As a learning and education professional, I’ve been watching the AI arms race and conversations around it with curiosity for the last year.
Some days I’m greeted with euphoric news of generative artificial intelligence saving me hours of precious time and enabling me to invest in the creative pursuits I love most.
Whilst on other days, I’m greeted with doomsday predictions that involve Arnie’s Terminator smashing down my office door and commanding me to ‘go with him if I want to live’.
It’s a strange paradox to live in.
- The context
- A simplified definition of AI
- Artificial Intelligence is not new
- Generative AI explained: The simple guide for humans
Yet, most of the time, specifically in the field of learning, I’m left wondering about WTF generative AI is and how can I unlock its power in the world of both corporate L&D and personal education.
You would think the answer to this would be simple to acquire.
Yet, for all the AI gurus that have emerged these last 6 months, very few seem to have the ability to share a simplified definition of the technology they continue to peddle across social feeds.
So, I decided to do what the legendary Pokemon catcher Ash Ketchum would do when looking to learn more about a new type of pocket monster, I went on the research trail to update my Pokedex.
Or, in my world, a document on my Mac. The former is of course more appealing.
I need context
To begin my journey, I needed more context.
How does the L&D industry view the generative AI evolution today and what does the majority know about this technology?
My first answer was found in the latest “Top 5 challenges For L&D Leaders in 2023” report from the Learning and Performance Institute. As you can see below, our friend has stormed right into the top spot. This lets me know fellow L&D pros are at least aware of it.
My next task was to learn from fellow L&D pros how they felt about generative AI and it’s potential impact across L&D.
To support this, I’d been working with a variety of global companies on their current understanding and directly with practitioners through a series of LinkedIn live experiences. The consensus was not unexpected, most people’s current feelings can be summed up by the below.
In conclusion, my finding so far was:
- L&D pros are aware of generative AI
- But they were pretty scared about it.
A simplified definition of AI
Before we delve deeper into what generative AI is exactly (and yes AI and generative AI have different definitions), let’s step back and align on what we mean when we say the words ‘Artificial Intelligence’.
Here’s my everyday human definition influenced by a variety of sources:
Artificial intelligence, or AI as the cool kids say, is used to describe a computer system’s ability to perform tasks that would usually require human intelligence, such as recognising patterns or understanding natural language.
Still with me? Great, let us march on.
Artificial Intelligence is not new
As shocking as that headline might be to those firmly entrenched in the matrix systems of social media. AI is anything but the new kid on the block.
99% of humanity spent 66 years blissfully unaware of AI in their lives.
Until… can you guess what happened?
Yes, ChatGPT – the craze which none of us can escape dropped into our conscious minds in late 2022 starting the equivalent of a Pokemon card sale at Walmart stampede into our lives.
The thing is, artificial intelligence has been all around us, since 1956 in fact. Back in 56, at the Dartmouth conference in the USA, the first proof of concept of artificial intelligence was born. So, it has always been here, mostly in the shadows, but easy to access consumer facing tools like ChatGPT are a new way for us to interact with this technology.
AI is already used in lots of platforms, including popular learning systems to run tasks and make recommendations. It lives in your local streaming service, knowing which binge-worthy tv show or cult-like movie to recommend next.
Generative AI explained: The simple guide for humans
Nearly all of my writing in essence is answering my own questions, and this piece is no different.
Don’t think of me as an expert in this field at all. I’m a fellow explorer (who might be further down the rabbit hole than you are or not) sharing what I’ve discovered. So you can and should question what I share, just as you should in using any AI tools.
Anyway, back to our explainer.
During my research travels I found many explainers on generative AI.
None were better than the one showcased above by the team at the World Economic Forum. A little fun fact about this explainer and the whole WSE article, it was completely created by a generative AI tool.
I’m not sure whether to feel confident in the fact that the technology I’m talking about is able to perfectly describe what it is, or be deeply concerned that it’s able to do this. Perhaps, you can decide for yourself with the AI’s breakdown of what generative AI is vs ‘me’ the human.
I’ve always loved the popular Reddit thread “Explain it to me like I’m 5”, so that’s exactly what I’m going to do with this overarching definition of generative AI.
Imagine if your teddy bear read all the books in the world and could start telling its own amazing tales! That’s what generative AI is like. It’s a super-smart computer that gobbles up lots of information, learns from it, and then uses what it’s learned to create new, exciting things when you give it a starting idea.
How was that?…
Let’s get a little more detailed to unpack exactly how generative AI learns, how you as a human can interact with it and how it creates new content:
1. How generative AI forms a database of knowledge
Think of generative AI as a very, very, very eager learner.
It “reads” lots of text from all over the internet, like websites, books, and articles. As it reads, it takes notes in its special notebook (its “database”). But instead of writing down everything word for word, it’s trying to understand the meaning and patterns in the sentences, like which words often go together and how sentences are typically structured.
So, it’s kind of building a big jigsaw puzzle from all the things it reads.
2. How humans can interact with generative AI with prompts
After our AI has soaked up all the knowledge it can, it’s ready to start sharing.
But to do so, it needs a little nudge to get the ideas flowing. That nudge is what we call a “prompt.” A prompt is a question or a subject you want the AI to talk about. If you were to say, “Make me laugh with a joke about a banana,” “a joke about a banana” is your prompt (massive fan of bananas, fyi – the fruit of the gods).
Think of this like cooking with a recipe.
You (the chef) choose a recipe (the “prompt”), and then the AI (the kitchen assistant) uses its knowledge of flavours, ingredients, and cooking methods to whip up a delicious dish (the response). Your chosen recipe guides the AI, but the final dish is uniquely created by the AI using its knowledge.
I hope that dish is bananas infused!
3. How generative AI creates new content for users
Now, when our AI receives your recipe (or prompt), it doesn’t simply follow it word for word. Instead, it creates a fresh, exciting, and related dish based on its vast cooking knowledge.
For instance, if you give it a recipe idea like “make a dessert with bananas”, it might whip up a detailed description of a new, innovative banana dessert you’ve never heard of. It uses the “flavours” and “cooking methods” it has learned from all the recipes it “read” to create this new dish.
It doesn’t remember the exact recipes it “read”, but uses the concepts and techniques it learned to create something new. So, it’s like the AI is a creative chef who can take a recipe idea (prompt) and cook up a fantastic new dish (content) that’s entirely it’s own!
And that’s it! That’s how generative AI works in a nutshell!
You’ve joined the cult
Great work! You’re now equipped to take on our AI overlords in the game of life.
Don’t forget, continuous education in this space is what will help each of us better navigate, regulate and accelerate generative AI for the good of our society.
Before you go… 👋
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