Episode 2: Rethinking Agency in the Age of AI: Why Does Agency Matter in the Age of AI?
Authors: Teddy Kim; info@ciddl.org
In the First Episode of this series, we explored how artificial intelligence (AI) influences student agency through the lenses of Social Cognitive Theory (Bandura, 1989), Self-Determination Theory (Deci & Ryan, 2012), and Causal Agency Theory (Shogren et al., 2017). We saw that AI can either support or undermine student agency depending on how it is designed and used. However, to fully understand why student agency matters in the age of AI, we need to take a broader view—one that considers societal and ethical dynamics.
This brings us to two powerful concepts: the Crisis of Moral Patiency (Danaher, 2019) and Triadic Agency (Johnson & Verdicchio, 2019). These frameworks warn us about the broader implications of human–AI interactions, asking us to consider not just how AI works but how it reshapes human roles, responsibilities, and identities. Most importantly, they challenge us to prepare intentionally: How are humans positioned in Human-AI Interaction? As passive users or empowered agents of change?
What is a Student Agency?
Before we explore how AI impacts student agency, it is essential to clarify what we mean by the term. According to the OECD (2019), student agency refers to the capacity and willingness of students to set goals, reflect on their actions, and act responsibly to effect change. It’s about being an actor, not a bystander—shaping the world rather than being shaped by it.
Student agency is not just about giving students more choices or encouraging independence. It involves a deep sense of ownership, purpose, and responsibility in learning and life. When students are agents in their learning, they are more likely to be motivated, set meaningful goals, and persist through challenges. They learn how to learn—and more importantly, why to learn.
The Crisis of Moral Patiency: When Action is Outsourced
According to John Danaher (2019), the “Crisis of Moral Patiency” suggests that as AI and robotics increasingly take over aspects of human life, including jobs, decision-making, and even daily routines, our opportunities to express moral agency may diminish. Danaher is not claiming that humans will lose their moral status, but that the increasing presence of intelligent systems may suppress the need for humans to act intentionally or take moral responsibility. As machines become more capable, humans may become more passive.
Danaher identifies three key areas where this shift is most visible: the workplace, political and legal decision-making, and personal life. Work has traditionally been a primary domain for moral agency—it’s where we contribute to society, support our families, and develop virtues like responsibility and perseverance. If AI removes this role, we may also lose a critical space for exercising agency. Similarly, as algorithms replace human judgment in public policy and legal systems, our participation in shaping society may decline. Even in our personal lives, AI assistants are beginning to make decisions on our behalf, potentially undermining our ability to reflect, grow, and develop character. The more comfortable these systems become, the less inclined we may be to act.
This is not just a philosophical concern. It is a practical warning. If we are not intentional about how AI is integrated into our lives and institutions, we risk raising a generation of learners who no longer see themselves as agents of change but as recipients of machine-driven outcomes.
Triadic Agency: Clarifying Human Roles in AI Systems
Triadic Agency is a model developed by Johnson and Verdicchio (2019) to account for how outcomes in AI-mediated contexts are co-produced by three essential components: the user, the designer, and the artifact. The user sets goals and commissions the creation of a system; the designer translates those goals into an artifact; and the artifact provides the causal mechanisms necessary to achieve the goal. This framework shows that responsibility is not reducible to any one component alone—each plays a constitutive role. While artifacts may lack intentionality, they are still causally efficacious. Responsibility, however, remains with the human agents (users and designers), as they alone possess intentional agency. Triadic agency thus provides a practical heuristic for tracing accountability in real-world AI systems where human intentions and machine functions are deeply entangled.
For example, imagine a high school student working on a personal narrative essay for an English class. The student (user) wants to improve the clarity and tone of their writing, so they turn to an AI tool based on Generative AI (e.g., ChatGPT, Gemini, Perplexity) for support. The AI tool was developed by engineers (designers) to analyze written input and generate suggestions for clearer phrasing, grammar corrections, and improved sentence flow. The AI system (artifact) provides real-time feedback, offering sentence rewordings and example transitions based on the student's original draft. The student selects which suggestions to use and revises the essay accordingly.
In this case, the final product results from the interaction of three elements: the student's goal and choices (user), the intentional design of the system (designer), and the AI's generative capabilities (artifact). Although the artifact contributes to the writing process, it lacks intention. Responsibility for the content and use of the AI’s suggestions ultimately remains with the student.
Why Is Focusing on the User Perspective Important?
As educators and researchers, most of us are not used to designing AI systems or engineering complex algorithms from scratch. Instead, our role lies in how we engage with these tools, as users. That’s why we need to focus on the user's perspective intentionally. We must teach our students how to select tools appropriately, use them responsibly, and critically reflect on the impact of AI. This is the space where educators hold both the most significant influence and the greatest responsibility. We have to ask ourselves: What should we be paying attention to when using AI? What skills and awareness do we need to develop in ourselves and our students? And how do we ensure that AI tools enhance rather than diminish the agency of the learners we serve? (CIDDL, 2024)
Looking Ahead
This blog series aims to address these questions by providing a deeper understanding of how artificial intelligence influences the learning experience. By placing student agency at the center of our exploration, we seek to help educators, researchers, and families guide learners to interact with AI in meaningful and intentional ways.
Future blog posts will present key research findings on how artificial intelligence influences students’ autonomy, motivation, and ability to make decisions. These entries will examine both the benefits, such as personalized learning and improved access to resources, and the potential challenges, including overdependence on automated systems, decreased self-reflection, and a weakening of moral responsibility. Through these discussions, we aim to provide clear and practical insights that help create learning environments where technology enhances, rather than limits, human agency.
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