Artificial Intelligence (AI) stands as both a remarkable tool for efficiency and a complex legal and ethical minefield. As educators, we look at a future in which AI has the potential to act as an assistant—analyzing student data to create personalized learning paths and automating administrative minutiae. However, it is important to understand the "traps" that accompany these benefits. For schools and students, the intersection of AI and the law matters.
In my own research, I have discovered how implicit bias in AI outputs is influenced by the Internet ecosystem. Then there are hallucinations, such as the one that led me to park on a highway in Brooklyn. And AI slop? Regurgitated low-quality information – we can pick out the garbage someone shares in a lazy copy/paste content, but can our students? Deepfake bullying is on the rise, while English teachers ponder the challenges of AI plagiarism. And so on . . . .
As educators, our fundamental concern should be how legal implications play into all of this. Let’s unpack it in a practical way.
The Challenge of Algorithmic Bias
One of the most alarming ethical concerns is that AI is not a neutral arbiter of truth. While the technology itself is not inherently biased, the broad internet ecosystems it is trained on are, leading to "Algorithmic Discrimination."
A stark example of this is found in AI detection platforms. While often marketed to protect academic integrity, evidence has shown these tools are "near perfect" for native English speakers, yet falsely flag 61% of essays written by non-native speakers as AI-generated. For schools, relying blindly on such tools risks unfairly accusing multilingual learners of cheating, and highlights the need for good, old-fashioned analog interpretation by teachers rather than automated judgment.
Then there are my personal investigations during which I continue to see bias in prompt responses. Consider when I ask AI to show me a successful business person: The bias is glaring, typically generating images of middle-aged, thin, white males. The same holds true for high school athletes, for which the AI shows Black males. It is only when you insist on seeing diversity, both in gender and race and body type, that you begin to see realistic, balanced results.
Digital Citizenship and Behavioral Liability
The legal risks of AI extend to student conduct, particularly regarding bullying and the rise of deepfakes. Data suggests that nearly half of students and more than a third of teachers are aware of instances of school-related deepfakes.
The legal precedent is already apparent. In the 2024 New Jersey case K.W. and S.W. o/b/o A.W. v. BOE of the School District of the Chathams, a student was held responsible for using AI prompts to generate racially charged slurs. This ruling clarifies that hiding behind an algorithm does not absolve a student of liability. The federal Take It Down Act (2025) mandates that platforms remove non-consensual deepfakes within 48 hours, and introduces federal criminal penalties for those who share these. Schools must inform within their digital citizenship curriculums to ensure students understand the permanent risks of their online interactions.
Presenting on the topic of AI and the Law at FETC 2026, I was discussing a deepfake bullying incident when suddenly, a fire alarm sounded and all 10,000 in attendance had to evacuate the massive Orange County Convention Center. On my way down the escalator, two kind-faced teachers from a small rural town deep in Louisiana country approached me and remarked that it was their school from which the EdWeek article I had referenced had come. These teachers emphasized that while they were bound by FERPA restrictions of confidentiality, the media did NOT get the whole story right.
I could not have been more grateful for that fire alarm because they had illuminated such a significant point of emphasis to me: be critical of–in fact, don’t trust–everything you see online. Even from a reputable source such as EdWeek.
Deepfakes are one of the most profound issues with AI, for students and the adults who have also been victims. Leveraging the force of laws such as Take It Down and adopting policies reflecting the law can equip school communities with the best defense of provocateurs: fear of punishment.
Informing our communities about legal consequences and subsequent policies reinforcing these provides an inhibitor for most (not all). If we can reduce most issues because of this approach, isn’t it worth taking these proactive steps? The answer is obvious.
Redefining Academic Integrity
AI has fundamentally challenged traditional issues of plagiarism. Because generative models create unique content from existing materials, users do not "steal" work in the traditional sense. However, submitting AI-generated content remains a violation of school policy because it bypasses the true assessment of a student’s knowledge and schools must have electronic usage policies updated to reflect this.
Consider that this gray area has already led to litigation. In one instance, a parent in Massachusetts sued a school district after their child received a zero and detention for using AI on a project, claiming the tool was used only for research rather than writing. This reinforces the urgent need for clear, updated district policies that define the boundaries of "Fair Use" and AI assistance. Transparency tools such as AI Trust You, a free Chrome extension developed by Laguna Beach USD, also can help teachers and students be open and clear about AI use on assignments.
Of greater significance, education of the school community; families, teachers, and most importantly children is the true ethical goal necessary to avoid most instances of outright plagiarism and taking credit for work generated by AI.
Note, that I emphasize most, not all. Since the days of Socrates teaching in Ancient Greece, students have cheated because whenever there is assessment, there are those looking for short cuts.
Special Ed and the "Black Box"
In the realm of special education, AI presents a paradox. It can be a magnificent assistive technology, providing real-time text-to-speech and interactive tutoring that supports a student's Free Appropriate Public Education (FAPE). However, automated decision-making can be questionable. If an AI system monitors productivity without accounting for a student's legal accommodations—such as the need for frequent breaks—it may unfairly overlook those needs.
Educators must ensure that "smart" tools remain flexible enough to serve every learner. Most of this can be navigated through thoughtful prompts in an AI chatbot.
The "Human in the Loop"
To navigate these challenges, the U.S. Department of Education and legal experts advocate for a “human in the loop" approach. Before adopting AI tools, school leaders should ask critical questions:
- Does the system have inherent biases?
- Is student data being used to train third-party models?
- Are we protecting student privacy with tools that minimize data collection?
The processes for taking on AI legal implications are grounded in these questions, and as importantly, educating school communities, educators, parents, and students about proper use of AI. Likewise, enforcing consequences aided by legal protections such as the Take It Down Act are important ways to inform and inhibit bad actors.
The time to do all this is now; waiting and debating means children, minorities, and girls especially, will get hurt–an all too familiar pattern and a cycle that has to be broken as you finish reading this article.
