Navigating the AI landscape 

Helping students and educators recognize AI-generated content 

By the NJEA Technology Committee 

As generative AI quickly evolves, distinguishing between authentic human work and increasingly sophisticated AI-generated content, including writing, images and video, is now a core educational challenge. Since current AI-detection software is unreliable and often produces false positives, both students and educators must develop strong critical media literacy skills. Research shows that AI-detection software is often unreliable and prone to false positives, making a human-centered approach—one that is focused on evaluating style, accuracy and authenticity—the most effective strategy.  

Recognizing AI-generated text 

AI writing often appears polished but lacks the individuality of human work. It typically includes repetitive or formulaic phrases and misses personal voice or class-specific insight. AI hallucination is the term used to describe AI-generated content that seems real but is false, misleading or made up. When writing feels generic or avoids referencing discussions, lessons or personal experiences, it may indicate the use of AI. 

Recognizing AI images and deepfakes 

AI-generated images frequently include distorted details such as extra fingers, inconsistent shadows, warped backgrounds or misshapen text. Deepfake videos may show unnatural movements, poor lip-syncing, or mismatched audio and lighting. Teaching students to use reverse image search and metadata tools strengthens their ability to verify authenticity. Educators can use sites such as detectfakes.kellogg.northwestern.edu from Northwestern University’s Kellogg School of Management to have students review AI-generated images and foster discussion about their ethical use and potential misuse. 

Instructional approaches for educators 

Instead of focusing on policing AI usage, experts advise redesigning learning experiences. Assignments that involve analysis, personal reflection, interviews, or referencing specific class content are harder for AI to mimic. Process-based assessments such as drafts, AI-use statements and class discussions encourage transparency and accountability. 

These principles apply to teaching students and educators of all ages about artificial intelligence and critical content recognition. 

  • Start young: Introduce foundational AI ideas beginning in the early years. 
  • Teach the mechanics: Focus instruction on how AI works, not just on operational use. 
  • Foster skepticism: Cultivate critical thinking by encouraging students to question, verify and be skeptical of all AI outputs. 
  • Address ethics: Cover essential topics such as data privacy, deepfakes and the responsible use of AI tools. 
  • Support educators: Provide teacher training to ensure educators have the skills to integrate AI effectively and knowledgeably into their lessons. 
  •  Be contextual: Tailor the use and discussion of AI to the specific subject or context.  

To prepare students for a world where digital manipulation is standard, schools must shift from relying on detection tools to teaching verification, critical thinking and digital provenance skills. This is done by tracing the origin, authenticity and creation process of online content to determine whether it is real or manipulated. By teaching students to verify sources, check metadata and confirm the origins of digital media, educators help them navigate an online world where misinformation and AI-generated content are increasingly common. The new normal is to treat all online content as potentially altered until proven otherwise. 


The NJEA Technology Committee

Sabina A. Ellis, chair, Essex County  

David Ahn, Bergen County  

Christopher Bowman, Burlington County  

Patricia M. Martel, Camden County  

Jonathan A. Gonzalez, Cumberland County 

Salvatore A. Randazzo, Gloucester County  

Daniel G. Abbadessa, Hudson County  

Olive M. Giles  , Mercer County  

Deana Baumert, Monmouth County  

Raymond A. Vikete , Morris County  

Lori E. Lalama, NJREA 

Melissa Krupp, Ocean County  

William A. Krakower, Passaic County  

Christopher J. Cook, Sussex County  

Jasmine Y. Slowik, Warren County    

Resources 

Britannica Education: Spotting AI 

MIT Sloan: AI detectors don’t work. Here’s what to do instead

TurnitinGuides: AI writing detection 

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