Problems With AI in Education: Risks and Practical Responses

The main problems with AI in education are inaccurate answers, work that conceals whether a student understands the material, privacy risks, unequal access, and unclear assessment rules. Practical responses begin with the learning goal: decide what students must do themselves, what assistance is allowed, and how someone will check the result.

Tools such as fenbs can retain the agreed teaching or study rules and lessons from using them. A shared record helps a teaching team apply the same boundary across sessions. It does not verify educational claims, grade students, or make a tool suitable for student records.

When does assistance get in the way of learning?

A completed answer and a learned skill are different outcomes. If an assignment asks students to build an argument, having AI produce the argument can remove the practice the assignment was designed to provide. The immediate result may look strong while leaving the learner unable to repeat the work independently.

Match assistance to the skill being practiced. If recalling a formula is the goal, start without assistance. If critiquing explanations is the goal and AI use is permitted, students might compare an AI explanation with a textbook and identify mistakes. Explain that distinction before the activity rather than expecting students to infer it.

• Ask students to make an initial attempt before requesting feedback.
• Require an explanation of the reasoning, not just the final answer.
• Include a similar problem completed without the assistant to check understanding.
• Invite students to identify which suggestions they rejected and why.

These are possible teaching choices, not universal rules. Cornell’s ethical AI guidance↗ (opens in a new tab) encourages critical evaluation of AI use and its implications for teaching and learning. Choose an activity because it serves a learning outcome, then check whether it did.

How should students handle convincing but incorrect answers?

Separate a useful explanation from evidence that the explanation is correct. Fluent prose can contain a false premise, a fabricated reference, or an answer to a slightly different question. A student should be able to point to the assigned material, calculation, or original source that supports a claim.

For example, say an assistant explains a biology process using an appealing analogy. Ask the student to mark where the analogy stops matching the actual process. That check makes the explanation an object of study instead of an authority. In math, work through the intermediate steps and test the result against the original problem.

Keep a simple distinction in study notes: suggested, checked, or unresolved. Open every source you intend to cite and read the relevant passage in context. An AI brain can preserve that distinction between sessions, but storing a claim never makes it verified.

What privacy questions come before a classroom activity?

Before asking students to use an AI service, establish which tool the school permits, what information may be entered, and who reviews the arrangement. A publicly accessible account is not automatically an approved place for student work, grades, accommodation information, or details about another student.

The US Department of Education’s education technology privacy resources↗ (opens in a new tab) include guidance and a terms-of-service checklist for evaluating online services. Its online educational services guidance↗ (opens in a new tab) explains that FERPA, the federal law protecting education records, can affect disclosures to providers. An institution must evaluate its own facts and applicable requirements; an instructor should not infer permission from a general AI policy.

• Use institution-approved services and the approved account configuration.
• Prefer invented examples when real student information is unnecessary.
• Check what the service collects, how information is used, and who can access it.
• Give students a clear route to ask about access, privacy, or an appropriate alternative.

Keep the project coordination record separate from protected student records. A teaching team can discuss a general lesson, such as unclear assignment directions, without copying identifiable student work into another tool.

Why do assessment rules need to be specific?

“Use AI responsibly” leaves too much unexplained. Students need to know whether they may ask for an explanation, obtain feedback on their own draft, generate text, or use a code suggestion. They also need to know how to disclose permitted help. An instruction should name activities rather than assume everyone understands a broad label.

Cornell’s academic integrity guidance↗ (opens in a new tab) recommends communicating policies in syllabuses and assignment instructions. It also advises against relying on automatic AI detection to establish integrity violations because such tools cannot provide definitive evidence. A detector score should not replace your institution’s process for reviewing a concern.

Design opportunities to see the process: draft discussions, short explanations, annotated sources, or demonstrations of a method. Choose forms that fit the subject and preserve approved accommodations. A student’s ability to explain a result gives you different information from the polish of a submitted document.

When the team changes a boundary, retain who approved it and which assignments it affects. fenbs Decisions and rules can keep that scope available to connected assistants helping prepare future teaching materials.

How do you respond to unequal access and inconsistent support?

Do not build an essential assignment around an assumed personal subscription, a particular device, or unlimited internet access. Check what every student can actually use through the institution. If a tool is optional, explain a workable path for students who do not use it.

Check accessibility with the people and services responsible for it. A tool that produces readable text may still have an inaccessible interface or provide unreliable support for a particular learner. Avoid treating AI as a replacement for approved accommodations, specialist instruction, or access to a teacher.

Start with one bounded activity and review its results. Ask whether students understood the material, could follow the rules, and could complete the work using the resources actually available. Record a concrete lesson, such as adding an example of acceptable feedback, rather than a vague conclusion that students need better judgment.

How to do this with fenbs

1. Create a free account and add a project for one teaching activity or your own study routine.
2. Write the approved AI-use boundaries in Decisions and rules. Include their scope and the source of the instruction.
3. Add tasks for checking learning materials, clarifying assessment directions, and reviewing the activity. Keep student records in approved school systems.
4. After the activity, save a nonidentifying lesson and the next step. Ask any connected assistant to read the rules and lessons before helping again.

fenbs does not provide a learning management system, an AI detector, or a student privacy review. Use the school’s required systems for assessment and student data. A personal checklist may be sufficient when you only need to remember the boundary for one study session.

What should you explore after identifying the problems?

For ways to structure permitted activities, see AI in education workflows, conversational AI in education, and uses of AI in education. The task is to choose one use with a clear learning purpose and a visible check.

The review habits in using AI at work also help a teaching team, while the AI governance guides cover broader responsibility questions. Keep the next change small enough to evaluate, then preserve what the activity taught you.