By Alejandro Rodríguez Hernández

Circolo Social Circle

Smart teaching:

And after so much libertarianism, what will work for us teachers in the new Mexican high school?

Artificial intelligence offers Mexican high school students a unique opportunity to personalize learning—the same public education, but organized, regulated, and empowered—and to free teachers from the administrative burden and rescue local languages and knowledge. However, it requires ethical regulations that prevent plagiarism, cognitive dependence, and the reproduction of colonial biases. Under the principle of possible pragmatism—measuring the value of an idea by its collective impact without sacrificing cultural dignity—the guide proposes the DIAEVAR method for students and teachers to define local problems, critically interrogate AI, verify data, and reflect on the written results. The strategy is complemented by the creation of phases for awareness-raising, literacy, co-design, implementation, and continuous evaluation. Thus, AI becomes a "cognitive prosthesis" that enhances pedagogical work instead of replacing it, reaffirms human accompaniment, and projects the school as a center of social well-being and sustainable innovation.

What are the challenges of artificial intelligence that teachers face in the classroom?

Today's Mexican classroom is a cultural palimpsest: its walls house the Mesoamerican calpulli, the Greek paideia, the Hebrew Torah, and the digital rubrics of the New Mexican School. However, beneath this richness lies a fissure: the ongoing struggle between the public interest and the privatization of education over the past two decades. The arrival of artificial intelligence (AI) amplifies this tension. While large cities are narrowing the digital divide, up to 50% of the Mexican population still lacks stable internet access. This technological deficit is compounded by the "invisible crisis" of educational guidance: what kind of citizens do we want to educate, and with what tools? The general baccalaureate, with its dual gateway to work or university, thus becomes a decisive space for reimagining school as a center of intellectual emancipation and collective well-being. Therefore, I assert that "without sacrificing cultural dignity, an idea is worth only what it improves collective life."

AI shines in the public imagination as the promise of "going beyond the stars." This is no coincidence: the simulation of protein folds that validated the structure of DNA or the early diagnosis of diabetic retina are already milestones in the human record; even the world's economic powers call it an advanced critical technology.

But that same brilliance is dazzling: at university, the debate revolves around intellectual property; at elementary and secondary levels, concerns arise about plagiarism, superficial reading, and the loss of study habits. For adolescents in the television and digital age, who already struggle with anxiety, attention deficit disorder, and precarious socioeconomic realities, AI can be either a springboard or an abyss: a personalized tutor or a shortcut that erodes agency.

In everyday practice, few teachers explicitly indicate how to use AI in assignments. The result is a "minimalist intuition of the prompt"2: students copy

1 According to the RAE, a palimpsest is an ancient manuscript that preserves traces of a previous writing that was artificially erased.

2 A “prompt” in the context of artificial intelligence (AI) is an instruction or text provided to an AI tool to generate a specific response or result.

In essence, it is the way we interact with the AI and tell it what we want it to do4 literally the statement of the command in the chat and it pastes the answer, without contrast or intellectual digestion.

That is, it copies the material exactly as it was written in the student's notebook, without any semantic or pragmatic richness. To contain this drift, we propose the DIAEVAR method (Define, Interrogate, Analyze, Speculate, Verify, Apply, and Reflect with the teacher).

DIAEVAR requires explicit sources, uncovering biases, and comparing empirical data before translating the response into a handwritten product. This sequence keeps the heuristic cycle of academic research alive and shifts AI from the center to the critical perimeter of the learning experience.

AI Problem Solving Flow (DIAEVAR Method)

1. Define the problem in your own and local terms.

2. Interrogate the AI with clear prompts + required sources.

3. Analyze the response: reasoning? quotations? biases?

4. Speculate with related data or mental experiments.

5. Verify with external data, experiments or human sources.

6. Apply the solution in a prototype or handwritten argument.

7. Reflect: What did I learn? What would I improve next time?

Generative AI has democratized audiovisual creation: solarpunk posters, polyphonic podcasts, and 3D animations emerge in minutes. Far from reducing artistic sensibility, this proliferation can expand it if teachers cultivate aesthetic curation. The challenge is to avoid the hegemony of a "synthetic taste" preconfigured from Silicon Valley and make room for Zapotec iconography, Mazahua textiles, or regional Mexican sounds like son jarocho. Integrating AI into aesthetic education involves two steps: on the one hand, teaching how to deconstruct how machines learn styles, and on the other, transforming the classroom into a laboratory where tradition and avant-garde dialogue without hierarchies, collaboration, and non-subordination.

Regulating the use of AI in schools isn't censorship; it's designing the margins of freedom.

There is a feedback loop between code and policy. Adjusting the algorithm—for example, by requiring answers with mandatory bibliographic references—automatically raises the user's cognitive threshold. A school regulatory framework can establish "minimum quality prompts," disconnection times, and the obligation to label hybrid (human/AI) authorship. Thus, programming becomes an ally of pedagogy: if the AI suggests answers with an appropriate reading level, the teacher gains time for personal tutoring, and the AI gains cultural relevance.

Far from becoming obsolete, teachers are emerging as a north star in the firmament of the future and of data. Our presence provides what no algorithm possesses: a gaze, gestures, and ethical authority, connection and reference.

Three functions support it:

As a critical curator, he selects content, comparing and exploring it with young people, and verifies the traceability of sources, maintaining numerous reference tables on the techniques used and their methodologies.

As a digital literacy mentor, it teaches how to formulate prompts, that is, how to program, generate a question, and request an instruction. This is important because it acts as a guide that allows the AI to understand what is expected of it and produce relevant and accurate results. It also allows for detecting hallucinations and comparing translations and vocabulary.

And above all, as a co-designer of experiences, as he articulates projects where handwritten text, oral presentation, and digital creation complement each other. These tasks are not automated because they require affective interpretation and situated understanding; they are precisely what give meaning to knowledge.

For many teachers, AI raises fears of replacement. However, when properly regulated, it becomes a time-saver: it corrects drafts, suggests contextualized problems, and generates tracking tables, allowing teachers to return to in-depth conversation and observation of the learning process, and even implement reinforcement and reward systems.6

This refocusing coincides with the goals of the New Mexican School: expanding community participation and nurturing school democracy. By reducing bureaucratic burdens, AI reinforces the fundamental function of teaching: forming criteria, habits, and a sense of belonging. I even imagine AI giving teachers advice and techniques for managing anxiety and crises, reducing the impact of teaching on teachers' emotional processes. What if students used it for personalized follow-up on a pre-emotional approach? Just like with references to the school of parents that never existed, the school of how to be different, and even, just like the school that compiles all the moral information of the known historical universe and gives the best advice, like Methuselah, who is said to have lived more than 1,000 years.

Now the question is how to achieve this?

Criterion is the compass that guides ethical and logical decision-making. It is cultivated through open questions and the comparison of perspectives to achieve discernment, a well-studied philosophical question. AI can stimulate it if used as a "devil's advocate," offering counterarguments, alternative paradigms, or historical analogies.

But such a benefit depends on two conditions: the requirement to reveal the chain of reasoning and verification with human or empirical sources. In this way, AI ceases to be a totem of truth and becomes a fallible interlocutor, a catalyst for critical judgment and creativity.

One of the ways we can develop study habits is through meaningful repetition, as it strengthens memory and character. Traditional teaching habits—underlining texts, reciting tables, summarizing—don't disappear; they are reconfigured. The planned use of AI can integrate metacognitive routines: each time the class uses a text generator, spend five minutes manually explaining what will be written as a reflection to reinforce learning. Thus, the digital habit is anchored in an ethic of deep learning.

Not even the best neural network can replace the transfer of humanity that occurs when a teacher encourages a fearful student or mediates a conflict in the playground and provides guidance. 7 Education demands bodily presence, shared mistakes, and shared celebration. AI lacks vulnerability and, therefore, cannot teach the virtue of getting up after a fall, day after day. Accompaniment—that willingness to listen, question, and wait—is transmitted exclusively between people. Understood as the process of being present and providing support to another person, it can be considered a manifestation of humanism. Accompaniment is a humanism because it seeks precisely that: to recognize and support the person in their experience, promoting their well-being and personal growth. AI, at the service of this relationship, enhances, but does not replace, the pedagogy of encounter.

The golden rule of legitimacy is: If a use conceals its origin, steals another's voice, or reduces another person's autonomy, it is illegitimate. Some legitimate vs. illegitimate uses could be, in the field of learning, step-by-step tutoring, local example generator, and code checker vs. taking exams, submitting texts without attribution, and literal plagiarism.

Mexican education is at a crossroads: either it simply reacts to the technological wave or it creates a paradigm that makes AI a tool for inclusion and cognitive justice. Regulating its responsible use is not intended to stifle creativity, but rather to give it an ethical channel. Properly guided AI fosters curiosity and liberates

teaching time and increases opportunities for contextualized learning. But this promise is fulfilled only if the school maintains its founding mission: to form criteria and habits, sustain intergenerational dialogue, and cultivate cultural dignity.

On the horizon of 2050—when every student can carry their "pocket AI"—we will remember that the real leap forward wasn't in silicon, but in having defended the centrality of human presence. Because, in the end, an idea is worth only what it improves collective life without sacrificing cultural dignity; and no machine can calculate that without the beat of a heart to teach it what it means to thrive together.

How can we prosper together? That would be the big question with which we will conclude: How far will we take the idea of the baccalaureate in the next 20 or 30 years in the face of the changing labor market? How much will it be enough to materially sustain our future? At least that of Mexicans, I mean. And what about automation and unemployment, or the new unlimited sources of thorium energy from the great powers, or something even closer, like telemedicine and targeted diagnosis with gene therapy, or the use of artificial intelligence for the design and implementation of technologies, teletechnologies, and biotechnologies? All of this demands the right to also orient ourselves toward other ways of organizing and managing the baccalaureate, including the general baccalaureate, updating it to the demands not only of the private and technological sectors, but also in the service of life, health, and the community.

Above all, for itself, in the pursuit of learning and doing so on its own, school by school, recycling, supporting, generating ideas and materializing them with what is available, proposing possible, plausible, probable, and even current futures. At the beginning and at the end, in this brief journey, building the common good could mean prospering together.

Literature.

1. Dussel, E. (2021). Philosophy of Liberation (5th ed.). Siglo XXI Editores.

2. National Institute of Statistics and Geography [INEGI]. (2025). National Survey on the Availability and Use of Information Technologies in Households (ENDUTIH) 2024-2025. INEGI.

3. United Nations Educational, Scientific and Cultural Organization [UNESCO]. (2023). Guidance for generative AI in education and research. UNESCO Publishing.9

4. Organization for Economic Cooperation and Development [OECD]. (2024). Education policy outlook 2024: AI & skills. OECD Publishing. https://doi.org/10.1787/ai‑skills‑2024

5. Ministry of Public Education [SEP]. (2023). Curriculum for the New Mexican School. General Directorate of Educational Materials.

6. World Health Organization [WHO]. (2024). Adolescent mental health: Key facts (Fact sheet No. 945). WHO. https://www.who.int/news-room/fact-sheets/adolescent-mental-health

7. McCarthy,John. «The Philosophy of AI and the AI of Philosophy». Jmc.stanford.edu. 10/23/2018.