by Guy Levi.
Originally published in Medium,
June 21, 2025

Collaborators: Guy Levi (HI and CI), Raanan Azoulai (HI and CI), ChatGPT 4.5 (AI), Gemini, and Notebook LM (AI and CI)

This piece began as an unusual kind of conversation - a hybrid dialogue between humans and machines. Guy Levi and Raanan Azoulai found themselves exchanging ideas with ChatGPT, Gemini, and Notebook LM (AI), in a reflective, cross-intelligence exploration. What emerged was a striking realization: in most models of AI Literacy, one essential dimension remains undervalued, the Human Factor. That insight became the catalyst for this work.

TLDR 

Introducing HI-AI-CI Literacy (Human, Artificial, Collective Intelligence) as a strategic learning framework for hybrid cognition. Grounded in Amy Zalman's maxim, this framework argues that traditional, technical AI Literacy is inadequate. As AI integration deepens, the focus must shift from machines to the Human Factor. HI-AI-CI Literacy moves beyond technical skill, emphasizing the critical, ethical, and creative orchestration of HI, AI, and CI. It is defined by three foundational components:

1. Critical Hybrid Thinking (short):

Guiding and refining collaborative processes with AI using human judgment.

2. Collective Epistemic Agility (short): 

Engaging with and enhancing Collective Intelligence within dynamic knowledge networks.

3. Ethical Cognitive Agency (short):

Continuously reflecting on the ethical implications of human-AI collaboration and ensuring responsible decision-making.

The framework asserts that neglecting the Human Factor (judgment, creativity, empathy, ethical reasoning) leads to predictable failures. Therefore, the practical application involves re-architecting learning around human capabilities. 

This is achieved through structured learning methods, or "symbolic frameworks" - such as:

• Cognitive Architecture “Studios” (short): 

Training learners to be cognitive designers, deciding when to trust, question, or override AI.

• Ethical Provocation “Labs” (short): 

Immersive simulations for navigating morally complex AI scenarios.

• Critical Intelligence Frameworks (short): 

Training in critical hybrid thinking and collective reasoning.

• Reflexive “Arenas” (short): 

Structured reflection follows real-time, AI-involved decision-making.

Organizations must "change the story," shifting from static training to ongoing cognitive dialogue, from content delivery to cognitive partnership, from hierarchical expertise to networked authority, and from efficiency to reflective outcomes.

0. Introduction

What does it truly mean to be literate in a world of accelerating intelligence?

For years, the focus of AI Literacy has been on understanding how artificial intelligence works and how to use it responsibly. However, as AI becomes increasingly embedded in our thinking, working, and decision-making processes, this technical framing no longer suffices. We need a new kind of literacy, one that recognizes the evolving interplay between Human Intelligence (HI), Artificial Intelligence (AI), and Collective Intelligence (CI). This piece presents a new strategic framework: HI-AI-CI Literacy. It redefines the goals of learning and development (L&D) in the age of hybrid cognition, positioning the Human Factor - not machines - at the center of that transformation.

Grounded in Amy Zalman’s theory of Strategic Narrative and her claim that “change the story, change the outcome”, this work begins by arguing that how we speak about intelligence shapes how we organize it. If we want better futures, we must first tell better stories.

From there, the piece traces the evolution from conventional AI Literacy to HI-AI-CI Literacy, articulating three core components: hybrid cognitive fluency, epistemic humility, and collective epistemic agility. These pillars underpin a broader rethinking of the Human Factor - not as a side effect of AI integration, but as the anchor of any ethical, adaptable, and resilient intelligence system.

The practical implications are explored through a set of structured learning methods and design principles that reimagine how individuals and organizations learn and grow. These include the concepts of reflective studios, ethical labs, and intentional frameworks designed to embed human judgment, emotional intelligence, and critical collaboration at their core.

Ultimately, the piece illustrates how these concepts are applied in real-world organizational practices - not as abstract ideals, but as tangible narratives that inform how teams learn, make decisions, and evolve in collaboration with machines.

HI-AI-CI Literacy is not an upgrade. It is a transformation of how we think about thinking - and how we shape the future through the stories we choose to live by.

1. The Strategic Narrative Perspective

Amy Zalman’s theory of Strategic Narrative posits that narratives are powerful frameworks that shape how we perceive reality, influencing our attitudes, decisions, behaviors, and ultimately, our outcomes. According to Zalman, by intentionally crafting or changing narratives, we have the power to redefine both individual and collective futures, hence her influential maxim: “Change the story, change the outcome”.

In the context of Learning and Development (L&D), strategic narratives have a profound impact on how organizations, employees, and learners interact with technology, particularly artificial intelligence. Traditionally, AI narratives have positioned these technologies as mere productivity tools or automations, designed primarily for efficiency and cost reduction. However, redefining the Generative AI narrative as one of partnership, cognitive collaboration, and ethical co-creation shifts perceptions, expectations, and behaviors within organizational and learning contexts.

By adopting Zalman’s strategic narrative framework, organizations can transition from viewing AI simply as external assistance to embracing AI as integral cognitive collaborators. This narrative shift redefines organizational outcomes, promoting deeper human engagement, greater cognitive agility, and more responsible use of AI, resulting in enhanced creativity, ethical decision-making, and collective problem-solving skills.

Thus, reframing AI narratives in L&D contexts from “tools we use” to “partners we think with”- is fundamental to achieving transformative learning outcomes and harnessing the full potential of human, artificial, and collective intelligence.

2. The Journey from AI Literacy to HI-AI-CI Literacy

The journey from AI Literacy to HI-AI-CI Literacy begins with the fundamental cognitive shifts outlined in “The Big Cognitive Bang”, and the “HI-AI-CI Paradigm (2025 Edition)”. 

Initially, AI Literacy focused on understanding and operating artificial intelligence tools. It emphasized technical proficiency, algorithmic awareness, and the practical application of AI solutions in specific tasks or roles.

However, as GenAI technologies evolved, they introduced broader cognitive transformations, including cognitive expansion - where human cognitive boundaries extend into digital realms; Hybrid Thinking - where humans and AI collaboratively produce insights; democratization of knowledge - where AI facilitates personalized, global access to information; and blurred boundaries between learning and application - where real-time AI interactions create dynamic learning environments.

These transformations demand a more expansive literacy framework: HI-AI-CI Literacy. This literacy moves beyond basic technical competencies to cultivate skills essential for navigating hybrid and collective cognitive landscapes. It integrates critical thinking and ethical responsibility with creative intentionality, promoting a nuanced understanding of AI as a cognitive partner rather than a mere tool.

HI-AI-CI Literacy prepares individuals and organizations to effectively leverage collective intelligence networks, actively engage in hybrid cognition, and thoughtfully manage the ethical complexities emerging from extensive human-AI interactions. Thus, the progression from AI Literacy to HI-AI-CI Literacy represents not merely a technological evolution but a profound cognitive and cultural shift, emphasizing comprehensive cognitive agility, ethical clarity, and adaptive creativity in all organizational and lifelong learning contexts.

3. Defining HI-AI-CI Literacy

HI-AI-CI Literacy is defined as the ability to effectively orchestrate Human Intelligence (HI), Artificial Intelligence (AI), and Collective Intelligence (CI) with critical awareness, ethical responsibility, and creative intentionality. 

This literacy framework emphasizes three foundational components:

Critical Hybrid Thinking

This involves actively questioning, refining, and contextualizing cognitive interactions with AI. Critical hybrid thinking demands that human judgment and critical reasoning consistently guide and refine the collaborative process with intelligent technologies. It emphasizes discernment in distinguishing valuable AI-generated insights from irrelevant or biased content, ensuring that human intuition and critical reflection shape the cognitive partnership effectively.

Collective Epistemic Agility

This skill set enables individuals to effectively engage with and enhance Collective Intelligence (CI) within dynamic knowledge networks. It involves recognizing credible information sources, facilitating meaningful dialogue among diverse groups, synthesizing collective insights, and collaboratively addressing complex problems. Collective epistemic agility fosters active participation in collective knowledge creation, enabling teams and communities to leverage shared intelligence to navigate rapidly changing environments and authority landscapes effectively.

Ethical Cognitive Agency

Central to HI-AI-CI Literacy, ethical cognitive agency entails continuous and profound reflection on the ethical implications of hybrid cognitive ecosystems. It requires individuals and organizations to critically evaluate the moral dimensions of human-AI collaboration, uphold principles of transparency and accountability, and commit to responsible decision-making. Ethical cognitive agency ensures that the deployment and integration of AI technologies within organizational and lifelong learning contexts remain aligned with broader societal values and ethical standards.

Together, these components equip learners and organizations to harness the strengths of human, artificial, and collective intelligences, ensuring adaptive resilience, ethical integrity, and innovative problem-solving capabilities in an increasingly complex cognitive landscape.

4. The Human Factor in HI-AI-CI Literacy

Among the most critical yet consistently undervalued elements in AI integration is what we call “The Human Factor”. Despite the increasing presence of AI systems in strategic decision-making, workflow automation, and knowledge production, organizational transformations often prioritize technology deployment over human development. As a result, essential human capabilities - such as judgment, creativity, empathy, and ethical reasoning - are frequently sidelined, treated as intangible or secondary concerns.

HI-AI-CI Literacy reframes this imbalance. It asserts that any meaningful and sustainable transformation with AI must begin by recognizing and strengthening the uniquely human dimensions of cognition. The Human Factor underscores our indispensable role as moral agents, imaginative thinkers, and collaborative sense-makers in hybrid ecosystems. It is not a counterweight to AI, but the very ground on which hybrid intelligence is built.

Neglecting the Human Factor leads to predictable failures: increased dependency on automated outputs, erosion of internal critical thinking skills, lack of engagement, and ethically questionable decisions made by default rather than design. These outcomes are not technological flaws - they are narrative failures, stemming from a story that centers AI capability and sidelines human potential.

To change the outcome, we must change the story. Organizations need to reorient their strategies around human agency, designing systems that support ethical reflection, encouraging environments where human creativity is amplified rather than automated, and embedding emotional intelligence, collaboration, and adaptability as core values in any AI-enhanced setting.

The Human Factor is not a nostalgic defense of pre-digital skills. It is a strategic imperative. It ensures that in the rush to augment intelligence, we do not outsource our humanity, but instead re-center it as the anchor of any collective cognitive future.

5. Re-architecting Learning Around the Human Factor

If the Human Factor is the anchor of hybrid intelligence, then learning environments must be redesigned to cultivate, protect, and elevate that humanity. Practical implementation of HI-AI-CI Literacy is not about deploying more AI tools - it is about crafting systems, spaces, and processes where human capabilities flourish because of the thoughtful integration of AI, not despite it.

In this spirit, organizational and lifelong learning ecosystems must be reimagined as incubators of reflective, relational, and resilient intelligence.

The following are not physical spaces but structured learning methods - symbolic frameworks and strategic tools designed to embed HI-AI-CI principles into practice. Whether implemented digitally, in workshops, or through curriculum redesign, each represents a mode of orchestrating hybrid cognition, ethical reflection, and human-centered skill development.

Cognitive Architecture “Studios” 

refer to structured exercises where individuals design their own thinking systems by intentionally orchestrating interactions between HI, AI, and CI. Learners are not passive users of AI but active cognitive designers, developing fluency in deciding when to trust, when to question, and when to override machine output. These studios model autonomy, critical reflection, and cognitive adaptability.

Ethical Provocation “Labs” 

are immersive simulations that expose learners to morally complex scenarios involving AI. They foster ethical discernment and emotional maturity by asking learners to navigate ambiguity, justify decisions, and reflect on the unseen implications of AI-enhanced actions. These are not add-ons - they are core to preserving the Human Factor.

Critical Intelligence Frameworks 

describe curated ecosystems of prompts, discourse formats, and challenge-based activities that train learners in critical hybrid thinking, collective reasoning, and epistemic agility. Their goal is not just to evaluate information, but to develop a robust culture of inquiry and mutual responsibility within networked knowledge systems.

Reflexive “Arenas” 

create the conditions for learners to develop resilience under pressure. These structured learning environments engage participants in reflection after real-time decision-making, especially when AI is involved. Learners strengthen their metacognitive and emotional responses through questions like “How did I arrive here?” or “What assumptions shaped this?”

Human-Centered Skill Integration

anchors all the above methods by deliberately embedding core human competencies. Complex problem-solving, ethical judgment, adaptability, collaboration, and emotional intelligence are treated not as soft skills but as strategic capacities for navigating and shaping the hybrid future. These skills are not AI-resistant - they are AI-enhancing when made intentional.

In summary, the practical application of HI-AI-CI Literacy involves designing learning not as content delivery, but as a cognitive architecture. It means elevating the Human Factor from a philosophical concern to a strategic design principle - one that turns every learner into an architect of hybrid cognition and every organization into a lab of ethical, shared intelligence.

6. Changing the Story in Practice

Strategic narratives come to life through action. If HI-AI-CI Literacy offers a new story about intelligence - one where human, artificial, and collective cognition are deeply entangled - then organizations must become storytellers through their practices, processes, and learning cultures.

Changing the story in practice means cultivating environments where human agency is not just preserved, but empowered; where AI is not just used, but co-thought with; and where learning is not just acquired, but continuously reshaped in the act of doing. 

The following examples illustrate how this narrative shift manifests in real settings:

From Static Training to Ongoing Cognitive Dialogue: 

Traditional upskilling is often linear and isolated. Organizations embracing HI-AI-CI Literacy move instead toward continuous co-learning models. For instance, a law firm doesn’t just train its staff on legal AI tools - it uses AI to facilitate case-based reasoning sessions, where human lawyers critique, challenge, and refine machine-generated suggestions.

From Content Delivery to Cognitive Partnership: 

In many L&D contexts, AI is still used to push content efficiently. But in HI-AI-CI-informed organizations, AI becomes a thinking partner. A healthcare institution might use generative AI to support clinical decision-making workshops, where human intuition and AI logic are jointly evaluated to develop critical judgment, not dependency.

From Hierarchical Expertise to Networked Authority: 

In business settings, this means empowering teams and cross-functional groups to co-validate insights, rather than relying solely on top-down directives. For example, a multinational corporation might build internal knowledge commons where employees across departments, supported by AI tools, collaborate to challenge assumptions, evaluate data sources, and co-create strategy briefs.

From Efficiency Metrics to Reflective Outcomes: 

Rather than measuring success by speed or completion, HI-AI-CI practitioners emphasize reflective outcomes - questions asked, ethical dilemmas explored, or collective sensemaking achieved. For example, a corporate leadership program might evaluate participants on how well they integrate human insight, AI suggestions, and group deliberation under pressure.

These shifts are not cosmetic - they signal a reorientation of organizational identity. In each case, the story being told is clear: intelligence is not a product to be delivered, but a process to be co-created. Learning is not a pipeline; it’s a narrative architecture that shapes how people perceive themselves, others, and their evolving relationship with AI.

To change the outcome, organizations must become narrators of this new reality, not just telling the story, but living it through design, culture, and collective practice.

Conclusion: Crafting the Future Narrative

The transformation from AI Literacy to HI-AI-CI Literacy is more than a pedagogical evolution - it is a strategic redefinition of what it means to learn, decide, and create in a world of accelerating intelligence. Amy Zalman’s insight - “Change the story, change the outcome” - is not a metaphor but a mandate.

This new literacy is not about mastering machines; it is about mastering the art of hybrid cognition. It requires us to design learning environments that elevate human judgment, cultivate ethical reflection, and foster collective intelligence. It places the Human Factor - so often neglected - at the center of AI integration.

HI-AI-CI Literacy challenges organizations to become authors of their own futures. It calls upon educators, leaders, and learners to shift from efficiency to meaning, from automation to augmentation, and from consumption to co-creation. In doing so, we don’t merely adapt to a changing world - we shape it.

Change the story, change the outcome. HI-AI-CI Literacy is our new story.

Learn more

Guy Levi is a learning innovator and AI expert, dedicated to shaping the future of education through universal Generative and Agentic AI Literacy and Fluency. Guy designs transformative learning experiences that empower individuals to think critically, act ethically, and collaborate meaningfully with Generative AI and Agentic Ai. Guy is the co-founder of the AI Shift .Net  
Learn more: Guy Levi on Medium | Guy's LinkedIn page  

Raanan Azoulai is an AI Growth Hacker, a strategic marketing and business development expert and advisor. Raanan believes that while Generative and Agentic AI are transforming every aspect of these fields, it's all about people, their creativity, judgment, and adaptability - that ,must remain at the heart of this meaningful progress. Raanan is the co-founder of the AI Shift .Net 
Learn more: Raanan Azoulai on Medium | Raanan's LinkedIn page