ChatGPT and other AI-powered tools have come to the forefront of the news over the past few weeks. As it grows in popularity and use, reliance on these tools may become commonplace. That said, there are a few pitfalls to the technology, and it should always be viewed as a tool first and foremost. There are a few things that it is really good at doing and a few things that it is not very good at.

Earlier this week, there were reports of a Lawyer who used ChatGPT to prepare a court filing. The case is actually a really good example of what to do and what not to do. ChatGPT can help to format text; it can help generate ideas and sentences for the author to use. However, it is not a replacement for human expertise. The filing was formatted well and made sense. However, the cases that ChatGPT used in the filing did not exist.

Large Language Models (LLMs) like ChatGPT may seem somewhat intelligent when interacting with them. However, what they are really doing is predicting the most likely next word based on the inference of your input. In short, they know what the answer SHOULD look like, so they give you words based on what the correct answer pattern would be. This is a gross simplification of the actual process but makes it a bit easier to understand ways to make the technology work for you.

Generate Copy Quickly

ChatGPT excels at creating sentences that make sense and are formatted appropriately. Give descriptive prompts on the who, what, when and where of events and have the AI generate full paragraphs in seconds.

A prompt like

Give me a paragraph about a fun event for 4-H horse camp. There will be free food, games and horse based activities for those with and without horses. It will happen on June 8, 2023 from 4-6 p.m. at 123 Main St in Raleigh, NC

Can generate interesting copy. For instance, that prompt returned:

Attention young horse enthusiasts and adventure seekers! Join us for an action-packed afternoon at the 4-H Horse Camp event on June 8, 2023, from 4-6 p.m. Located at 123 Main St in Raleigh, NC, this incredible gathering offers a range of horse-based activities, including grooming, short rides, and horsemanship lessons. But wait, there’s more! Enjoy free food, exciting games, and the chance to make new friends. Don’t miss out on this thrilling celebration of horses and fun!

While that is an enticing paragraph that has all the basic information provided in the prompt, ChatGPT also returned a number of activities in specific that we may not be providing. So while you can definitely get great content quickly, it needs to be heavily edited before release.

Create Outlines

You can also use ChatGPT to create outlines for basing your content. ChatGPT is great at coming up with quick, detailed and easy-to-follow outlines. Like with the example above, use the tool for broad strokes, then refine as needed.

If I wanted to create a post about the previous event, I might try a prompt like

Create an outline of a post about an upcoming 4-H Horse Event

The returned information was,

1. Introduction
   1. Grab attention: Exciting announcement of an upcoming 4-H event
   2. Briefly introduce the purpose and nature of the event
   3. Mention the date, time, and location to build anticipation
2. Event Overview
   1. Highlight the theme or focus of the event
   2. Provide a brief description of the activities and offerings
   3. Emphasize the inclusive nature of the event, catering to participants with and without horses
3. Key Features
   1. Detail horse-based activities available for participants with horses
   2. Describe engaging activities and games for participants without horses
   3. Highlight educational aspects, such as horsemanship lessons or workshops

Alternatively, you could have it create a to-do list of everything you need to do to prepare for the event. Just make sure you edit!

In general, ChatGPT can be a great tool to enable the creation of the content you would like to make, and make sure that you are editing and reading what it is generating. It’s important to note that large language models are not explicitly programmed with rules or specific knowledge. Instead, they learn to generate text by discovering patterns and correlations in the training data. The models do not possess real-world understanding or knowledge beyond what they have learned from the training data. Therefore, caution should be exercised when relying on large language models for factual accuracy, and experts should validate the output.