In January, OpenAI’s conversational platform, ChatGPT-3, became the fastest-growing app in internet history. This is just one indication of growing curiosity about GPT (generative pre-trained transformer) and other chatbots in the past few weeks. As one of the first learning professionals to see the potential of conversational AI and one of the few designing the applications for years, I’m excited to see the recent attention paid to this engaging technology.
In my book, AI in Talent Development, I outline several ways chatbots can be used as part of a robust learning experience, and ChatGPT-3, the third version in OpenAI’s ChatGPT series, demonstrates most of them. When ATD asked me to write a post on this subject, I struggled to find the value I could add to the exploding conversation. I decided to do what people say I do best: Give you the bottom line and point the way towards practical applications. Let’s start with the basics.
How ChatGPT-3 WorksChatGPT operates on an autoregressive model. It’s not as complicated as it may sound. A transformer is a program, model, or algorithm that converts code into something else—in this case, human language. The autoregressive part means the software uses prior events to predict the most likely future events, which is what your brain does all the time. It allows ChatGPT and similar applications to simulate a conversation between two humans. Learn the two keys to making an application like this work:
1. Natural Language Programming
Natural Language Processing (NLP) allows the bot to recognize input through human speech or writing, eliminating the need for menus or code to engage with it. This same ability enables the bot to reply through text. Before the development of NLP, most chatbots were menu-driven, and the bot responded by selecting the best fit from a database of pre-written options. Conversational AI represents a new way for humans to use computers; it’s a user interface requiring less hardware and prior knowledge than any previous UIs.
!CAUTION! Don’t confuse Natural Language Processing with the pseudo-science term using the same acronym. Neural Linguistic Programming is widely disproved and an invalid practice.
2. Massive Training Datasets
Like any neural network (including your own), AI models must be effectively trained using a technique called deep learning. Quite frankly, the stunning capabilities of ChatGPT-3 are nothing new. As David Chalmers points out, there is no new technology here. There are many bots with similar abilities, and I described them in detail in 2020. How this bot is trained and how well this approach works is innovative. First, Open AI used the largest training dataset, combining a database containing much of the internet, a huge library of books, and Wikipedia.
Then, after refining the bot in-house, Open AI released it free to the world. As we all started to play with it, we were training it further for them. Think of it as a crowd-sourced training effort. The sheer size of the training database resulted in what everyone always expected: Impressive results that can mimic human expression so well it is hard to tell a machine generated it. However, there continues to be an underlying problem: Chatbots are only as good as their training (like us humans). If you consider the source of GPT’s training, you can see why it sometimes makes mistakes.
What Can We Do With ChatGPT-3?Because this product is still being explored, there may be new use cases by the time this post publishes. Below are a few applications that can save time and make your work as a learning professional more efficient and productive.
If you ask the bot to write a paragraph introducing a subject, it comes back almost instantly with plausible, grammatically correct text. Because its training included unvalidated sources like the internet and Wikipedia, some of the content it produces must be corrected. Still, you can get excellent first drafts and refine your content from there.
Looking for a “Reader’s Digest” version of a book or article? Paste the text into a prompt to ChatGPT, and it returns a nice summary that should hit most of the highlights.
Write and Troubleshoot Computer Code
Because ChatGPT was built to analyze and produce output in human language, it is also great at computer languages. Programmers are using it to troubleshoot code. It can even generate new code if you ask it to develop a new capability.
Far more effective than other translators out there, ChatGPT can take a website or article and translate it into another language.
Write and Grade Quizzes
You can feed your content into GPT and ask it to generate a quiz with answers. Or, give it a general subject, like world history, and it will do the same. Feed your student’s quiz responses into GPT, and it will grade them (even essays!).
I asked GPT to create a game teaching sixth-grade students about the solar system, and the bot came back with a fun adventure through space.
Improve Your Writing
I didn’t do this for this article, but I could have asked GPT to review my draft and suggest improvements.
I asked the bot to provide a list of current peer-reviewed studies on chatbot use in education using APA style and received a properly formatted list.
Why Does ChatGPT Have Some People Worried?While most of the comments about GPT are positive, you will find a few educators deeply concerned about this new tool’s capabilities.
Mimicking Human Writing
Teachers are worried about GPT’s ability to write plausible text reading like a human created it and write in a known author’s style. A student could ask the bot to write a paper in the same style as one of their previous works, and it would be hard to tell the GPT paper wasn’t an original student effort. But, again, this mimicking ability is nothing new. AI has generated art in the style of great artists for years. ChatGPT applies the same predictive approach to language.
ChatGPT Makes Mistakes
Another concern is the bot’s ability to present false information so convincingly that some users forget to validate the response with research. For example, I asked the bot to calculate the mean of five numbers, and the result was interesting. I received a detailed explanation of the statistical definition of “mean” and how to calculate it, which I did NOT request. However, the bot added the five numbers incorrectly.
To be fair, ChatGPT wasn’t built to perform math problems. But it didn’t tell me that or report the result might be incorrect. Like any willing assistant, it did its best to provide an answer. If I had been a student relying on GPT’s help, I would have been wrong. The reason for most of these mistakes is the same reason that it is such a stunning improvement in the chatbot experience: It’s primary sources of information are the internet and Wikipedia.
I asked Vince Han, one of the pioneers in building chatbots for learning, to sum up the challenges presented by GPT’s new capabilities, and here’s his response:
“One of the effects of ChatGPT & increased quality in Artificial Intelligence in general is shifting the skills users need. For example, most users have developed a skill for how to search which is knowing how to craft keywords and how to sift through search results. Now, people will need the skill of discernment, or learning how to decipher truth and views from a chatbot that provides what reads like a definitive answer. So, from a performance support perspective, yes, one can now get an immediate response to a question but how accurate and relevant that response is will be up to them to determine. “
As educators, we must now confront a problem that has been boiling for decades—the decline in critical thinking across most domains, demographics, and workgroups. In my opinion, ChatGPT makes this gap more visible and increases the urgency for closing it quickly.
Closing ThoughtsBecause Microsoft owns the license for the exclusive use of the model, we’ve all been working for them, revealing exciting use cases that may find their way into AI-enabled Microsoft products. For now, the platform consists of both free and professional versions. It’s an excellent way to begin learning about the promise of AI and our place alongside it. As machine learning expert Santiago Pino says, “AI will not replace you. A person using AI will.”
Where Can You Learn More?
There are so many articles about this subject right now that I’ve limited myself to a few favorites:
- Under the Hood of Chat GPT With Myra Roldan
- How ChatGPT3 Impacts the Future of L&D in an AI World
- ChatGPT Has Educators Scrambling to Keep Up
- What Is ChatGPT and How to Teach With It
- What Is ChatGPT and Why Does It Matter?
- What Is ChatGPT? Is It the Beginning of the End?
- Ger’s Learning Notes #51 - ChatGPT