aspects of course creation these tools can’t take on independently. This is another area where you can add value. Because you're uniquely positioned to guide your partners on what AI truly means to the world of e-learning—from identifying where it has the best potential to shining a light on all the ways human creators like you ensure the final result makes a real impact.
AI may be the current hot trend that’s impacting learning and development. But advocating for the value we bring to our organizations and learners has always been crucial to what we do. This is just another chance to put your advocacy skills to work.
4. How are e-learning professionals using AI right now?
Lots of people in our field have been experimenting with these tools and sharing their results. Thanks to their work, we’ve got a wealth of ideas for how the current wave of AI tools can fit into e-learning workflows, including:
- Idea generation: Summarizing common thoughts on a topic, providing guidance on standard content outlines and formats, suggesting possible flows of information, and even helping you past writer’s block by giving you ideas on what not to write about.
- Administrative tasks: Taking meeting notes and summarizing them, integrating information from multiple tools to simplify booking meetings, drafting common email responses, providing suggestions for better scheduling your time, summarizing long documents or emails, and streamlining processes for moving content from one format to another.
- Research and writing: Summarizing large amounts of research or content dumps, aligning your writing to a brand voice or desired tone, suggesting edits to improve grammar and readability, and building basic first drafts of content.
- Media editing and generation: Generating media ideas and basic course layouts, automating simple media editing tasks like removing background noises or flubs, tweaking stock images, and generating talking head videos.
- Supporting advanced e-learning functionality: Providing personalized feedback on freeform answers from learners, playing basic roles in interactive digital roleplays, supporting chatbot functionality, and helping to write or troubleshoot simple code for enhancing courses.
Wrap-Up
You’ve now got the current AI basics down pat! But as with any rapidly growing technology, it’s also helpful to keep an eye on how AI will evolve over time—both to help you make strategic choices for yourself and so you can advise your organization on doing the same.
Not sure where to look for AI updates? Free webinars from L&D professionals and AI tool vendors are a handy way to stay on top of what’s new. Following AI experts on social media can give you quick industry updates, as can following e-learning experts who are playing with these tools. Regularly reading tech blogs and magazines can provide a deeper dive into where AI is going next. And industry whitepapers and ebooks are also useful sources for more in-depth information.
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Published 2 years ago
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