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Curious about how you can make the most of generative artificial intelligence (AI) in your training programs while keeping everything ethical and effective? Wondering what best practices can help you maximize its benefits and minimize any risks? Let’s explore how generative AI can revolutionize your approach to learning and development.
Generative AI is transforming the landscape of various industries, including the life sciences. By automating repetitive tasks, enhancing creativity and providing valuable insights, generative AI opens new doors for innovation and efficiency.
Joseph Weizenbaum created a talking computer in 1961.
Eliza was the first historical example of generative AI. Eliza was a talking computer program that would respond to a human conversation, using natural language and responses designed to sound empathic.
ChatGPT, the first generative AI tool that the world was introduced to, has been the hot topic since it hit the scenes in November 2022. According to OpenAI CEO Sam Altman, today ChatGPT attracts around 100 million weekly active users.
Although many have used generative AI tools like Google Gemini and Microsoft CoPilot, most are not really sure what they are.
To put it simply, generative AI involves advanced algorithms that can create new content such as text, images and music based on patterns and data they have been trained on. The most notable examples include ChatGPT, which generates human-like text, and DALL-E, which produces images from textual descriptions. These tools can be leveraged to develop more engaging and effective training programs, ultimately leading to improved learning outcomes.
However, right now the generative AI space is like the Wild West; you must tread lightly when incorporating generative AI into your organization as it requires careful consideration of various factors to ensure its ethical and effective use.
To help you better understand generative AI, it is helpful to compare it with traditional AI. Traditional AI was created during World War II by Alan Turing. Traditional AI focuses on recognizing patterns, making predictions and performing tasks based on predefined rules and data. These systems are designed to solve very specific problems by analyzing input data and producing outputs that are consistent with the data they have been trained on.
If you’ve ever gone through the Netflix library, you may have noticed the recommended programs for you based on your watch history – that’s traditional AI. If you’ve ever shopped on Amazon and were presented with images of items that other people purchased based on the item you are viewing – that’s traditional AI.
AI has silently integrated itself into our lives. So much so that a recent Pew Research study found that 44% of Americans believe they do not use AI regularly.
Generative AI combined with large language models, on the other hand, goes a step further by not only analyzing data but also generating new content that was not explicitly present in the training data. This capability allows generative AI models to create text, images, videos, music, code and other forms of content that are semi-original and human-like.
Let’s drill in a bit more to help ensure you grasp the differences. Table 1 shows four key differences between traditional AI and generative AI. This distinction is crucial as it opens new avenues for creativity and engagement that were not possible with traditional AI alone.
Let’s end this article with a reflection, and a look ahead. It’s not enough to read about actionable tasks and then set the article aside.
First, reflect on the sections of this article that resonated with you:
How might this impact your role?
What concrete steps can you take?
How can you shape AI implementation in your organization?
Then, stay tuned: We’ll have more on generative AI in the November 2024 issue of LTEN Focus on Training magazine, spotlighting key considerations and an action plan for implementing generative AI in your organization.
Myra Roldan is a technology thought leader, author and speaker with decades of experience in AI and disruptive technologies. Connect with Myra through https://linkedin.com/in/myraroldan.
