The Cardinal Review - Generated by Humanity

THE CARDINAL REVIEW

Sam Custodio

GENERATED BY HUMANITY

YOUR BRAIN & AI While AI use is inherently evil, keep in mind that there are uses of generative tools that are significantly less healthy than others. An overreliance on AI can foster or hinder critical thinking and dull imagination and clarity in thought.

Every time you outsource your brain to ChatGPT, Gemini, or any other AI program, consider the permanent damage you risk victimizing yourself to. A study from MIT proved that groups that use AI as a crutch experienced: much lower electrical connectivity in their brains than the brain-only group’s brains decreased perception of ownership of the writing lower recall of quotes from the essay they had written

STOP USING AI IF YOU CARE ABOUT YOUR ABILITY TO THINK! KNOWLEDGE ISN’T A PRIVILEGE! YOU SHOULD NEVER OPERATE UNDER THE ASSUMPTION THAT YOUR BRAIN IS INFERIOR TO AI!

“I <3 EM-DASHES” Psychology of Deskilling

AI is everywhere now. It can draft essays, solve equations, generate images, even brainstorm ideas. At first, it feels like magic. Tasks that once took hours—writing, coding, creating—can happen in seconds. It’s fast, it’s impressive, and it’s hard not to rely on. But with speed and convenience comes something subtler: a slow shift in how we think and work, sometimes called deskilling.

Deskilling doesn’t hit suddenly. It creeps in like water into cracks. Skills we once practiced—the ones that shaped our reasoning, memory, and creativity —can weaken when they aren’t used. Every time a tool finishes a task for us, a little mental effort is skipped. Over time, that little skip adds up, and abilities that used to feel natural start to feel harder.

Psychologists describe this as cognitive offloading. Humans naturally delegate mental work to tools. Calculators handle arithmetic, spell checkers catch errors, GPS finds routes. AI simply extends that delegation into more complex realms. Drafting paragraphs, troubleshooting problems, generating ideas—these can all be handled externally, leaving less space for the internal processes that once strengthened skills.

It’s easy to see in writing. A paragraph polished by AI might read perfectly, but the writer didn’t struggle with phrasing, organize ideas, or wrestle with the rhythm of language. In coding, an AI-generated script might run flawlessly, but the programmer hasn’t practiced debugging or structuring logic. In art or design, AI can create images instantly, but the artist might skip the exploration, the iteration, the mistakes that lead to unique insight.

The psychological effects go beyond skill loss. Immediate results from AI can reinforce a preference for speed over struggle. Thinking through a problem, experimenting, or revising ideas takes patience—qualities that are quietly practiced less often when a machine steps in. Over time, people can begin to rely on external solutions, trusting the output more than the process of figuring it out themselves. Confidence in independent thinking can waver, even subtly.

Deskilling is not evenly distributed. Early learners, students, or those practicing new skills may notice it sooner, but even experienced professionals can experience its slow creep. The temptation to outsource thinking is strong when the results seem better, faster, or easier. And each time we let the machine handle something, we practice the habit of reliance rather than the act of skillful effort.

Yet, there is another side to consider. Tools, including AI, can also expand what is possible. They can spark ideas, open new creative paths, and allow people to explore beyond the limits of manual effort. The question isn’t about whether AI is good or bad, but about the subtle ways it changes the balance between doing and watching, thinking and delegating.

Observing deskilling is like watching a shadow stretch across a familiar landscape. It doesn’t strike dramatically—it just shifts the shape of how we work. Certain processes, once practiced daily, may quietly fade into the background. Awareness, reflection, and deliberate effort are what help keep those processes alive. Writing by hand, solving problems independently, exploring ideas before suggestions arrive—these moments reinforce the skills that machines cannot replace.

In the end, the psychology of deskilling is a subtle reminder:

SKILLS ARE BUILT THROUGH PRACTICE, STRUGGLE, AND ENGAGEMENT, NOT JUST RESULTS.

Tools can amplify human potential, but they also shape the way we think, often subtly. Paying attention to what we do ourselves, and noticing what we delegate, is the only way to see the balance between human effort and machine assistance.

Appreciation of Human Art

BATHERS

Paul Cezanne painted upward of twohundred paintings of female and male bathers. This painting is from a series of three works, all depicting female bathers, that Paul Cezanne worked on in his later years. This series was hugely influential on early twentieth-century art.

PAUL CEZANNE

Instead of using models, Paul Cezanne used his memory and sketchbooks as references for the women, possibly leading to his abstract style in the painting. He draws upon already existing artwork, the woman in the center of the picture who is laying on her stomach and reaching forward may have been inspired by a statue of Venus, among other pieces.

You should never operate under the assumption that your brain is inferior to AI.

THIEVERY: AI art is ICKY AI generated content being passed off as human is rampant in the new age of technology. Not in just the most obvious areas like writing assignments, generating code or summarizing articles, but AI is even being used to help write scientific papers, spread misinformation through deepfakes, promote biases in the court of law, etc. However the most concerning usage of generative AI continues to be its use in creating art and the harm it brings to artists. Art is a bit of an ambiguous term, but the Oxford English Dictionary defines it as “the use of the imagination to express ideas or feelings, particularly in painting, drawing, or sculpture”. Art is inherently human, which is why AI “art” is so concerning, is that it is the very opposite of art.

Besides the philosophical quarrels, in a more direct way, AI harms artists by devaluing their art and stealing their work to do so. Before AI can make art, it needs to be fed a paramount amount of data. To do so AI models scrape the internet for anything and everything they can get.

Books articles Pictures Original illustrations.

Videos Literally anything put on the internet.

You won’t be notified if your art is taken to train AI models.

So, what rights do you have and how can you protect your work from being taken?

Legality: 1.You automatically hold copyright over all original works, but registering original works with the copyright office certainly helps.

2. AI works can’t be copyrighted

+ GRAY AREAS Fair Use Doctrine a.Permits the use of copyrighted works for specific use like education, commentary, research, etc. b.The Copyright office has not made a statement whether AI taking data from the internet counts as fair use or not, leaving a legal grey area. c.Derivative works that are created Derivative works a.Derivative works are works that are created based on previous works b.Some derivative works include, translations, adaptations, and revisions, of previous works. c.The copyright of a derivative work only protects the changes that were made to the original work. d.There is debate over whether or not all AI work is derivative work.

Milena Silk

Stella Liao

PROTECT YOURSELF When posting works on a platform, make sure that you read their privacy policy because many platforms will have a clause that allows them to share your data and use it to train AI models. After this, look for the option to opt- out of sharing data—-these options will likely be hidden so you might have to do some digging. Another way of protecting access to your content is making more things private. Making your works private is also a good idea, even if it doesn’t protect it from the platform itself, this will make it harder for external AI’s to take your content.

“Poisoning” your art is also a viable solution for protecting visual art. It involves altering pixels in your image so that to the human eye there is no difference, but an AI will read it completely differently. Projects like Nightshade and Glaze are good examples of resources that you can use to poison your art.

Jalen Meeker

AI & The C lassroom Earlier this month, my friend told me that she had been accused by her teacher of using AI, and that since then she had stopped trying to produce “good” writing. Later that day, another one of my friends expressed a lot of stress and concern about false AI accusations. They are not anomalies, and I realized the very existence of false accusations was creating a lot of fear in the academic environment. As a result of these conversations, in this essay I will be breaking down the accuracy of AI checkers, the biases they have, and finally, their effect on students…

The first piece to this story is the commonality of AI usage in schools. A survey collected by Science Direct found that 19.68% of public high school students self-reported using AI to “write all of a paper, project or assignment,” while only 1.45% of private school students reported the same. AI usage overall is at least twice as common in public school students than private. Private school teachers generally don’t have to be as concerned with AI generated work, which is why private school students, such as myself, can afford to be a lot less concerned with being accused of using AI. My friend goes to a public school, and told me she was really concerned with AI accusations due to their prevalence, and often adjusted her writing to sound less formal—or less “Chat GPT.” Being accused of AI is demoralizing, she told me that since she was accused she tries less on assignments out of fear her time and hard work will be discounted by an AI checker.

The accuracy of AI checkers is much more convoluted than it may appear at first glance. “Evaluating the accuracy and reliability of AI content detectors in academic contexts” by Hadra et al.

(2026) in the International Journal for Educational Integrity, collected data on the following characteristics:

“Sensitivity (Sen) /RecallAI: This measure describes out of all actual AI-authored texts, how many were correctly identified by the detector. Specificity AI (Spec): Specificity indicates out of all non-AI texts; how many were correctly identified as not AI-authored. PrecisionAI: Precision indicates out of all texts predicted as AI-authored, how many were actually AIauthored. F1-ScoreAI: F1-score is the harmonic mean of Precision and Recall. Accuracy AI (Acc): The accuracy indicates the overall rate at which the detector correctly classifies both AI and non-AI texts.”

The table reveals that bothTurnitin and Originality are susceptible to misclassifying AI work as human, however, both checkers showed a strong ability to identify human work correctly. Neither checkers were adept at detecting hybrid work as partly AI written. The low error rate in false positives does not represent a complete go-ahead to rely solely on these checkers.

If, at most, one out of every hundred students gets falsely flagged for AI usage, 150,000 American public high school students would be falsely accused of AI. I have personally written around 12 essays this year for my history and english classes (this number is on the higher side for most high school classes), and if that trend is consistent throughout my high school career, I will have written 48 essays upon my graduation. That is 48 separate opportunities to be falsely accused of AI. At a 1% error rate I would have a 50% chance of being accused of AI throughout my high school career, assuming I graduate in 4 years and I take English and History classes throughout those four years.

That is 1,800,000 high school students every year (this does not account for repeated accusations). A one in four chance. Most estimates of false positives range from 1% to 15%. There are no reliable estimates under 1%, to my knowledge. A 15% false positive rate on one essay would affect 2,250,000 students. False positives could then potentially affect up to 27,000,000 essays annually. There were 15,000,000 public high school students last year. At the highest estimate, that is over a 100% chance of your work being accused of AI falsely. Is preventing cheating really worth it?

My friend generously gave me a copy of her essay titled “Champion Speech” that her teacher flagged as AI. The essay is a proposal for National Snoopy day. The essay goes over Snoopy's history, prominence, and cultural impact. I am going to pull a few sentences from that essay that probably contributed to the accusation. She wrote, “It’s easy to wonder if Snoopy really deserves all the honors he already has, much less a national holiday, considering that he’s a bit of a menace. But honestly, he was never meant to be a role model.”

The blacked out portions are not relevant to the conversation. She is following a useful and valid persuasive writing principle: A common belief, hypothetical, or doubt followed by contrasting fact or limitation to the previous thought. The purpose of this structure is to assume a persuasive but truthful narrative, as the author gets to present the opposing thought and then immediately refute it. Unfortunately, AI also commonly uses this structure for the same purposes. AI wants to appear truthful and conscious of opposing narratives, which often results in the structure above. Another example of a similar structure is, “These perceived imperfections haven’t only made him so adored by the public, but also incredibly influential to other cartoonists.”

This follows the same structure: A general belief followed by an expansion of that belief. The easiest way to avoid being accused of AI because of this type of sentence structure is to use it sparingly. Most writers use some version of this sentence in a persuasive essay or speech; AI uses it in every sentence. It’s easy to wonder if AI has a monopoly on structural contradictions, considering its reliance on them. But honestly, as long you do not over use this struture— your writing will sound perfectly human. If you find yourself unable to detach from said structure, try: The easiest way to skirt AI’s perceived monopoly on sentence contradictions, considering its reliance on them, is simply not to mimic AI’s over reliance on them. I understand that adapting your writing to avoid AI accusations is tiring and demoralizing, and you may think that this structure is the best way to establish a persuasive point, but consider that repeating the same structure sounds bland anyway. Honestly, diversity in prose is always best practice.

AI checkers should never be the end all be all for students' work.

It is awful for students to be constantly cornered with false positives, not to mention the clear bias in AI checkers that should immediately prove its damage. Both the mental consequences of AI checkers and the physical consequences of cheating allegations—like permanent zeros, failing classes, academic suspension, and expulsion—affect public school students at a much higher rate than private school students. There is a serious issue of higher consequences for neurodivergent students, ELs, and poorer students. The result of AI paranoia is not less AI usage but decrease of morale amongst student populations.

My recommendation for teachers grappling with rampant AI usage is to create assignments that do not perform well with AI, like class discussion or physical work. My second suggestion is to believe students are acting in good faith, AI is not known to produce high quality work, the natural consequence of poor grades is enough of a punishment. Also consider that if AI can complete the work you assign better than your students can (provided your students are not eight years old), your assignments are not actually assessing the right things. You may notice I haven’t discussed the benefits of AI in the classroom, I will not. Not because there are none, but because I do not want to encourage AI usage. The negative economical and environmental effects of AI, to name a few, are beyond the scope of this essay, but are not beyond the scope of my consciousness.

CONTRIBUTORS Articles Your Brain and AI - Michael Rosales, 2026 Psychology of Deskilling - Oliver Mosher, 2029 Appreciation of Human Art - Emrie Benn, 2029 Thievery - Stella Liao, 2029 AI & The Classroom - Lillian Kline, 2027

Art Cover - Sam Custodio, Hanford HS, 2029 Chess - Jalen Meeker, 2029 18:36 - Milena Silk, 2029 Jerboa - Stella Liao, 2029 Bathers - Paul Cezanne