Using GPT Chats and Generative Artificial Intelligence in L&D

Create new content, images and sounds in seconds

As artificial intelligence (AI) increasingly affects how we work, learn and live, newsworthy advances in AI have grabbed the headlines, including Chat GPT and other generative AI features. While generative artificial intelligence is still in its infancy, this article explores what it is, how it works, and how it can be used in learning and development (L&D).

What is generative AI and how does it work?

Generative AI is a type of machine learning that generates new outputs such as text, images or sounds [1] based on the content he was trained on. Generative AI works with Generative Adversarial Networks (GANs) [2], which are deep learning capabilities for creating new content. GANs were created in 2014 by Ian Goodfellow and his colleagues to include two neural networks: a generator that creates new content and a discriminator that evaluates new content. The two neural networks operate on the basis of a zero-sum game, where the win of one neural network is the loss of the other. The generator constantly tries to fool the discriminator and the discriminator tries not to be fooled by the generator, and both continue to train on the newly generated data. Some examples of generative AI include Chat GPT, which generates text; MidJourney, which generates images; Murf, which generates sound; and Codex, which generates new code.

Examples of generative artificial intelligence

GPT chat

Chat GPT is an open source artificial intelligence model generating language developed by OpenAI. Chat GPT scans millions of pages of content, including articles, books and Wikipedia, and produces text in seconds that is highly coherent and realistic. GPT Chat uses deep learning to analyze massive amounts of text data, learn patterns, and mimic the structure of natural language. This allows Chat GPT to generate realistic and expressive text when tuned for specific tasks. Chat GPT works with a text prompt where a human provides the prompt and Chat GPT generates content based on the prompt. To test this, I asked Chat GPT to write an article on “The Impact of Chat GPT on Learning and Development”, which he delivered in seconds. Below is an excerpt from the article’s conclusion:

GPT Chat has the potential to revolutionize learning and development. With its ability to provide on-demand personalized learning, timely and relevant information, improved efficiency and improved accessibility, Chat GPT has the potential to change the way we learn and develop new skills. However, it is important to carefully consider the challenges associated with using Chat GPT and take appropriate measures to ensure the accuracy, reliability, privacy and security of the information provided. As the field of learning and development continues to evolve and grow, it will be exciting to see how Chat GPT continues to shape and reshape the field.

It is clear that the content is coherent and meaningful. However, GPT chat is still a generative AI with limitations and biases; it often provides the wrong answers and lacks context and nuance, so it’s important to be careful when using it to create learning content, images, and microlearning modules.

MidJourney

MidJourney is a generative AI ability that generates new images based on a challenge. For example, prompts could be “a group of diverse people working on a joint project shot from above”, “a picture of a woman sitting at a computer” or “Santa Claus riding a bicycle”. After being prompted to describe an image in natural language, Midjourney takes about a minute to generate four image options. Examples of uses for this capability include visuals for educational content, presentations, illustrations, and new creative image ideas.

Murph

Murf is a generative AI capability that generates studio-quality voiceovers in a variety of human voices in minutes. Such AI-generated voices can be used in learning modules, presentations and podcasts, among others. Murf allows the user to define the gender, accent, pitch, stress and interjections of the voice. Using natural language at the prompt, the user can describe the voice they need from over 120 text-to-speech voices and over 20 languages. Murf can be quite useful in generating voice comments for use in teaching and development, including comments for training modules, presentations, websites and HR onboarding videos.

Code

Codex is a generative AI that can write code and can be used to create or improve websites and write code for software and technology development. Codex handles more than twelve coding languages and can translate commands from natural language into code. This is quite powerful and useful in L&D, as using generative AI like Codex can help instructional designers create landing pages and microlearning modules without knowing how to code.

Conclusion

According to McKinsey [3]The relationship between humans and machines has been constantly optimized since the Industrial Revolution more than 150 years ago. There are three types of economic activity: production, transaction and interaction. Machines and technology in manufacturing have expanded production and digitization has improved transactions. Today, generative AI can greatly impact interactions by moving closer to human involvement, such as customer service and education. Generative AI can be powerful in many industries, including education and development, where it can help generate learning content, images, and micromodules.