It’s not easy to predict the future. This can be especially true for educators, who are often so focused on our day-to-day that we rarely have time to prophesize. Consequently, we focus on the now, and generative AI is perceived as a direct threat to our daily practice. It completely undermines the work we are doing and the way we assess our students. It’s an extra sore subject for ELA teachers and those who assign regular writing assignments. Take it from Victoria Livingstone, whose viral editorial “I Quit Teaching Because of ChatGPT” paints a solemn picture of an AI-infused world.
To those planning to stick it out – and I hope that’s most of you – you’ll need to be patient. The pendulum of change has swung to one extreme, with autonomy in the hands of students and total freedom over the use of AI tools (outside the classroom, at least). Unfortunately, changes to legislation, policy, and practice always lag behind technological advancements. And while change is never easy (especially in education), with AI, there won’t be much room for debate. We can’t expect Blockbuster to thrive in a Netflix world. We’ll soon have no choice but to revamp a largely antiquated system of schooling that has been in place for more than 150 years.
Moving Forward
For students to be successful in the future workforce, they’ll need a deep understanding of AI and a strong foundation of core soft skills. Rather than fighting the plagiarism battle (or getting caught up in the “teacher time-savers” conversation, for that matter) let’s skip to the good part and focus our energy on preparing for the long-term paradigm shift that will need to occur for our classrooms to create citizens who will serve a new society:
- AI will reframe academic rigor and raise the bar for what we can expect from students. As AI tools become increasingly vetted, safe, useful, and ubiquitous, we’ll see more and more schools implement student-friendly policies that endorse AI usage. It’s already happening in higher education and is only a matter of time before it infiltrates K-12 classrooms. This will eventually create an urgency to update academic standards and curriculum, and even to create new courses. Pretty soon, students will be able to accomplish so much more in a shorter amount of time. Why would we hold them back?
- Teachers will officially need to redefine their roles from traditional knowledge givers to facilitators of learning experiences. This should excite us, not scare us. In most cases, it might mean teachers should “do less” and truly embrace learner-centered strategies that put more ownership, responsibility, and autonomy on students. Consider the teacher of the future an “experience architect;” they set up great conditions for learning, then get out of the way. Luckily, students will always need us for the human part of teaching – the coaching, mentoring, motivation, guidance, and support – that AI could never replicate. Luckily, this is often the most rewarding part of teaching anyway.
- AI urges revisions to (or elimination of) standardized testing by revealing a mismatch between high-stakes assessment and real-world skills. ChatGPT recently performed in the 90th percentile on the Bar Exam. Unless we plan on using Generative AI to replace lawyers, it’s clear that this assessment does not reliably predict real-world legal competence. And it’s not just the Bar Exam; ChatGPT also dominated the GRE, SAT, and many AP exams. As AI models continue to improve, more assessments will lose their value. In their place, we’ll need to usher in new standards-based, performance-driven forms of assessment that measure student achievement in nontraditional ways.
The AI in education conversation is often compared to the monumental shift to classroom practice brought on by calculators in the 1980s. Resistance was strong at first but eventually, mathematics pedagogy, standards, and assessment have become intertwined with this technology to embrace a new normal. Teaching evolved to include more mathematical reasoning, standards rose to new heights, and assessments became more problem- and process-oriented. It took more than 20 years, but we are better off because of it. Let’s not wait that long again—let’s embrace AI now as a powerful catalyst for meaningful change.
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