Artificial intelligence takes schooling to the next level

Key Concepts

• Virtual Reality (VR) Enhanced Learning: Immersive educational experiences utilizing VR technology.
• Generative AI: AI models capable of creating new content (text, images, etc.).
• Large Language Models (LLMs): AI models trained on vast amounts of text data, used for various language tasks.
• Small Language Models (SLMs): Focused AI models utilizing curated datasets for safer, more controlled learning environments.
• AI Regulation: The development and implementation of rules and guidelines governing the use of AI, particularly concerning children’s safety and data privacy.
• Data Privacy: Protecting personal information collected and used by AI systems.

Transforming Education with AI and VR

Erica Donalds, Chair of Education Opportunity at America First Policy Institute, discussed the potential of AI and VR to revolutionize education, specifically through Optima Ed and Optima Academy Online – the world’s first virtual reality school. The impetus for creating this platform stemmed from a need for school choice and high-quality educational options, particularly highlighted during the COVID-19 pandemic. Optima Academy allows students to experience learning immersively, going beyond traditional textbook methods. Students can “visit” ancient Rome, travel to the moon, or explore the interior of a cell using VR headsets, either at home or in a classroom setting. This “magic school bus style” learning aims to make education more engaging and accessible.

Addressing Concerns About AI and Cheating

A key concern raised was the potential for AI to facilitate cheating. Donalds countered this by emphasizing the need to proactively guide AI usage for learning enhancement rather than allowing students to dictate its application. She cited an example of teachers instructing students to use AI to generate questions about their essays, fostering deeper understanding and creativity. The core argument is that controlling how AI is used, rather than banning it outright, is crucial.

Parental Controls and Data Privacy

The discussion highlighted a significant gap in awareness: 70% of teens used generative AI last year, yet 83% of parents report schools haven’t addressed it. Donalds outlined several guardrails for parents and schools. These include prioritizing data privacy, implementing filters for content accessed through large language models, and developing smaller, curated language models (SLMs) containing trusted information. Transparency is also paramount, with parents needing access to logs of their children’s AI interactions. She noted that Florida schools are already adopting policies to address these concerns. A report indicated that 42% of children use AI for companionship, a phenomenon Donalds contextualized as a modern equivalent of past childhood attachments like Teddy Ruxpin or lifelike robotic pets, emphasizing the need for safe and educational applications.

The Need for National AI Regulation

The conversation shifted to the broader landscape of AI regulation. New York recently passed a comprehensive AI safety bill, but White House AI advisor David Saxs warned that a unified Republican approach behind President Trump’s proposed “one rule book” is necessary to prevent states like New York and California from unilaterally setting national standards. Polling data from Tony Frizzio revealed that a majority of voters favor a national standard for AI safety, particularly concerning children. Donalds agreed, stating that a patchwork of state regulations would hinder innovation and national leadership in the AI space. She argued that the rapid pace of AI development necessitates a federal standard, while also acknowledging the role of teachers and school districts in implementing their own safeguards through existing IT programs.

As Donalds stated, “we need a federal standard, especially when it comes to our student safety.”

Logical Connections & Synthesis

The discussion flowed logically from the introduction of VR-enhanced learning to the challenges and opportunities presented by AI. The concerns about cheating and companionship were presented as natural anxieties, but were then addressed with proactive solutions focused on responsible AI integration and parental involvement. The final segment broadened the scope to the national regulatory landscape, framing the need for a unified federal approach as essential for fostering innovation and ensuring student safety.

The central takeaway is that AI is not inherently detrimental to education; rather, its potential can be unlocked through careful implementation, proactive safeguards, and a collaborative effort between educators, parents, and policymakers. Ignoring or outright banning AI is not a viable solution; instead, a focus on responsible use, data privacy, and a national regulatory framework is crucial for harnessing its transformative power.