In the 21st century, it’s far more likely than not that you’ve heard of artificial intelligence (AI). There’s a chance you’ve even dabbled with making a few prompts as someone who is in a technological field or just someone who was curious. If you have used AI for any length of time, though, you might’ve noticed certain inconsistencies in regard to how AI responds to your prompts. For any person, when you ask them the same question 3 different ways, you’ll likely get the same answer 3 different times and an exasperated sigh. However, asking an AI and re-asking the AI is an essential part to getting the response desired.
The Rising Demand for AI Skills
This sentiment is especially true for AI prompt engineers, who spend large amounts of time training and relearning AI. AI prompt engineering is the science of structuring an instruction that a generative AI can then interpret and follow. However, despite the sweeping popularity of AI, a large majority of IT professionals vastly overestimate their proficiency with prompting AI.
As many as 2 in every 3 leaders simply wouldn’t hire someone without AI skills. Despite over 80% of these professionals thinking they can fit the criteria as an AI user, only a very slim 12% actually have the skills to effectively create prompts for AI. This has led to a 50% hiring gap in AI jobs and AI job roles, which only further drives home the importance of learning AI. So, what is keeping supply from meeting demand?
The AI Proficiency Gap
Simply put, 70% of global workers need to upgrade their AI skills, especially with prompt engineering. Most desk workers don’t know how to effectively use generative AI, much less get the most value from it. Mix in that these prompt engineers must use only trusted data sources in order to keep their company’s first-party data from being jeopardized. The combination of these factors is why 60% of IT decision-makers claim AI makes up their largest skill gap.
Key Prompt Engineering Techniques
When it comes to learning effective AI prompting techniques, there are a plethora to choose from. One of the most common with ChatGPT and other major generative AI is called ‘chain-of-thought’. The technique involves using intermediary steps to prove your answer along the way. It is like when you solve a difficult math problem, and show your answers in steps to prove there aren’t any flaws in your answer.
This technique is especially useful when the user wants to understand how the AI arrived at an answer or to attempt to correct an AI with an incorrect assumption. Another commonly used technique is generated knowledge prompting, which takes the answer from previous prompts in order to refine and specify future answers for a user. This technique is paramount so that an AI learns from previous corrections, and doesn’t keep regenerating the same incorrect answer. When it comes to generating images and videos with AI, you can even use textual inversion. This technique involves providing an AI with a training set of images and asking it to generate similar images.
The Importance of AI Education and Training
With such a variety of techniques to choose from, learning them all from scratch or attempting to relearn so many can be a daunting task. Fortunately, the rise of AI’s popularity has led to the rise of courses willing to teach AI. For beginners, there are Intro to AI and Advanced Prompt Engineering courses. For more advanced learners just hoping to refresh their memory, there are several courses as well. They have AI strategies for businesses and organizational leaders, as well as AI for specific purposes like financial management and marketing. Additionally, courses are available for other fields, such as education, entrepreneurship, and human resources.
Summing Up
The need for widespread AI literacy is undeniable. Bridging the AI skills gap is crucial for both individual career advancement and the overall progress of businesses and society. Regardless of where you currently are in your AI journey, your resume and your skillset can vastly improve after taking an AI course. By prioritizing AI education and embracing continuous learning, we can unlock the full potential of this transformative technology and ensure a future where AI benefits everyone.
