By Gabrielle Uwa, Junior Reporter
In classrooms around the world, a quiet revolution is taking place. Artificial Intelligence (AI), once confined to science fiction, has stepped boldly into the everyday life of students and educators. With tools like ChatGPT, Grammarly, and various AI-based research assistants, students can now compose essays, generate citations, summarize articles, and even brainstorm creative ideas within seconds. What was once a slow and deliberate process of writing, revising, and reflecting is now faster and sometimes more polished than ever before. Yet, with this newfound convenience comes a host of complex questions. Who truly owns AI-generated work? Can students claim authorship over something created by an algorithm? And how do schools protect student privacy when technology quietly collects their data behind the scenes? These questions lie at the heart of the growing debate over the legal and ethical use of AI in education. Understanding the legal perspectives surrounding AI in schoolwork is essential to ensuring that progress does not come at the cost of integrity, fairness, and trust.
The first and perhaps most urgent legal concern is academic integrity and intellectual property. Education is built on the principle that learning must be genuine, reflecting a student’s own understanding and effort. When a student submits work created by an AI system, the line between assistance and dishonesty becomes blurred. Most schools have long-established policies on plagiarism, but these were written for an era of books, essays, and human authors, not algorithms that can generate unique text in seconds. Legally, copyright law offers little clarity. In most countries, only humans can hold copyright, meaning that AI-generated content technically belongs to no one. This grey area raises questions about ownership and accountability. For instance, if a student submits AI-produced content that contains factual errors or copyrighted material, who is responsible, the student or the AI developer? Because legislation has yet to catch up, universities and schools have created their own policies to fill the gap. Many institutions now define uncredited AI use as academic misconduct, like plagiarism. These rules aim to protect the authenticity of scholarship, reinforcing that the true purpose of education is not perfection, but personal growth through effort and understanding.
However, legal issues surrounding AI go far beyond questions of authorship. Another major concern involves data privacy and consent, which form the backbone of ethical digital learning. Every time a student uses an AI tool, they may unknowingly share sensitive information, such as names, essays, or behavioural data with private technology companies. These platforms often collect data to improve their algorithms, but this process can expose users to risks they may not fully understand. Laws such as Canada’s Personal Information Protection and Electronic Documents Act (PIPEDA) and the European Union’s General Data Protection Regulation (GDPR) set strict standards for how organizations can collect, use, and store personal data. Schools and universities that adopt AI systems must ensure they comply with these laws by obtaining proper consent, securing data storage, and maintaining transparency. Yet compliance can be difficult in practice. Many AI tools are cloud-based and store data in servers located in other countries, where privacy laws differ. This creates a legal challenge: even well-intentioned educators may inadvertently expose student data to international privacy risks. The legal obligation, therefore, extends beyond convenience; it demands vigilance and due diligence from both institutions and students.
Closely linked to privacy is the question of transparency and accountability. AI systems are often described as “black boxes,” meaning that their decision-making processes are not fully understandable even to their creators. When a tool suggests an essay topic, provides feedback, or generates a written response, users have little insight into how or why those results were produced. This lack of transparency poses legal and ethical problems, especially in education, where fairness and clarity are fundamental. If an AI system provides incorrect information or biased results that harm a student’s performance, can the developer or the school be held liable? Current laws provide few answers. Governments around the world are beginning to explore frameworks for AI accountability, such as the European Union’s Artificial Intelligence Act, but educational settings remain a grey zone. To address this, schools must establish clear policies outlining the acceptable use of AI, along with disclaimers that clarify its limitations. Legally and ethically, both transparency and accountability are essential for maintaining trust in technology-driven learning.
Another crucial legal and moral issue is equity and access. The digital divide - the gap between those who have access to technology and those who do not - has long been a concern in education. AI risks widening that gap even further. Students who can afford premium AI tools or have high-speed internet connections may gain an even more significant advantage over those who cannot. This imbalance raises potential violations of human rights and education equity laws, which guarantee equal access to learning opportunities. Additionally, algorithmic bias within AI systems can unintentionally discriminate against certain groups. For example, AI language models trained primarily on Western or English-dominant data may produce content that favours specific cultural norms, penalizing students from other linguistic backgrounds. From a legal standpoint, such biases could breach anti-discrimination laws or educational equity mandates. Schools, therefore, carry a legal and moral responsibility to ensure that AI tools are tested, inclusive, and accessible to all students, regardless of their background or economic status.
Despite these challenges, AI also holds the potential to enhance learning when used responsibly. It can help students overcome language barriers, improve writing skills, and receive instant feedback. Legally, the goal is not to ban such technology but to regulate it in a way that upholds academic and ethical standards. Policymakers are beginning to explore solutions, including requiring AI transparency in education, mandating data protection audits for educational technology, and integrating AI literacy into the curriculum. These steps would help students understand how to use AI ethically, safely, and legally. The challenge lies in striking a balance between innovation and accountability between embracing progress and preserving the core values of education.
In conclusion, the legal perspectives on AI in schoolwork reveal a field that is as exciting as it is uncertain. Artificial Intelligence has the power to reshape how students learn, write, and think, but it also challenges the very foundations of academic integrity, privacy, and fairness. Laws on plagiarism and copyright struggle to define authorship in a world where machines can “write.” Privacy legislation must evolve to protect students from invisible data collection. Equity and fairness demand vigilance to ensure that technological advancement does not deepen inequality. To navigate this landscape, collaboration between lawmakers, educators, and technologists is essential. Clear policies, transparent practices, and strong legal protections can help ensure that AI serves as a tool for learning rather than a shortcut through it. Ultimately, education should empower students to think critically; not just to generate words, but to understand their meaning. In this sense, the true challenge of AI in schoolwork is not simply legal or technical, but profoundly human.