Presence the foundation of AI Resistant Academics

Let’s start by taking a look at what the first pillar of an AI-resistant assessment looks like, and that first of the five pillars is presence. In the absolute simplest terms, functionally speaking, given what modern technology can do, the only way you can guarantee that a student actually did the work they supposedly did is if they actually did it in front of you. In the short term, things like videos showing them doing the work might still seem viable, but even those are rapidly losing their reliability. With only a few lines of speech and a few pictures, students can already create digital avatars powered by AI that can emulate convincing videos of themselves supposedly completing an assignment. While this technology is not yet widespread, it already exists. Because of that, the most reliable way to ensure that a student genuinely did the work is if they genuinely do it in front of you. Seeing the student make the diagram themselves, write the paper, or answer the question is foundational to ensuring that AI was only involved to whatever degree the teacher allows.

Presence, in the 21st-century academic context, can therefore be defined as the real-time, physical, in-person participation of the student in the learning or evaluative process under direct observation or supervised conditions. We already recognize the importance of this principle in high-stakes testing environments such as the SAT, Praxis, MCAT, and Bar Exam, where students cannot simply phone the exam in and strict security measures exist to ensure that the person taking the test is the one actually doing the work. Those fields already understand that when knowledge must be proven beyond doubt, presence is non-negotiable. Without it, the assessment quickly loses its meaning.

When students are assigned work, many times their mind immediately goes to the question: what is the fastest way to get this done? Unfortunately, that mindset is partly what underpins the academic cheating we have seen so prevalently—especially in higher education—where students, driven by the desire simply to “get things done,” are not actually engaging with their own learning. Instead, they complete tasks by the fastest and most efficient means possible, not realizing that it is the process itself they are supposed to be after.

A degree is useless if you did not earn it. Functionally, the purpose of a degree is not to hold it in one’s hand. If I wanted to hold a degree from Harvard, I could simply print out a template and write my name on it. But everyone would immediately understand that doing so is meaningless because the degree would carry no authenticity behind it. A degree is valuable because of what it represents. It represents the accomplished learning of the individual. That is true for every diploma, certificate, and graduation credential—from kindergarten through a doctorate. At a very practical level, if you do not actually know the material, then the paper in your hand is worth about as much as the paper it is printed on. You might spend twelve years moving through elementary, middle, and high school, and perhaps four years and tens or hundreds of thousands of dollars going through college—but those years only provided the opportunity to learn. They never guaranteed that you actually did learn, especially if a student begins outsourcing their thinking to a machine.

Every teacher has had that moment where a student proudly turns in an assignment that is nothing more than the top result on Google. In more recent times, it is not even a copy-paste job from Wikipedia but directly from ChatGPT or another AI tool—sometimes still including the prompt chain or the AI’s enthusiastic preamble. This is not understanding. It is not even a particularly convincing attempt at pretending to understand. Just because an answer is correct does not mean the student actually understands it. My two-year-old loves to sing the “count by fives” song from Mother Hen. She can recite the sequence perfectly, but while she is factually correct, she has no comprehension yet of what it means to count by fives. She is repeating something that sounds right, but she has not actually learned what she is doing. Presence helps solve this problem because it allows the teacher to see the student’s thinking unfold in real time. When students are writing, drawing, explaining, or constructing something directly in front of the teacher, it becomes far easier to observe whether understanding is genuine or merely rehearsed repetition.

However, while presence dramatically reduces the opportunity for AI substitution, it does not necessarily eliminate all AI use—and that is not always the goal. The important question for the teacher becomes: what exactly are you trying to assess? Some assessments are straightforward. If you are trying to determine whether a student can spell a word correctly, then they clearly do not need AI assistance. If the goal is to test memorization, internal skill development, or independent reasoning, AI involvement should be minimal or nonexistent. But there are other situations where AI may actually be a useful aid to the student without undermining the learning objective. For example, if students are being asked to identify patterns in words or explore different suffix structures, an AI tool might help them locate examples more efficiently. Dictionaries are not typically organized by suffix patterns, but an AI system can quickly generate lists of words that share similar endings, allowing students to analyze them more effectively.

This is where the MAPS scale becomes helpful. Do you want your students using AI only for spelling or grammar checks? That would correspond to Level 1 on the MAPS Scale. Are you allowing them to work more collaboratively with AI, where both the student and the AI contribute to shaping the work? That begins to approach Level 3, what I refer to as Synthescribing.

Functionally speaking, what I have observed in both myself and my students is that AI does not make someone inherently smarter. However, if the tool is used correctly, it can allow a student’s natural abilities to shine more quickly and sometimes more clearly. A student who is already a strong writer can use AI feedback to refine their clarity without losing their voice. A student who struggles with writing, however, will not become a better writer simply by letting AI do the work; it will only mask the underlying weakness. Presence therefore becomes the foundation of authentic assessment. It allows teachers to observe real thinking, ensures that the student—not a parent, a contractor, or an AI system—is actually doing the work, and provides the structural conditions in which responsible AI use can still exist without replacing the student’s own intellectual development. In short, presence does not mean rejecting technology. It means ensuring that the human being remains the one doing the thinking. AI can support that process when used appropriately—but the student must always remain the one at the center of the work, and they must show up in person to do that work.