Should Teachers be AI Certified?

Urie Bronfenbrenner, a Russian-born American psychologist, is best known for developing ecological systems theory, which emphasizes that humans develop through a series of multiple, nested layers of influence. These layers embedded in nested systems are not just psychological; they involve cultural, economic, political, and social elements as well. The nested systems create cross interactions between different agencies, groups, spaces, and times. Developmental movements range from the immediate environment (microsystem), crossing connections between the indirect environment (exosystem), which ultimately leads to long-term growth over time (chronosystem). The dynamic interactive stimuli that occur across systems can have a positive or negative progressive impact, which will either accelerate or stagnate growth. Bronfenbrenner’s theory is not dissimilar to Russian psychologist Lev Vygotsky’s Sociocultural Theory (SCT), which posits that human cognitive and social development occur through communal, reciprocal interactions. Both theories are also similar in that it is hypothesized that they are not specifically time-bound but rather transpire as a cyclical process occurring in transitional phases.

As we continue to navigate the rapidly changing educational systems that are increasingly influenced by AI, we must be able to make sense of not only what changes are happening but also how we can understand their cumulative temporal influence on human-to-human and technology-to-human educational modalities and teacher preparation. To make sense of these changes, it is imperative that our understanding of AI’s transformational potential is deliberate, pragmatic, and not heuristic. This compels understanding that AI is not a fixed, static technology but rather one of progression whose meaning and impact will change and shift as teachers, students, and educational entities change alongside it. From a systems perspective, this would implicate the outermost layer of Bronfenbrenner’s model, the chronosystem, which focuses on the role of time. Specifically, it associates how individuals and institutions adapt and reinterpret their individual and collective experiences over a sustained period.
Chronosystem thinking can enable educators and educational stakeholders to more deliberately and intentionally move the conversation from AI as a trend to AI as transformational. Here, we can also suggest both Bronfenbrenner’s and Vygotsky’s positions that for human development across interactions and systems to result in overall positive growth, there must be early, scaffolded interventions that can facilitate sustained development. In the case of transitioning teaching and learning modalities to be more AI-infused, the question moves from asking if teachers should be AI-certified to why certification is essential in creating an educational future that is ethical, impactful, innovative, and stable.

We have already seen the influence that AI, particularly generative-AI (gen-AI) has had in traditional human-centered instruction and digital-to-human instruction. Tools like ChatGPT, Gemini, Claude, and Khanmigo are already being used by educators to supplement traditional classroom routines, from lesson planning to classroom management to personalizing student tutoring in real time. Teachers and administrators are also using data from these programs to improve curricula and processes, especially in schools and districts that rely heavily on distance and virtual learning programs. So, administrators, educators, and school districts are now faced with the pivotal question: Given the seemingly precipitous integration of AI, should it be a requirement for teachers to be certified in AI, and should that certification include ethical AI use?

Initial consideration of this question seems to be more procedural; in other words, administrators and teachers may deem this certification more technical than practical and just another professional development box to check in an already demanding profession. However, the issue is much deeper, especially when considering the potential transformations in ethics, institutions, and systems. Thus, chronosytem thinking reminds us that within educational ecosystems, human relationships, institutional interactions, and integrated technologies change over time. What may be the heuristic technology of the moment may eventually become either outdated, normalized, or, in some cases, regretted (see the rapid integration of smartphones in K-12 schools). The meaning or intent that we currently assign to AI, i.e., convenience, efficiency, novelty, may drastically change if guardrails such as teacher certification in AI are not in place. Implementing AI is not a neutral practice like more static technical skills, such as creating a document or slide deck; it is fundamentally reshaping what it means to be a teacher and a learner in the modern 21st-century classroom. We are entering an era of new educational realities that directly impact not just immediate learning but also have profound, systemic implications for educational identities and societal changes. Through the chronosystem lens, we must consider AI’s broader after-effects that could include the following: 1. Overdependency leading to reduced human productivity; 2. Skill erosion leading to cognitive atrophy; and 3. Ethical passiveness leading to less sensitivity to biased, myopic, or opaque systems.

Finally, this leads us to consider the importance and urgency of teachers, and arguably all educational stakeholders, receiving AI certification. While some may argue that it is just another layer of bureaucratic control, it is about being intentional, responsible, and transparent across systems. In a sense, it is less about digital literacy and technical aptitude and more about future-focused human stewardship over AI’s ethical implications and sustainable implementation. Considering AI certification requires us to be reflective and have foresight when contemplating its viability in educational and societal systems, such that we are temporally co-constructing its use across systems as we continue to integrate AI into our traditional teaching and learning practices. A chronosystem mindset will move us from AI as a fleeting trend to AI as systemically transformational.