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Writer's pictureGlobal Youth Congress

Why Teaching AI in Education is as Important as Learning Excel in the 90s


Picture this: It’s the 90s, and businesses are transitioning from paper ledgers to spreadsheets. If you didn’t know how to use Excel, you were behind. Fast forward to today, and we’re facing a similar shift—but now, it’s Artificial Intelligence (AI) that’s becoming the new “must-know” tool. Just like mastering Excel became essential for job applications in the past, understanding AI will soon be just as critical for students entering the workforce.


But here’s the thing: while AI offers incredible opportunities, it also brings ethical challenges. How do we teach our students to use AI responsibly? And what are the risks we need to be aware of? Let’s dive into why this matters and how we can guide the next generation to use AI with care, ethics, and awareness.


The Problem: AI Skills Are the New Excel

Remember when knowing how to use Excel set you apart from others in the job market? That’s where AI is now. Companies are increasingly relying on AI for tasks like data analysis, customer service, and even creative work. For today’s students, knowing how to navigate AI tools is quickly becoming a baseline skill—one that could make or break their future career prospects.


However, unlike Excel, AI isn’t just a technical tool—it’s a decision-making powerhouse. That means students aren’t just learning how to input formulas or format cells; they’re interacting with systems that influence everything from hiring decisions to personalized learning paths. That’s where the ethical challenges start to emerge.


The Ethical Dilemma: Transparency and Bias in AI

As educators, our role isn’t just to teach students how to use AI—it’s to ensure they understand how AI works and the risks that come with it. One of the biggest ethical concerns is transparency in AI systems. Just like Excel functions can sometimes be hidden in complex formulas, AI often operates in a “black box,” making decisions that aren’t always easy to explain or understand. If students don’t know how an AI system works, how can they trust it?


Another key issue is bias in AI algorithms. AI systems learn from data, and if that data is biased, the AI will be too. This can lead to serious issues, especially in education. Imagine an AI tool that helps teachers grade assignments but is unknowingly biased toward certain groups of students. This could result in unfair assessments, limiting opportunities for some while giving others an unearned advantage.


That’s why teaching AI needs to go beyond the technical—students must learn to question how data is used, how decisions are made, and whether those decisions are fair.


The Risk: Data Privacy and Autonomy

When students interact with AI, they’re often sharing personal data—sometimes without even realizing it. This brings us to another pressing issue: data privacy and security. With regulations like the GDPR and CCPA, schools are becoming more aware of how personal data is collected and used. But students need to understand the risks, too.


If we’re not careful, AI tools in education could collect sensitive data on students—everything from their learning habits to personal information. And while AI can personalize learning experiences, it’s important that students maintain autonomy over their own decisions. We don’t want AI systems to take away their ability to choose what and how they learn, which is why human oversight is crucial. Teachers need to guide AI use, ensuring it supports students’ independence, rather than stifling it.


The Solution: Educating with Ethics at the Forefront

So, where does this leave us? Just like we taught Excel with a focus on practical skills, we now need to teach AI with a focus on ethics and awareness. Yes, students need to understand how to use AI tools—but they also need to know the potential risks and how to navigate them responsibly.


This means reinforcing the technical side of AI with strong moral values. Students must be equipped to question AI decisions, recognize bias, and prioritize data privacy. It’s not enough to be proficient with AI; they need to be thoughtful, critical users of these systems. And most importantly, we need to ensure that human oversight is always part of the equation, so that AI doesn’t replace human judgment but rather enhances it.



Conclusion: AI Education Needs Ethics, Now More Than Ever

Teaching students to use AI is no longer optional—it’s essential. But with this power comes responsibility. Just as Excel skills helped people succeed in the past, AI skills will shape the careers of tomorrow. The key is making sure students don’t just learn the tools, but also understand the ethical landscape surrounding them.


By focusing on transparency, addressing bias, protecting data privacy, and ensuring students maintain autonomy with human oversight, we can prepare them for a future where AI is a major player in their professional lives. The goal is clear: equip students with the knowledge to use AI not only effectively but also ethically. Because when technology and ethics go hand in hand, we build a future where innovation serves everyone.


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