8 Ethical Ways Teachers Can Use AI in Their Classrooms

Forbes

2 days ago

Nearly three in five teachers — 60% — now report using AI in their daily practice, signaling that AI is no longer a futuristic concept but today's educational reality (Kiplinger). Schools and systems that ignore this shift risk being left behind.
At the same time, rapid adoption has surfaced pressing concerns—about privacy, algorithmic bias, and whether AI will support or undermine the human-centered teaching that matters most.
8 Ethical Ways Teachers Can Use AI In Their Classrooms
Here's a roadmap to integrate AI into classrooms ethically, effectively and inclusively for:
• Teachers and school leaders seeking high-impact, real-world strategies that preserve equity, foster agency, and strengthen relationships.
• AI companies and developers aiming to create tools educators don't just use, but endorse, shape, and build with.
AI can be a powerful assistant for teachers, says Randi Weingarten, president of the American Federation of Teachers (AFT), helping with tasks like lesson planning, IEP writing, and personalizing materials—freeing more time for building relationships. But she warns the current school landscape is a 'Wild West' with minimal regulation, leaving student privacy, equity, and teaching integrity at risk.
Her solution is proactive: AFT, Microsoft, OpenAI, and Anthropic launched the $23 million National Academy for AI Instruction to give 1.8 million educators free AI training—ensuring they have both the skills to use AI effectively and the leverage to shape how it's built. She stresses that AI's impact differs depending on whether it's teacher-facing (assisting educators behind the scenes) or student-facing (direct use with students), the latter requiring stricter guardrails. Weak policies can amplify bias, especially against marginalized populations.
Weingarten cites AFT's Commonsense Guardrails for Using Advanced Technology in Schools and the AI Educator Brain webinar series on Share My Lesson as practical resources for both teachers and developers. Her advice: start with AI literacy—understanding where AI gets its data, how it works, and how to spot errors or bias. New users should begin with a few safe, teacher-only tools, try them even if hesitant, and move slowly; engaging students with AI 'requires more time and a deeper understanding.'
Harvard psychologist Howard Gardner sees AI as the long-awaited key to truly individualized learning—something that, in the past, only the wealthy could access through private tutors. 'Now, thanks to AI, we can present materials in multiple ways, matched to the learner's interests and preferred modes of engagement… a perpetually evolving personalized tutor.'
He cautions that such power must be used ethically, with all stakeholders—students, teachers, parents, and peers—agreeing on what constitutes proper use and avoiding what he calls 'pedagogical or student malpractice.' From a developmental standpoint, Gardner notes that AI's lack of true authority can confuse younger learners. Pre-teens often struggle to detect misinformation or nuance, so early use should be closely supervised. Older students can better handle complexity, debate, and contradictions.
Ethics, he says, must be grounded in honesty, not surveillance: 'In a democracy, we rely on people's honesty rather than spying on them all the time and reporting what's been learned to Big Brother or Big Sister.' While he doubts the U.S. will lead on AI ethics in the near term, Gardner believes Europe may set the example. For getting started, he recommends practical thinkers such as Ethan Mollick (Co-Intelligence), Stephen Kosslyn (Minerva University), and Yuval Harari—and, above all, regular colleague conversations to exchange resources, examples, and lessons learned. Looking ahead, he predicts schooling will become more like children's museums or hobby clubs—hands-on and exploratory (see his blog post).
Practical, high-impact uses include:
• Lesson planning and differentiated instruction.
• Individualized Education Program (IEP) drafting and report writing.
• Accessibility support for diverse learners.
• Generating multiple representations of a concept to match different learning styles.
Gardner sees AI as a 'perpetually evolving personalized tutor' that adapts to each student's interests and needs—something historically reserved for those who could afford private tutors. For Weingarten, the key is to make AI a time-giver for teachers, freeing them to focus on relationships and in-person learning.
Franklin School in Jersey City, NJ, shows what happens when the conversation shifts from if to how. Director of Innovation Jaymes Dec describes the approach as moving students 'from being passive consumers of technology to active designers and problem-solvers.' Projects are embedded into existing courses, supported by teacher training, and energized by partnerships with technologists and parents.
Students have created accessibility tools and custom chatbots that act as college counselors, book recommenders, and homework helpers. Franklin's custom AI agent, Sparkz—built with Animated Intelligences—can be tailored to any topic or project. Internal classroom versions give students feedback on presentations before they deliver them, while public-facing versions, like those used during the school's global Sparkathon, act as 24/7 mentors offering targeted feedback on student pitches. Cross-disciplinary projects are common: in one, AI students coded chatbots to simulate Big Five personality traits designed by psychology classmates, then evaluated results against validated surveys.
Head of School William Campbell emphasizes that the work builds technical skills and habits of mind—curiosity, resilience, systems thinking—alongside ethical reasoning and collaboration. Franklin serves as North America's lead node for the Fab Learning Academy, providing hands-on AI professional learning for teachers. The school has been named a Top 10 Finalist for the World's Best School Prize for Innovation.
What others can try now: Start small with one AI project that solves a local need; co-design with students; and avoid unreliable AI-plagiarism detectors that erode trust. Free tools like Teachable Machine and beginner-friendly Python projects using OpenAI or Anthropic APIs can help teams prototype quickly and safely.
Global education change expert Michael Fullan cautions against mistaking adoption for progress: 'AI provides the illusion of modernity. If it is not linked intimately with human purpose it will be inevitably superficial… a sure recipe for superficial learning.' He notes that AI's potential and risks are equally relevant in any setting—whether strengthening equity or widening gaps—depending on how it is used.
He points to the Ottawa Catholic School Board—45 schools serving roughly 89,000 students—as a model sequence:
• AI literacy (including ethics)
• AI certification (practical skills for use)
• Transformation at scale—embedding critical thinking for all, and rethinking assessment and evaluation
For educators feeling overwhelmed, Fullan's advice is to start with pedagogy, not technology; prioritize ethics and equity; communicate a clear vision; invest in human capital; and foster a culture of experimentation and learning.
Both Gardner and Weingarten warn against:
Over-reliance on AI-generated content without human review. AI should always be checked for accuracy and appropriateness before use.
Using AI to replace authentic teacher-student connection. Its role is to free up time for human relationships, not diminish them.Ignoring equity—AI can perpetuate harmful stereotypes and compromise student privacy if not designed and monitored inclusively. Protecting marginalized populations and ensuring safe, ethical use must be central from the start.
For AI companies, this means bias testing, inclusive design, and transparent sourcing are not optional—they are foundational to trust.
Weingarten emphasizes starting with AI literacy for both teachers and students: how AI works and where its data comes from; how to spot errors or bias; and how to verify outputs with trusted sources. Her union's 'commonsense guardrails' guidance offers a framework schools and developers can adapt. Practical first steps:
• Limit early AI use to teacher-facing tools.
• Develop clear policies for student-facing AI before deployment.
• Give teachers protected time to test and shape tools before rollout.
She adds a note of patience: engaging students with AI 'requires more time and a deeper understanding.' Go slow to go far.
Gardner believes AI will help transform schooling into more hands-on, exploratory learning communities. Weingarten's focus is ensuring that transformation is led by educators, not imposed on them. The message to both audiences is clear:
• For teachers: AI can be a powerful ally if you take the lead in shaping how it's used.
• For AI companies: Your best products will come from listening to, partnering with, and being guided by educators.
One final thought—what we measure still shapes what we value. If AI can coach, adapt, and even create alongside students, how do we judge what's 'real' learning? Who decides what matters most when knowledge is no longer scarce? And what happens to grading, testing, and credentialing when the work in front of us may have been co-authored by a machine?
Assessment expert Dylan Wiliam once warned: 'The most important assessment decisions are taken in rooms with no adults present.' In the age of AI, that room might include an algorithm—and the stakes for getting it right couldn't be higher.