AI is making some of the traditional academic skills easier to outsource. Students can now have an AI system summarize a chapter, explain a hard concept, even come up with ideas in seconds. This alters the value of some skills, not the importance of education. Instead, it asks a more pertinent question: what do students need to be good at in a world where many tasks are performed by machines?
Knowing When Not to Trust the Answer
A key skill students can learn is how to understand when an AI-generated response should be investigated. When information is incomplete or outdated or even incorrect, AI systems can still offer confident explanations.
Students should be taught to check claims and not accept an elaborated answer as proof. Validating the source of information to find supporting evidence is a skill that is useful even outside of school.
Asking Better Questions
AI has also made the quality of a question more important. An unclear request tends to get a generic response, while a specific question yields a useful answer. There is a learning opportunity in the process of defining a problem before asking an AI system to solve it. They should:
This is not simply about learning prompt engineering. It is about thinking through a problem before looking for an answer.
Understanding How Money Moves
Financial education takes on a different importance when students can access sophisticated financial information and automated tools at an early age. Before they gain significant financial experience, students may encounter:
It is thus essential that students learn about interest, debt, risk, taxes, investing, scams, and online financial security so that they can apply their knowledge to the real world. A student pursuing an AIU finance degree, for instance, may end up working with technologies to automate analysis, but still need to understand the financial principles used in the calculations. The objective is not to turn every student into a financial expert. It is to help them recognize the consequences of financial decisions and make informed choices about their financial future.
Writing Without Depending on a Machine
While AI can generate decent writing in a matter of seconds, students must grasp the structure and elements of arguments. Otherwise, they might be unable to identify if an AI-generated work actually supports a coherent argument.
Practicing various essay structures can help students to grasp the organization of evidence and explanations. With an understanding of why a structure functions, they can rely on AI for editing or brainstorming without having it define their entire line of thinking.
Building Skills That AI Cannot Easily Standardize
There is also a value in activities that involve students making decisions without a correct answer. Judgement is required for designing an experiment, negotiating a group project, presenting an unusual solution, or defending an unpopular position, and it cannot be boiled down to the retrieval of information.
In an AI-focused world, these experiences can enhance the relevance of education by exposing students to uncertainty. Not every answer exists in a database, and sometimes the “best” answer is dependent on a situation that cannot be captured by a simple instruction.
Becoming Comfortable With Change
Students entering the workforce in the next decade will likely face tools that do not yet exist. Their preparation for one type of technology may then be of less value than their ability to learn new technologies rapidly.
A student who can grasp a new interface, evaluate its functions, determine its shortcomings, and determine its application within their work has a real edge. They do not need to know every new AI application. They need enough technical confidence to investigate one when it becomes relevant.
Endnote
The best education in an AI-first era might not be about forecasting the next big thing. Rather, it is in teaching students how to make decisions when the next big thing is introduced.
