My goal is to encourage teachers to mobilize collective intelligence (CI) in the service of learning and to take advantage of the new pedagogical possibilities opened by Artificial Intelligence (AI)—a tool our students are already using, albeit not always appropriately. I will begin by explaining why collective intelligence should be an integral part of our teaching strategies, and then outline several ways to use AI to support CI-centered pedagogy.
The « we » in this text refers to teachers in general, specifically secondary school teachers. I include myself in this collective, having taught for forty years at the secondary, higher education, and vocational levels. I have practiced what I preach: using digital technologies to facilitate learning through collective intelligence. This text is an expanded version of a previous post, prepared for a presentation at the 6th Interdisciplinary and Intersectoral Symposium on Secondary Education in Quebec on March 20, 2026.
Collective Intelligence: Preceding, Exceeding, and Succeeding Us
For over thirty years, I have explored collective intelligence from every possible angle. Here, I approach it through a temporal lens and an educational perspective. The CI that precedes us comes from the past: we are in a position to receive. The CI that exceeds us opens us to collaboration in the present. The CI that succeeds us looks toward the future: we bear the responsibility of transmission.
Collective Intelligence Precedes Us
CI precedes us: we have inherited our languages and our knowledge. Our skills and tools have been passed down to us. The ideals that drive us were already mobilizing previous generations. The landscapes and cities in which we move were built by others. The libraries (physical or virtual) where we learn were written by countless authors who read one another. The essence of learning is to drink from the collective memory; in an age of abundant digital sources, the teacher’s role is, more than ever, to create a thirst for knowledge.
What does this mean for education? It means we must utilize available memory as much as possible to support student learning. But it also means we must train students to take advantage of this memory, as there are no longer any physical obstacles between them and accumulated human intelligence. We must develop the skills that allow them to search for, find, and usefully consult books in libraries and audiovisual media in resource centers. We must provide the intellectual tools and reflexes necessary to navigate the Web and databases. Finally, we must teach them the proper way to use contemporary AI, which mobilizes the knowledge stored in libraries and digital data—an AI that is also capable of personalizing this knowledge according to the students’ abilities and needs.
Collective Intelligence Exceeds Us
Collective intelligence exceeds us because no individual possesses more than a tiny fraction of the knowledge, skills, and soft skills that sustain the modern world. Hence the necessity for collaboration and openness to others, which must be practiced and valued from the earliest stages of schooling. Furthermore, learning is an essentially social enterprise—not only because the camaraderie of a shared effort fosters mutual aid and enthusiasm, but because everyone possesses a unique experience and viewpoint that can illuminate others and reveal their blind spots.
Pedagogical dialogue must be not only vertical (teacher/student) but also horizontal (student/student… and teacher/teacher!). We can view the teacher’s role as a facilitator of their students’ collective intelligence. I have personally used social media in class to stimulate CI-based learning; it was an enriching experience for everyone.
Mobilizing student CI requires an adequate pedagogical strategy. The teacher must act as an effective « conductor. » The goals of exercises must be clearly stated, and comprehension verified before students begin collaborating. The teacher must accompany and motivate students throughout the activity. Crucially, assessment must be designed for collective functioning. Approaches that « gamify » the distribution of points according to clear, universal rules are preferred. It is even possible to use peer-to-peer collective assessments where students participate in their own grading. After all, what is critical thinking if not the ability to exercise responsible judgment, including on one’s own work and that of one’s peers?
I used to tell my students that our exercises were training for future « knowledge ninjas. » We aimed for excellence in objective knowledge and practical skills, but also in interpersonal and collaborative abilities. Understanding common goals, respecting the rules of the game, and mutual aid (never leave a comrade behind!) are just as important as learning the content.
Teachers must also engage in collaborative intelligence. This means that instead of waiting for institutional training, they should adopt a mindset of permanent learning and research. The best method remains building a Personal Learning Network (PLN). This involves finding experts on relevant channels (LinkedIn, Facebook groups, discussion forums) and exchanging experiences with them. Strengthened by our own trials and errors, we can eventually become experts ourselves and help our colleagues.
Collective Intelligence Succeeds Us
Collective intelligence succeeds us: having received (almost) everything, it is our turn to transmit what our academic, professional, and existential journeys have taught us. We must adapt our knowledge to the varied needs and new circumstances of our peers and collaborators. In fact, one never learns a subject as well as when one has to teach it. Addressing others or contributing expertise to a collective memory forces us to clarify implicit concepts, systematize empirical knowledge, and decontextualize experiences. In doing so, we allow knowledge to circulate and be more easily adopted by others.
What does the idea that CI « succeeds us » mean in education? Success in education is what remains once the course is over and the class disperses. Was the knowledge acquired? Were the skills integrated? Did our students become aware of their personal responsibility in building and transmitting collective memory? Every text or image published on the Web, every data deposit, every interaction with Perplexity, Claude, or ChatGPT contributes to the construction of collective memory and the training of AI. We are not just downstream of collective intelligence; we are also upstream.
Artificial Intelligence in Education
General Philosophy
Once the foundation of collective intelligence is laid, let us turn to AI for learning. We must first correctly characterize contemporary Generative AI. Rather than an « autonomous » mechanical intelligence, it is actually a statistical compression of the immense digital memory used for its training. AI should be considered a mobilization of collective memory for the benefit of its users. It is a manifestation of past and present CI. In other words, AI is a digital interface between accumulated collective intelligence and the living intelligence of students and professors.
Pedagogically, I believe we must now include AI in our teaching scenarios and evaluate its proper use by students. It has a role to play in the class group’s CI, in open dialogue with the professor. AI can serve as an interlocutor in debates where students work in collaborative learning. For example, it can help compile and structure ideas generated collectively, organizing individual contributions into a coherent document that the group then critiques and improves together. AI must not replace human interaction; it should be used as a catalyst to enrich collective reflection.
Essential AI Skills for Students
- Linguistic Relevance: The primary skill is conceptual and linguistic. The more coherent, elaborate, and precise the « prompt, » the better the result. AI mirrors the intelligence of the student; it mobilizes high-quality data when met with high-quality input. It is useful to show students how responses change based on a single word or turn of phrase.
- Critical Thinking: AIs are probabilistic machines; they inevitably make mistakes. Students must remain alert and verify citations, facts, and peremptory claims. Critical thinking must be mobilized not only against « hallucinations » but also against the biases of training data. AI does not tell « the truth »; it reproduces what it has learned.
- Perseverance: The first answers are not necessarily the best. Students must learn to cross-examine the machine, compare different AIs, and take the time to follow reference links.
Pedagogical Strategies for AI in Collective Intelligence
- The Dialectic of Learning: Learning occurs through a four-pole dialectic: teacher guidance, the student’s personal memory, dialogue with peers, and AI mobilizing accumulated collective memory.
- Interaction with a Shared Memory: AI can act as an interface for a class-specific knowledge base (historical texts, scientific articles, etc.). This allows students to query content without the risk of hallucinations and generate summaries on demand.
- Facilitating Conversations: The teacher becomes the conductor of AI-assisted CI. During brainstorming, AI can rephrase contributions for clarity or propose intermediate syntheses. In debates, it can play « devil’s advocate, » forcing students to refine their arguments.
- Collaborative Writing: Students can write a collective short story where AI proposes stylistic variations or helps maintain narrative consistency. Alternatively, AI can generate a first draft that the group collectively evaluates and corrects.
- The Critical Thinking Exercise: Divide the class into teams whose goal is to find the maximum number of factual errors in an AI-generated essay.
- Assessment: Since AI can generate finished products, assessment must focus on the process rather than the product. We should evaluate the student’s ability to interrogate the AI, detect hallucinations, and improve the machine’s suggestions through their own culture.
The Tools
The choice of tools should only come after determining the desired knowledge and pedagogical strategies.
- General AIs: ChatGPT for group conversations and simulated debates; Perplexity AI for sourced research and fact-checking; Claude for synthesizing long documents; Gemini (Google’s AI); and Grok for real-time news.
- Specialized Tools:
- NotebookLM (Google): Limits the AI to user-provided documents; ideal for « drinking » from a specific collective memory without hallucinations.
- Mizou: Allows teachers to create specialized chatbots with strict instructions (e.g., « Never give the answer, only ask questions »). Ideal for Socratic dialogue.
- Khanmigo: An AI tutor designed to guide students without doing the work for them.
- Padlet: Transforms a wall of student ideas into an AI-structured mind map.
- Canva Magic Studio: Used by groups to turn collective text concepts into visual presentations.
Conclusion: A Resolutely Humanistic Approach
From a philosophical standpoint, we must never neglect to enrich the personal memories of our students. Just because « everything » is on the Internet does not mean we should stop cultivating individual memory, which is the foundation of living thought. Critical thinking is woven in the dialectic between collective memory (mobilized today by AI), personal memory, and open dialogue with our peers.
The richer our personal memory, the better we can exploit AI resources, ask the right questions, and spot hallucinations. By no means can AI substitute for reading « real » texts by human authors, and even less can it substitute for knowledge. It can, however, serve as an untiring coach. If we are ignorant, we will be manipulated by language models. Conversely, the more knowledgeable we are, the better we can master an AI that is fast becoming the technical environment of thought—a new sensorium.
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