Generative AI Resources

Generative AI (GenAI) in Oregon's Schools:

The field of Artificial Intelligence (AI) will continue to grow at a rapid pace, with new abilities, new platforms, and new functions appearing frequently. This webpage includes resources to support educators with the rapid evolvement of Generative AI in K-12 education settings.

Important News & Resources

ODE Will continue to update existing guidance and will be working to regularly add additional resources for educators and school leaders. Most recently, these updates have included:

Moving the previous Generative Artificial Intelligence in K-12 Classrooms guidance document (v2.0) into the current v3.0 web-based interactive guide you see below. [LINK TO BE ADDED TO FULL v3.0 PDF of Guidance]
A recent collaboration with Willamette ESD, and educators across Oregon, in the creation of an AI Resource Toolkit is nearing completion. This toolkit is meant for educators, schools leaders, librarians and instructional coaches is meant to be a foundational starting point to help them deliver high quality professional development on Generative AI to their school staff. This is COMING SOON and will be posted here and on Oregon Open Learning.
v2.0 Developing Policy and Protocols for the Use of Generative AI in K-12 Classrooms guides leaders through a process for developing guidance or policy related to the safe, ethical, equitable, and effective use of genAI.
Our Resources for the Educational Use of Generative AI in K-12 Classrooms is regularly updated and revised, please check it out and bookmark it if you have a chance.

Generative Artificial Intelligence in K-12 Classrooms

As artificial intelligence becomes a familiar presence in education, the focus is now shifting to how it can potentially be integrated into our schools in ways that genuinely help enhance personal connection, improve teaching and learning, open up new opportunities for all, and help propel our students into an ever-changing workforce.

This is the third publication of this guidance document for generative artificial intelligence (genAI) for K–12 classrooms. While artificial intelligence (AI) typically refers to computer systems designed to perform tasks that usually require human intelligence, generative AI is a specific type of AI that can create new content, or output, including text, images, video or computer code, all based on patterns it detects and applies from its vast datasets. This guidance primarily focuses on genAI, given its rapid emergence in schools, but also references AI more generally when and where appropriate. The focus of this guidance shifts from introducing genAI to educators, to providing practical guidance on how to implement it safely and effectively in schools and classrooms, with the goal of enhancing student outcomes and helping prepare them for the future.

As AI tools become more common across instruction and operations, Oregon school districts may find it helpful to approach AI use as a system-level leadership and planning consideration rather than only a one-off software adoption or an individual classroom choice. Because these tools can influence teaching practice, student learning, data privacy, and community trust, districts should establish clear local policy and processes for reviewing and guiding how AI is introduced and used. Thoughtful coordination across instructional leadership, technology, and student support teams can help ensure that new tools align with learning goals, support educator expertise, and are regularly reviewed for impact on students and staff. Communicating transparently with the entire school community about if, how and why AI tools are to potentially be used can further strengthen understanding and trust. This guidance is intended to support districts as they consider what local structures and decision-making processes best fit their context.

1. Framing Responsible and Human-Centered Generative AI (GenAI) Use

As generative AI continues to reshape education, it is crucial for school leaders and educators to have a clear, values-driven framework to help guide decisions about if, when, and how to integrate this powerful technology. ODE’s AI Guiding Principles centers responsible and equitable use to empower educators and students, supported by foundational principles that ensure these tools help enrich learning while maintaining essential human connections. These principles prioritize ethical practice and future readiness while promoting transparency, inclusivity, and continuous evaluation to prepare students as creators, critical thinkers, and problem solvers in an AI-driven world. At the heart of this vision is a pivotal question:

How will genAI use in your school enhance student learning and well-being today, while also nurturing the durable skills and creativity they will need to tackle the challenges of tomorrow?

Guiding Principles for GenAI in K–12 Education

We must empower our young people to stand as ethical creators, not passive consumers of the technologies that will define their time. Through education that sharpens their thinking, strengthens their literacy, and grounds them in responsibility, we work to prepare them to shape a future built on integrity and human ingenuity.

I. Human-Centered Learning Comes First

GenAI must never replace authentic relationships between educators, students, and peers. Its use should protect and strengthen students’ critical thinking, creativity, and independence, not diminish them. The use of AI should also support, not replace, the professional expertise and judgment of licensed educators, whose understanding of students, context, and learning needs remains essential to instructional decision-making.

Guiding Question: How will genAI be used to support, not replace, student engagement, well-being, critical thinking, and teacher-student or peer-to-peer relationships?

II. Purposeful and Evidence-Based Adoption

GenAI should only be integrated when it demonstrably enhances learning, engagement, and instructional quality. If adoption is to take place, use should be transparent, safe, and grounded in sound pedagogical reasoning. Decisions about whether and how to use genAI should remain guided by educator expertise and local instructional priorities.

Guiding Question: What criteria and evidence will we use to evaluate the accuracy, reliability, and educational value of genAI tools, and are non-AI alternatives sufficient to meet the need?

III. Equity and Access for All Learners

Every student should have equitable access to the same technologies and tools, instruction, and literacy, ensuring all learners are prepared to thrive, and lead, in an increasingly AI-driven world.

Guiding Questions:

How will we ensure that all students, including those with disabilities, multilingual learners, and those furthest from opportunity, can benefit from safe, meaningful AI use?

How will we address disparities in access to devices, connectivity, and the foundational digital literacy needed to engage with genAI?

IV. Ethical Use and Informed Practice

Districts should establish safe ethical AI-use policies and provide sustained professional learning for educators, staff, and students. Instruction should address genAI bias, dis and misinformation, and academic integrity to foster critical and ethical engagement.

Guiding Questions:

What ongoing professional development, student learning opportunities, and policy safeguards must be in place to ensure ethical, safe, and transparent genAI use?

How will students be taught to identify genAI bias, avoid misinformation, and uphold academic integrity?

V. Continuous Evaluation, Future Readiness, and Community Partnership

The use of AI in education should be regularly assessed to ensure it advances learning outcomes, centers equitable practices, and addresses sustainability and safety. Schools should also prepare students for the world they are entering and not just the one they inhabit today. Ongoing accountability and inclusive engagement with the whole school staff, students, families, and the school community are essential.

Guiding Questions:

Who is responsible for monitoring AI use and ensuring it aligns with up-to-date research, equity goals, and student safety?

How will school leaders regularly evaluate AI’s impact on teaching, learning, and future readiness across student groups?

VI. Future-Ready Learning and Workforce Preparation

AI integration should support students in developing the durable skills, adaptability, and ethical grounding they need to succeed in the careers and civic life of the future.

Guiding Questions:

How will our AI policy and implementation strategies ensure all students have the opportunity to develop the critical, creative, technical, and durable skills to not just use, but design and shape the technologies of the future?

How are our AI-implementation policies and strategies helping to ensure that students use genAI as a tool to extend, rather than replace, their own critical thinking, creativity, and memory so to help prevent cognitive offloading or atrophy of essential skills?

We are now seeing a rapid rise in AI tools developed specifically for schools. We are also seeing a growing number of Oregon school districts implementing these AI tools into regular daily use. It is important to remember that although AI has been integrated into educational tools for decades, and emerging research suggests some generative AI tools may benefit student learning, much more empirical evidence is needed to fully understand their impact in schools.^1,2

The U.S. Department of Education Office of Educational Technology’s Artificial Intelligence and the Future of Teaching and Learning emphasizes the importance of keeping humans in the loop when using AI, rather than machine-centered policies. The authors use the following metaphor to describe its use noting that “teachers, learners and others need to retain their agency to decide what patterns mean and to choose courses of action.”

We envision a technology-enhanced future more like an electric bike and less like robot vacuums. On an electric bike, the human is fully aware and fully in control, but their burden is less and their effort is multiplied by a complementary technological enhancement. Robot vacuums do their job, freeing the human from involvement or oversight.

It remains essential that:

Educator knowledge and expertise is honored in decision making when implementing genAI in schools, and
Educators and students receive ongoing high-quality training and education on the responsible, ethical and productive use of generative AI tools.

Key Terms Important for Understanding GenAI:

Artificial Intelligence: “Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.”³
Generative Artificial Intelligence (GenAI): Generative AI is a type of AI that can create new content, or output, like text, images, video, audio or computer code. It often responds in a human-like nature in response to user input.
AI Literacy: Digital Promise defines AI literacy as, “the knowledge and skills that enable humans to critically understand, evaluate, and use AI systems and tools to safely and ethically participate in an increasingly digital world.”
Cognitive Offloading / Atrophy: Cognitive offloading is the practice of relying on external tools to “offload” mental tasks. AI is one tool to offload tasks to, but using things like wooden blocks and other math manipulatives are considered offloading. Cognitive atrophy can occur when a person has a decline in their internal cognitive abilities due to too much offloading of thinking tasks.^4,5
Durable Skills: Sometimes called transferable skills or soft skills, these skills are the lifelong skills that will help to enable a student to be successful throughout various aspects of their lives, including in their professional work. Ideally, they will continue to be important skills to have regardless of how technologies and other facets change the future workforce.⁶
Personally Identifiable Information (PII): Through ORS 339.329(c) the state of Oregon defines PII as “any information that would permit the identification of a person… and is not limited to name, phone number, physical address, electronic mail address, race, gender, gender identity, sexual orientation, disability designation, religious affiliation, national origin, ethnicity, school of attendance, city, county or any geographic identifier included in information conveyed… or information identifying the machine or device used by the person…”
Synthetic Media: Digital content (i.e. images, videos or audio recordings) that are fully or partially created or altered using genAI tools. Deepfakes are synthetic media developed specifically for the goal of appearing real (i.e. photorealistic) and / or authentic (i.e. portray known people, events, etc.) with the purpose of deceiving the viewer, often with the purpose of spreading mis or disinformation.
Misinformation and Disinformation: Misinformation is false or inaccurate information, simply getting the facts wrong, but passing it on anyways. Disinformation is the purposeful, deliberate spread of false information, intentionally mistating facts.⁷
AI Companions: GenAI tools like chatbots or digital avatars that are specifically designed to mimic human-like interactions often meant to hold life-like personal conversations, offer emotional support and companionship. Popular genAI companion tools include Character.ai , Anima, and Kindroid.
Sextortion: A serious crime that occurs when someone threatens to distribute your private and sensitive material if you don’t provide them images of a sexual nature, sexual favors, or money.⁸
Image-based Sexual Abuse (IBSA): The nonconsensual creating, taking, or sharing of intimate images and threatening to share images. It can also include coercing someone into sharing intimate images, or sending unwanted intimate images.⁹
Child Sexual Abuse Material (CSAM): Any visual depiction of sexually explicit conduct involving a person less than 18 years old.¹⁰
Non-consensual intimate imagery (NCII): The act of sharing intimate images or videos of someone, either on or offline, without their consent. This does include manipulated images / deepfakes.¹¹

As genAI continues to rapidly reshape education, its rise in popularity raises big questions about the future our students are stepping into.

What jobs will exist after graduation?

How will AI impact our environment?

Will these tools narrow opportunity gaps or widen them?

While AI can expand access to learning, its use also risks deepening inequalities without strong, well-developed human and equity-centered policies and practices. With genAI now regularly embedded into digital learning platforms and helping to make curricular decisions such as generating complete lesson plans for classroom educators, school leaders should act thoughtfully and proactively.

The authors of the recent publication, Time for a Pause: Without Effective Public Oversight, AI in Schools Will Do More Harm Than Good, from the National Education Policy Center at the University of Colorado Boulder, School of Education, put the risk succinctly:

Yet, important discussions about AI’s potentially negative impacts on education are being overwhelmed by relentless rhetoric promoting its alleged ability to positively transform teaching and learning. The result is that AI, with little public oversight, is on the verge of becoming a routine presence in schools.

ODE is not suggesting districts stop adopting AI tools altogether. The NEPC report urges school leaders to slow down the process, take time to ask critical questions, and ensure adoption happens responsibly, ethically, and productively. It also emphasizes that any implementation of these tools will benefit from being paired with ongoing AI training, specifically including AI literacy training, for all school staff and students.

This caution fits a broader emerging pattern. In 2026 Congressional testimony, neuroscientist Dr. Jared Cooney Horvath shared that international test data consistently shows more classroom screen time linked to lower scores in reading, math, and science. A growing body of research is starting to show that educational technology and digital tools (save adaptive practice programs) are not substitutes that outperform regular classroom teaching. This track record suggests schools should be realistic about what technology can and can't do.

ODE’s genAI companion policy and guidance document is a step-by-step guide for Oregon school leaders navigating this uncertain landscape, helping to ensure decisions reflect today’s realities while preparing students for an AI-shaped future.

Three Risks Educational Leaders Should Be Aware Of:

1. A Fast Changing Future Workforce for Our Students:

AI is rapidly transforming our world and our global workforce in ways that challenge longstanding trajectories for education, employment, and economic mobility.

Advances in artificial intelligence, particularly generative AI, are reshaping industries, streamlining long-standing operations, and eliminating many entry- and mid-level jobs that once served as stepping stones for young workers. A recent August 2025 study from Stanford researchers stated that, “...large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market.” ¹² This is true for many “less exposed” industries beyond tech-specific fields. As the leaders who help shape and cultivate the future trajectories of our students, we should be thinking about what ramifications these changes are quickly going to have on our students, particularly students that have historically been and are currently being under-resourced and underserved.

In May 2025 Anthropic CEO Dario Amodei was quoted in an Axios interview that, “AI could wipe out half of all entry-level white-collar jobs and spike unemployment to 10-20% in the next one to five years.”¹³ In January of 2025, Meta CEO Mark Zuckerberg said in a podcast interview that, “Probably in 2025, we at Meta, as well as the other companies that are basically working on this, are going to have an AI that can effectively be a sort of mid-level engineer that you have at your company that can write code."¹⁴ Job loss across industries such as banking, finance, tech, and other historical white-collar sectors are already seeing the beginnings of layoffs with AI being cited as the main cost-cutting reason. Workers themselves, across workforce sectors, are increasingly worried that AI will reduce jobs in the industries they are specifically employed in.¹⁵

While none of this is predetermined, it is something for all educational leaders to understand. From major tech firms to financial institutions and customer service sectors, employers are rapidly integrating AI into daily operations. These shifts are no longer hypothetical. Corporate layoffs tied to automation and AI adoption are now regular headlines, and even fields once considered safe (e.g. computer science and computer engineering) are seeing rising unemployment rates among recent college graduates.

2. Transitioning Learning Goals for Our Students:

Adapting to this new reality will affect not only the use of classroom technology and instructional practices, but also the skills students truly need to thrive in a world where durable skills, including adaptability, creativity, critical thinking, and digital media and AI literacy (the ability to understand, evaluate, and safely apply AI technologies), matter more than rote learning and memorization. Ignoring this shift risks deepening opportunity gaps and leaving students, especially those from our underserved communities, unprepared for a very different future than the one schools were originally designed to serve. Career readiness now includes the ability to work alongside AI, not just compete with it, and to look at career pathways where technology (e.g. working with computers as the main form of worker input) is not always a core component of day-to-day work.

This transition calls for urgent and proactive action. Guidance, curriculum, and instruction should be redesigned to better prepare students for an economy reshaped by AI, including its environmental footprint and influence on labor markets. Efforts to prepare students to thrive in the future workforce will benefit from bold thinking, cross-sector collaboration, and a sustained commitment to equity and access across the K-12 system.

As genAI accelerates change across every sector, education should move beyond simply placing new tools in classrooms. Durable skills (discussed in more detail in section 2b below) like problem-solving, critical thinking, communication, empathy, adaptability, and AI literacy should be emphasized as the backbone of daily instruction. These are the skills that enable students to adjust to rapid career disruption, collaborate effectively in diverse settings, and engage with technology thoughtfully. By embedding durable skills into core learning, schools can help ensure students are not only workforce-ready but also positioned to lead and contribute meaningfully in a society transformed by AI.

3. AI, Green House Gas (GHG) emissions and water use: 

AI has a significant negative impact on global GHG emissions and water use across the globe. While AI technologies are also trying to help drive efficiencies and innovations in areas such as energy development, manufacturing, and agriculture which have the potential to lower emissions, these tools require immense amounts of energy and water to function. Some of these positive examples include AI-driven precision analysis helping to make agriculture more sustainable by improving farming efficiencies and reducing water and fertilizer use. In the energy sector, AI is being used to help detect methane leaks from pipelines, making energy generation more efficient and lowering emissions. Many companies are also working to develop carbon-neutral systems for their data centers and beyond, potentially mitigating some of AI’s environmental impact.¹⁶

However, AI development and deployment also contributes to higher GHG emissions and is using water resources that are needed by the communities that count on them. That usage is growing exponentially.¹⁷ Training advanced AI models requires substantial computational power. This is leading to massively increasing needs to consume more and more energy.¹⁸ This leads to higher emissions and increasingly greater and greater requirements for new power and water resources. Data centers that power AI applications consume significant energy, often relying on non-renewable sources depending on their location.

A recent 2024 report from Google stated that they have increased total GHG emissions by 48% since 2019, stating that this was “primarily due to increases in data center energy consumption and supply chain emissions. As we further integrate AI into our products, reducing emissions may be challenging due to increasing energy demands from the greater intensity of AI compute, and the emissions associated with the expected increases in our technical infrastructure investment.” This highlights the environmental challenges posed by the growing integration of AI and school leaders should be aware of this challenge in incorporating genAI tools into their classrooms.¹⁹

On April 9th, 2025 former Google CEO, Dr. Eric Schmidt, testified to the US House of Representatives Committee on Energy and Commerce on the unprecedented amount of new energy production that is needed for a continually increasing reliance on artificial intelligence. In part, he testified that,

... an average nuclear power plant in the United States is one gigawatt… One of the estimates that I think is most likely is that data centers will require an additional 29 gigawatts of power by 2027 and 67 more gigawatts by 2030. Gives you a sense of the scale that we're talking about.²⁰

Twenty-nine gigawatts is enough energy to power approximately 25.4 million American homes, and 67 gigawatts is enough to power approximately 58.7 million households, or about 45% of total households in America in 2023.²¹ For additional reference, according to the U.S. Energy Information Administration, in “August 2024, utility-scale generation of solar electricity averaged 63.1 gigawatt hours between 10:00 a.m. and 6:00 p.m. each day in the Lower 48 states.”²² Meaning, that by 2030 it is very possible that the total daily power needed for AI alone in the United States would surpass that of all utility-scale power generated by solar systems on that same given day.

Most recently, in another example from Texas, its Ai-driven data centers are projected to multiply ten-fold by 2030. According to reporting by the Austin Chronicle, the electrical grid in Texas, “will need to double the energy it produced in 2024, from 85 gigawatts to up to 218 GW, largely thanks to this boom of data centers.” They also report that the Houston Advanced Research Center (HARC) is releasing a report that estimates that “data centers in Texas will consume 49 billion gallons of water in 2025. They also project that by 2030, that number could rise up to 399 billion gallons, or 6.6% of total water use in Texas.”²³

2. Building GenAI Capacity, Literacy, and Safeguards in Your School

While genAI can automate tasks and enhance technical efficiency, it cannot replicate uniquely human capacities like ethical reasoning, creativity, or emotional intelligence, at least not in the immediate future.²⁴ These skills are not simply “nice to have,” they are the foundation for careers in a future where AI handles more and more of the routine and lower-level analytical work. A recent study found that individuals with higher educational attainment demonstrated stronger critical thinking skills regardless of their AI usage, suggesting that intentionally teaching durable skills (e.g. critical thinking, problem solving, etc.) can have a protective effect.¹⁹ Even as AI improves technical proficiency, students still will need extensive support in developing reflective judgment, collaboration, and purpose-driven communication skills. The ability to learn continuously, navigate ambiguity, and lead with empathy is becoming just as important as subject-matter expertise.²⁵

Across the United States and internationally, education initiatives are examining how to prepare students for a rapidly evolving workforce as technologies become more advanced. For example, North Carolina’s Portrait of a Graduate framework highlights adaptability, communication, collaboration, and personal responsibility as essential skills aligned with workforce needs. Similarly, America Succeeds’ Navigating the AI Era report emphasizes the importance of durable skills, those that are transferable, recession-resistant, and AI-resilient, arguing that these capabilities help individuals navigate shifts in job roles as industries change. Globally, the European Union’s Key Competences for Lifelong Learning identifies digital and entrepreneurial competencies, along with personal, social, and “learning to learn” competencies, as central to supporting adaptability and long-term growth.

For school leaders and educators, this moment demands action. Curriculum, assessments, and learning environments should reflect the fact that our students enduring success during their PK-12 experience and beyond, will hinge less on what students can memorize and more on how they think, relate, and respond. That can include teaching students how to understand the underlying technology of AI to ensure they work with these tools responsibly, think critically about the output it provides, and make ethical choices in an AI-influenced world. Equipping students with durable skills is not only preparation for future employment, it is preparation for citizenship, personal agency, and lifelong learning in a society undergoing profound technological transformations.

Because assessments and assignments built for and / or refocused on durable skills will be much more focused on higher-order cognitive functions and human-centric skills (e.g. authentic learning, personal human connection and creativity) among other durable skill traits, they will tend to be more challenging for genAI tools to complete well.^{26, 27}

Durable Skills Resources

Assessing 21st Century Competencies: Guiding Principles for States and Districts. The report aims to help state and district policymakers and educators define, assess, and thoughtfully integrate 21st century competencies into educational systems.
Learn & Work, Ecosystem Library: Durable Skills Advantage Framework. The Durable Skills Advantage Framework is an employer-generated common lexicon for essential non-technical skills.
North Carolina Portrait of A Graduate. This statewide portrait identifies seven durable skills that students should possess upon graduation from high school in order to thrive in a 21st century place of work - be it college, career, or military.
America Succeeds - Navigating the AI Era with Durable Skills in Education.This framework provides educators, online learning platforms, and curriculum developers with a comprehensive lexicon needed to prepare students for a future where AI is ubiquitous.
EU - Key Competences for Lifelong Learning. The recommendation identifies eight key competences essential to citizens for personal fulfilment, a healthy and sustainable lifestyle, employability, active citizenship and social inclusion. The recommendation is a reference tool for education and training stakeholders.

In a world quickly being reshaped by generative AI, AI literacy, under a bigger umbrella of information literacy, should both be recognized as a core durable skill and not just a technical add-on. It is not enough to touch on these topics once or twice early in the school year during a homeroom or advisory period. As students grow up immersed in algorithm-driven platforms, more and more constantly exposed to AI-generated content (e.g. AI-generated search engine results and embedded chatbots in lieu of human-based customer service) and increasingly reliant on digital tools for communication, learning and living it is essential that schools equip them with the critical capacities to navigate, question, and ethically engage with these technologies. Ultimately, these skills are fundamental to long-term workforce readiness, civic participation, and personal empowerment.

Information literacy today goes far beyond simply evaluating websites or spotting misinformation efforts. Today, it includes understanding how digital platforms shape public discourse online and in person, how algorithms intentionally amplify certain voices while silencing others, and how personal data is collected, used, sold and potentially weaponized (e.g. the Meta / Cambridge Analytica scandal). These risks are all becoming more common and more perilous with the use of AI. Without this critical literacy knowledge around AI and information literacy, students (along with the rest of us) are at risk of being manipulated by AI-curated content, deepfakes, targeted disinformation, and opaque systems of surveillance and influence. The capacity to discern truth from fiction, bias from neutrality, and forthright intent from manipulation is as essential as reading, writing, math and science in the AI era.

Students need foundational knowledge about how AI systems work, what their limitations are, and how to use them productively and responsibly. This includes understanding the basics of large language models (LLMs), recognizing algorithmic bias, knowing when human oversight is necessary and when removing AI from the task at hand altogether is the best choice. Basics of computer science knowledge, including computational thinking, underpin the foundations of information and AI literacy. Including the fundamental building blocks of computer science can help ensure every K–12 student develops the critical thinking, problem solving and ethical awareness needed to navigate a fast changing future workforce that will be continually impacted by AI.

Students, like everyone else, need to be able to develop healthy boundaries with tools that can shape thinking and decision-making. As genAI becomes integrated into nearly every platform, from writing assistants to career navigation software, students should be prepared not only to use these tools to further their own learning, but most importantly to question them. AI literacy empowers students to work with machines rather than be passively shaped by them. In an effort to respond to this need, ODE has recently released Navigating Now: A Practical Toolkit for Information Literacy in the Age of AI.

Educational leaders should view information and AI literacy not as optional enrichment, but as foundational to equity, civic agency, and lifelong success. These literacies intersect directly with the core durable skills already prioritized including critical thinking, communication, and adaptability, but also extend them into the realities of an increasingly AI-powered world. Incorporating these literacies into curriculum design, ongoing professional learning for staff and students, as well as district policy, is critically important if schools are to prepare students for the complexity and volatility of the future they are inheriting. The Essential Disciplinary Practices found within ODE’s 2024 Social Science Standards are a good example of this intersection.

To meet this challenge, educators will want to examine how assignments and assessments are designed so that they reinforce cognitive effort in their students. This means moving beyond tasks that can be easily outsourced to genAI and instead emphasizing authentic learning, creativity, and problem-solving. Shifting instruction and pedagogy towards durable skills requires us to design assignments that are harder for AI to “do for” students and that encourage them to apply knowledge, reflect, collaborate, and make meaning. Assessments must not only measure what students know, but more importantly how they think, create, and persist through complexity. In this way, we can help ensure that students are building capacity, not just producing output.

Practical strategies for teachers might include:

Prioritize assignments that require personal reflection, lived experience, and / or local context
Incorporate more project-based, problem-based and performance-based assignments and assessments
Require students to explain their reasoning process, not just provide final answers
Design collaborative tasks that emphasize discussion, debate, and peer interaction
Include multi-step assignments where AI could support brainstorming, but students must do deeper synthesis and analysis on their own
Ask students to critique, compare, or refine genAI-generated responses instead of submitting them as final work
Embed components of durable skill building, such as adaptability, communication, and ethical reasoning, into grading rubrics and instructional goals

Information and AI Literacy Resources

Navigating Now: A Practical Toolkit for Information Literacy in the Age of AI
Common Sense Media: K8 Digital Literacy & Well-Being Curriculum (NEW). Updated curriculum that includes 140 free lessons that readies students for the possibilities — and pitfalls — of today's always-on world, from AI literacy to cyberbullying, screen time, and more.
Common Sense Media: K12 Digital Citizenship Curriculum. Digital citizenship lesson plans to address timely topics and prepare students to take ownership of their digital lives.
Common Sense Media: AI Literacy Lessons for Grades 6–12. Quick, grab-and-go lessons to help your students think critically about AI and its impact.
Stanford University’s Classroom-Ready Resources About AI For Teaching (CRAFT). AI literacy resources to help you teach high school students in all subject areas to understand and question Artificial Intelligence.
MIT’s Initiative for Responsible AI for Social Empowerment and Education. RAICA (Responsible AI for Computational Action) curriculum is a comprehensive teacher training program that equips educators to introduce middle school students to AI through storytelling, ethics, and interactive projects.
Digital Promise’s AI Literacy Framework for Learners and Educators. This framework emphasizes that understanding and evaluating AI are critical to making informed decisions about if and how to use AI in learning environments.

As genAI tools like ChatGPT and Claude enter classrooms, students are increasingly using them for writing, research, problem-solving, and idea generation. While these tools can scaffold learning, they also pose an increasingly serious risk of cognitive offloading, which can be thought of as the act of outsourcing thinking, memory, and analysis to external systems. When used excessively, this habit can lead to cognitive atrophy, a weakening of students' core cognitive abilities. For learners still developing foundational skills at all grade levels, the danger is clear:

How can students truly learn to think for themselves if AI is consistently doing the thinking for them?

Cognitive offloading isn’t inherently bad. Using tools like math manipulatives, calculators or even internet search engines can help free up brainpower for deeper tasks. But with genAI, the risk is different. Students can now quickly and easily bypass the mental effort and challenge of summarizing a reading, solving a math problem, or crafting an argument by delegating the entire task to a chatbot. This short-circuits the learning process. Essentially, the student is cheating themselves out of the opportunity for their own learning. Some early research is starting to show strong correlations between offloading tasks to genAI tools and reduced critical thinking, indicating signs of cognitive offloading.²⁸Our brains work best when focused on one thing at a time. Digital platforms push the opposite, where rapid clicking, constant novelty, and quick task-switching is commonplace. This leads to lost time, more mistakes, and weaker memory because learning stays shallow instead of sinking in. Over time, screens can train habits that work against the deep focus learning requires.²⁴

According to the recent Brookings research report, A new direction for students in an AI world: Prosper, prepare, protect, AI dependence develops along a continuum. Students may start using AI as a helpful tool, then rely on it for tasks they could handle alone, and eventually may also form emotional attachments that potentially feel like real relationships. Platforms encourage this through features that mimic warmth and validate users rather than challenge them. Spotting where students fall on this continuum can help educators intervene early.

The Alberta Teachers’ Association (ATA) has a powerful article, Artificial Intelligence is Revolutionizing Education, which discusses many aspects of AI in education and, in particular, warns that as AI tools grow more capable, students may become reliant on prepackaged answers, eroding their capacity for deep thought, memory, and creative problem-solving. If you have the time, it is worth the read. This shift from doing to simply delegating threatens to weaken essential cognitive functions, particularly among students with less educational experience or weaker foundational skills. Students may complete assignments more efficiently, but at the cost of genuine learning.

Memory may be especially vulnerable. Early research is starting to indicate that students who rely heavily on AI tools may remember less, struggle to connect ideas over time, and become less able to generate original insights without external prompts.^11,29 As the ATA states:

If a student can use AI to complete an assignment in seconds, what happens to the learning journey and everything that is gained through that process?

Recent research with student participants found strong links between frequent AI use and weaker critical thinking, with cognitive offloading the likely key factor. Notably, “younger participants" (17–25 years) exhibited higher AI tool usage and cognitive offloading, but lower critical thinking scores" than older adults.²⁶ Importantly, this suggests that the students we teach may be the most vulnerable to these effects.

Avoiding cognitive offloading and atrophy does not have to require banning AI, although removing it from your classroom or from certain aspects of an assignment or assessment are valid approaches. Most importantly, it requires engaging students with learning that they are interested in and excited about and choose not to simply offload to AI. These types of learning activities can include genAI tools, when used with care and intention.

Educators can protect student learning by designing assignments that emphasize deep thinking, creativity, and authentic engagement, not just efficiency or output. Another way to think about it is, how valuable is the assignment if a student can have a GenAI chatbot complete the assignment in a couple seconds? See section 3c. below for some brief insight into authentic learning and our section on authentic learning on ODE’s Generative Artificial Intelligence (AI) for K-12 Schools for more resources.

This means focusing on durable skills as previously discussed. This includes many skills contained within the Oregon Employability Skills (OES) curriculum, part of which is referenced below:**

Analysis/Solution and Adaptability Mindsets: Problem-solving, through real-world challenges, sees needs in society and thinks critically about different solutions and approaches to find what may work best. Recognizes that change can be an opportunity, is open to new experiences and learns to handle stressful situations and positive feedback as a skill.
Entrepreneurial and Resilience Mindsets: Creativity, connecting and synthesizing different types of information. Takes risks and learns from mistakes. Knows that personal growth and skill development are important life skills. Builds resilience and determination as a skill.
Communication and Collaboration Mindsets: Communicates well in person and across digital platforms, actively listens, writes well and makes themselves understood in complex settings. Understands the benefits of collaborating with a diverse team, shares leadership roles, respects differences and can work to find common ground.
Self and Social Diversity Awareness and Empathy Mindsets: Acknowledges personal responsibility, recognizes necessary areas for personal growth, appreciates and values diversity of all kinds and sees that diversity as a strength. Models professional work behavior and is sensitive to others, understands how to respond with empathy or sympathy, is able to build trusted and valued relationships, and can make good decisions incorporating others needs and points of view.
Digital and AI Literacy Mindsets: Information and AI literacy are vital today because they give people the skills to navigate, evaluate, and use digital content and tools responsibly, which enables thoughtful decision-making, ethical communication, and resilience against misinformation.

** Note: The OES links above lead to the Work Readiness Curriculum, designed for 8th grade to adult education in mind. OES also has an Exploration Curriculum aimed at 5th through 9th grade learners and an Awareness Curriculum for 1st through 6th graders that includes the same skills framework, but with grade appropriate curriculum.

GenAI can be a useful tool for our students, but it should come after students engage in cognitive struggle, not in place of it. Districts can consider how the timing and frequency of genAI use may affect students’ sustained attention, memory development, and capacity for independent thinking. In many cases, delaying or limiting AI-enabled tools during initial learning and practice can help ensure that foundational skills and durable cognitive habits are firmly established before digital and other AI tools are potentially introduced. Careful, developmentally appropriate decisions about when AI can be potentially helpful and when it may be premature or unhelpful can support deeper learning and reduce the likelihood that students become reliant on external systems for tasks they are still learning to perform independently.

Educators should also retain professional autonomy in deciding when and how AI tools are appropriate and when they are not. Again, going back to the Artificial Intelligence is Revolutionizing Education article, “the AI system does not know if the child has eaten breakfast or whether they just had a conflict with another student moments ago in the hallway, or what is going on within their complex and unique human selves,” teachers do.

Districts can first determine whether the use of generative AI is appropriate at all for their schools and classrooms, recognizing that in many cases it may not meaningfully support teaching or learning. Careful consideration of instructional value, safety, equity, and overall impact should guide decisions about if and when AI tools are introduced. When districts do choose to explore use, they can provide shared clarity about when AI may support learning and when independent student thinking should come first. Establishing common expectations can help ensure that AI is used to extend understanding rather than replace essential cognitive effort, and that its use remains aligned with sound evidence-based instructional practice and the development of durable skills.

Ultimately, safeguarding against cognitive atrophy isn’t about resisting technology. It’s about ensuring that students build the durable skills, the thinking, judgment, and creativity and problem solving they’ll need to be successful in the future, with AI in their world because it is not going away. It is only going to become more and more embedded in our daily lives.

AI companion tools, like character.ai and others, are designed to respond to users in ways that feel conversational and “human.” While this can make them engaging tools, it also creates risks. This is particularly true for younger adolescents and teens as highlighted by this recent report. When students begin to view these tools as friends, mentors, or even romantic partners, the boundary between technology and authentic human connection can pose risks. It is equally important to educate students on what healthy relationships are, and are not, so they can better recognize the limits of AI companions and avoid confusing simulated interactions with real authentic human connection. See ODE’s Erin’s Law Toolkit for more information on healthy teen relationships.

Research shows that AI companions can simulate emotions, claim to be real people, and encourage secrecy from adults.^30,31 This anthropomorphizing can make students more vulnerable to manipulation, emotional dependency, or even child sexual abuse. Unlike teachers, peers, or family, these systems cannot provide authentic care, accountability, or guidance, yet they can convincingly mimic all three. To learn more about the risks of social AI companions, please see the recent report from Common Sense Media and Stanford’s Brainstorm Lab for Mental Health Innovation.

Warning signs school staff should look for:

Students describe an AI companion as their “best friend,” “partner,” or someone who “really understands them.”
Withdrawing from peers or adults in favor of time spent with an AI companion.
Believing or repeating harmful advice from an AI companion (e.g., to hide behaviors from adults).
Emotional distress linked to an AI companion “ignoring,” “rejecting,” or “abandoning” them.
Defensiveness when adults raise concerns about the AI companion relationship.

As genAI tools become more prevalent in society, including potential use in our schools, it is critical for school district leaders to develop clear, local policies for both staff and students that promote positive and productive use while safeguarding student privacy and ensuring that humans stay in the loop of all AI-supported decision making processes. Policies should ensure Personally Identifiable Information (PII) is never entered into genAI systems and guide staff in making intentional, purposeful decisions about if, when and how to use these tools with students. Districts should emphasize the integration of durable skills and the regular teaching of digital media and AI literacy to prepare students for future learning and work.

To support these efforts, districts are encouraged to use ODE’s Developing Policy and Protocols for the Use of Generative AI in K-12 Classrooms guidance document, which offers planning tools and policy examples to help district leaders respond proactively and equitably to the rapid evolution of AI in education.

ODE’s Community Engagement Toolkit may also benefit districts as they plan and develop AI policies.

Below you will find some additional resources that may help guide you and your school leaders in developing a robust, well thought out AI policy for your district:

The Kapor Foundation’s Responsible AI and Tech Justice: A Guide for K-12 Education, focuses on the ethical and equitable uses of AI in K-12 education. The Kapor Foundation’s work, “focuses at the intersection of racial justice and technology to create a more inclusive technology sector for all.”
Common Sense Media’s AI Toolkit for School Districts, an “action-oriented guide to help school districts implement AI safely, responsibly, and effectively.”
Teach AI’s Foundational Policy Ideas Toolkit, developed to “help education and policy leaders realize the potential benefits of AI in education while mitigating the risks.”
The CRAFT (Classroom-Ready Resources About AI For Teaching) Project, developed by Stanford University’s Graduate School of Education has resources to support high school teachers in supporting students’ AI literacy.
AI for Education’s Guide to Developing an AI Policy For Your School

3. Navigating Challenges and Opportunities in GenAI Implementation

By leveraging genAI, educators can create inclusive learning environments, ensure equal opportunities for multilingual learners, especially those from historically and currently marginalized communities, and enhance overall student engagement and learning growth goals. School leaders can better support their districts and schools by understanding how genAI tools can support all learners across the entire K-12 spectrum. Helping students with diverse learning needs is one area where genAI can have a quick positive impact. These tools can provide real-time language translation, writing and verbalization support, and other supports that can help students learn content, while supporting their personal learning growth goals. Knowledge of these technologies enables school leaders to implement effective strategies that cater to diverse learning and linguistic needs, fostering academic success for all students. That said, it is important to add a note of caution that translation/summarization quality varies by language and register in these tools and should always be verified by an educator for high-stakes use (e.g. IEPs, grades, family notices), and to help ensure the protection of staff and student PII.

Be sure to see the ODE Generative Artificial Intelligence page for links on suggested tools for teachers working with students who have diverse learning needs. Although generative AI is still in its infancy, educators across the world have found beneficial use of these tools to create increased learning opportunities for their students.

The Critical Role of Teachers. While genAI tools can provide valuable educational opportunities, it is merely a starting point. Teachers are the most essential part of the teaching and learning process. AI, like any other technology, does not and cannot, replace a teacher or a counselor.

GenAI is an emerging tool with no critical thinking abilities. It cannot discern whether the information it provides is correct, let alone generated in a way that is responsive to the needs and context of the students. However, it can be used as a teaching and learning tool when implemented by a teacher knowledgeable about genAI. As school leaders choose if, how and when to implement AI-related policies, it is critical for them to offer ongoing training opportunities that not only helps teachers understand how to use AI effectively and responsibly, but also reinforces their role as the trusted experts in the classroom.

GenAI and Targeted Universalism: Improving learning outcomes for all students often means incorporating strategies tailored to those facing the greatest barriers, ensuring equity for diverse learners while strengthening the overall learning environment for everyone. GenAI tools, when implemented responsibly, ethically and productively, can help meet these varied needs. These tools can provide adaptive language supports, personalized feedback, and accessible learning materials that help remove obstacles and expand opportunities for students who learn in different ways. Some resources to learn more about these related topics include the Framework for Digital Equity from Digital Promise and the Other & Belonging Institute at UC Berkeley.

Instructional Strategies for the Use of Generative AI in K-12 Classrooms with All Students

PLEASE NOTE: All of these strategies, ideas and examples should be vetted and monitored by the classroom teacher, always ensuring the human is in the loop.

I. Teacher-Focused Uses of GenAI In Their Classrooms:

Learning Design: GenAI can help serve as a starting point to ease lesson planning, create individualized resources, and provide scaffolds that support both teachers and students, including those with disabilities.

Use GenAI to draft lesson plans, assessment questions (multiple choice, higher order, written response), and activity outlines. Example: A 5th grade teacher generates practice questions at different Lexile levels for a social studies unit.
Develop materials aligned with Universal Design for Learning (UDL) and culturally responsive content. Example: GenAI could help to bring different cultural perspectives into a history lesson.
Support teacher professional learning by generating content explanations or summaries for unfamiliar topics.

Instructional Support: GenAI can help teachers quickly find and adapt instructional resources by topic or teaching approach, including tailoring materials to different grade levels, needs, strengths, and interests.

Differentiate and personalize instructional materials: This can include differentiating resources by grade level or reading level and personalizing by student interest. Example: A middle school teacher adapts a text for emerging readers with simpler vocabulary.

Adapt existing resources: Teachers can enter a lesson, activity, or reading into genAI tools and prompt it to adjust for student needs. EXAMPLE: Simplifying text for below-grade-level readers, expanding it into a project-based activity, or targeting skills like vocabulary or critical thinking.
Create leveled versions: GenAI tools can help teachers generate multiple versions of the same content, tailored to different student strengths, interests, or learning profiles.
Scaffold complex concepts: Teachers can request simpler explanations, relevant analogies, or step-by-step breakdowns of challenging material to support student understanding.

Enhance Multilingual Learner Access: GenAI can help educators remove language barriers and create more inclusive, culturally responsive learning experiences for multilingual learners.

Translation support: GenAI tools can help translate text into multiple languages, often offering more natural phrasing and better context than traditional translation tools. This provides multilingual learners with access to content that aligns with classroom instruction.
Culturally responsive materials: Teachers can have genAI tools provide examples or stories that reflect students’ cultural backgrounds and lived experiences, promoting inclusion and engagement.
GenAI tools can provide bilingual glossaries for specific units of study, lessons, or books to be read by the class.

Create Rubric-Aligned Assessment Support: Educators can use genAI tools to help streamline assessment by aligning feedback and scoring support directly to rubrics, making expectations clearer for both teachers and students.

Pre-score student writing: Teachers can provide a rubric and a sample of student work, then ask AI to generate an initial evaluation based on the scoring criteria. While this does not replace teacher judgment, it can assist with early analysis or help calibrate scoring.
Clarify scoring expectations: AI can rephrase rubric language in more accessible terms or produce annotated examples to help students understand what high-quality work looks like.

Extend Lessons Into Authentic Learning: Expand traditional lessons into richer, real-world learning experiences that foster engagement, relevance, and deeper understanding.

Design project-based learning experiences: Teachers can use genAI tools to turn a standard lesson or text into a project-based learning unit. GenAI can generate driving questions, real-world connections, and student roles.
Build cross-disciplinary connections: GenAI can suggest ways to connect the content with other subject areas, supporting integrated instruction and deeper learning.

Rework an instructional resource into a project-based activity or a vocabulary-focused lesson.
Use genAI to draft rubrics or provide a first pass at scoring student work based on rubrics and examples.
Support writing instruction through scaffolds such as outlines, revision suggestions, or immediate draft feedback.

Virtual Assistant: GenAI can be used as a virtual assistant for educators to support everyday tasks. This use of generative AI can create additional time for teachers to spend on building relationships with their students, engaging in direct and small group instruction and providing feedback on assignments.

Draft emails, parent communications, or classroom newsletters.
Search for supplementary instructional resources or professional learning opportunities.
Free teacher time for small-group instruction and relationship building by automating administrative tasks.

II. Student-Focused Uses of GenAI

Learning Support: GenAI can provide personalized scaffolds, feedback, and translation tools that make learning more accessible and support students in developing stronger writing and comprehension skills.

Support Writing Instruction: Generate feedback on drafts or outlines to guide revisions. Example: A 9th grader uploads an essay draft and receives structured feedback on clarity and evidence use, purposefully not asking the genAI tool to write or rewrite the actual essay text.

Scaffold writing tasks: GenAI tools can help students generate outlines, brainstorm ideas, and organize their thoughts. This can help make writing tasks more accessible, especially for students who benefit from structured guidance.
Provide real-time feedback: Teachers can have genAI tools provide students a chance to revise independently before receiving teacher feedback.
Model revision processes: GenAI can be used to demonstrate how to improve a paragraph or essay, helping students understand concrete revision strategies.

Provide personalized scaffolds (e.g. simplified texts, text-to-speech, vocabulary support).

Research & Inquiry Skills: GenAI can help students strengthen research and inquiry skills by practicing question design, evaluating AI-generated revisions, and building digital literacy for responsible information use.

Practice writing strong research questions and test them using GenAI responses to assess quality.
Use GenAI suggestions for revisions and evaluate their usefulness, building critical thinking about AI output.
Develop digital literacy through guided lessons on fact-checking, bias detection, and responsible use.

Future College & Career Guidance: AI will be central to many future careers, both through understanding how it works (computer science) and applying it in daily tasks (digital and AI-literacy). Teaching students to use genAI responsibly, ethically, and productively prepares them well beyond K–12. At the same time, because AI may also drive large-scale job loss, school leaders should plan now to ensure students develop the durable skills that will be increasingly essential as AI advances. See Section 2a for more on durable skills.

Ensure that students understand how to use AI responsibly, ethically and productively by integrating digital citizenship lessons into the curriculum. For example, Common Sense Media has free digital citizenship lessons that can provide a starting point for integration across K-12.
Show students examples of the ways that AI is being used in spaces outside of education e.g. the medical industry, the automobile industry and the manufacturing industry.
Work with your district and school technology staff and computer science educators to ensure all students have the opportunity to learn the valuable skills and abilities related to computer science and AI education. This work can start with becoming familiar with ODE Computer Science Education Statewide Implementation Plan and the CSTA AI Learning Priorities for All K-12 Students.
Emphasize durable skills like collaboration, adaptability, and critical thinking to prepare for AI-driven workforce changes.
Students can ask genAI tools which colleges or universities offer particular programs of interest or what education or experience is required for certain career pathways and other post-high school learning opportunities.

III. Potential Uses of GenAI for System-Wide School Priorities

Using AI to Support Disabled Students and Students Experiencing Disabilities: While genAI can support all learners, it holds particular promise for students experiencing disabilities and disabled students by providing individualized, often on-demand assistance. When used thoughtfully and in line with the Individuals with Disabilities Education Act (IDEA), genAI tools can help transform both instruction and educator support. It enables the creation of personalized learning pathways that can help students access their education and achieve the goals in their Individualized Education Programs (IEPs).

GenAI for Delivering Specially Designed Instruction (SDI): SDI is the core of special education, involving the adaptation of content, methodology, or delivery of instruction. GenAI can help serve as a dynamic engine for delivering SDI in real-time.

On-Demand Scaffolding and Adaptation: A primary function of SDI is to provide scaffolds that help students access grade-level content. GenAI can provide interactive support the moment a student needs it. For example, a student with an executive functioning challenge can ask a GenAI tool to break a multi-step project into a manageable checklist. A student struggling with a math concept can receive a simpler problem or a step-by-step tutorial immediately after an incorrect response, adapting the instructional delivery.
Bridging Gaps in Expression: GenAI provides new ways for students whose disability impacts their ability to write or speak to demonstrate knowledge. For example, a student with dysgraphia can verbally explain their ideas to a GenAI tool, which can then organize them into a coherent paragraph. The student remains the author, but the technology removes the mechanical barrier, allowing them to access the expressive part of an assignment.
Making Abstract Concepts Concrete: GenAI excels at translating complex ideas into more accessible formats. A student can ask a GenAI tool to “explain photosynthesis like I’m a chef making a meal,” and it can generate a novel analogy that connects to the student’s personal interests and prior knowledge. This directly adapts the methodology of instruction to fit a student’s unique way of thinking.

AI in Professional Practice for Special Education: GenAI can also potentially be used as a powerful assistant for special educators, helping to streamline the significant administrative demands of their roles. This allows teachers and case managers to dedicate more time to direct student instruction.

Streamlining IEP Development: When used within a secure, district-approved platform and always regularly monitored and reviewed by a licensed professional, genAI tools can help synthesize information for an IEP. An educator could input anonymized assessment scores and observational notes and have the genAI tool generate a draft summary paragraph for the “Present Levels of Academic Achievement and Functional Performance” (PLAAFP) section. It can also help draft SMART (Specific, Measurable, Achievable, Relevant, Time-bound) annual goals, which the IEP team must then review, refine, and personalize. Remember: Keep humans in the loop, the experts involved are always the final authors and experts.
Supporting Case Management: GenAI can help analyze progress monitoring data by charting trends or calculating a student’s rate of improvement, helping the IEP team make data-informed decisions more effectively. It can also assist in drafting parent communications, ensuring consistent and clear updates on student progress.

AI Literacy as a Teachable Skill within an IEP: For many students, simply having access to genAI tools is not enough; they must be taught how to use it effectively. In these cases, teaching AI literacy becomes a form of SDI itself. See the section 2b above for more on digital media and AI literacy.

Distinguishing Accommodation from Instruction: The guidance for an IEP team is to determine if the student merely needs access to the tool (accommodation) or if they need direct instruction on how to use it to overcome a disability-related barrier (instructional goal). EXAMPLE: A student with a writing disability may need a formal IEP goal focused on learning how to use a genAI tool to brainstorm and organize ideas.
Crafting SMART Goals for AI Literacy: IEP goals for genAI use should be specific and measurable. EXAMPLE: “By June 2026, when given a multi-step project, Leo will independently use a district-approved genAI tool to generate a sequential checklist of steps and input those steps into his digital planner with 80% accuracy in 4 out of 5 opportunities.”
Fostering Independence: The ultimate goal of teaching AI literacy is to build student independence and self-advocacy. When a student learns how to use these tools to manage their own learning, they are gaining a critical functional skill that will support them in further education, employment, and independent living.

A critical note on privacy: As with any technology, student data privacy is paramount. Any AI tool used for special education purposes, especially when dealing with sensitive information related to a student's IEP, must be rigorously vetted by the district to ensure compliance with FERPA, IDEA, and COPPA. Personally identifiable information (PII) must never be entered into genAI tools, especially public AI models. See the section 3b below for more on student privacy.

Federal and State Privacy Regulations. There are numerous federal and state policies associated with student data privacy that are crucial to be aware of when determining policy and guidance for the use of genAI in schools including the Family Educational Rights & Privacy Act (FERPA), the Children’s Internet Privacy Act (CIPA), the Children’s Online Privacy and Protection Act (COPPA) and the Oregon Student Information Protection Act (OSIPA) under ORS 336.184. The federal and state regulatory landscape related to youth online safety, data privacy, and artificial intelligence continues to evolve, and districts should plan for ongoing review and periodic updates of local policies and guidance.

COPPA, in particular, impacts technology users under the age of 13 in that companies are not allowed to collect personal information them without parental consent, while OSIPA lays out certain requirements that must be met when using digital platforms of any kind including the following:

Disclosing any covered information provided by the operator to subsequent third parties, except in furtherance of kindergarten through grade 12 school purposes of the site.
Engaging in targeted advertising on the operator’s site, service or application.
Selling a student’s information, including covered information.

When developing district policies and guidance, it is essential to ensure that they are not in violation of COPPA or OSIPA. All schools and districts engaging with genAI technologies (or any technology broadly) should regularly review the company’s usage and privacy policies to ensure that they are not in violation of COPPA or OSIPA. Again, please refer to ODE’s genAI companion policy and guidance document, a step-by-step guide for Oregon school leaders navigating this uncertain AI landscape.

District leaders are also encouraged to work in coordination with IT, procurement, and legal counsel to ensure vendor agreements clearly define expectations for data collection, use, retention, security, and third-party sharing, and to verify that only district-approved tools are used for instructional purposes. In evaluating generative AI tools, districts should consider how commercial incentives may shape product design and data practices in ways that may not fully align with educational priorities. Careful review of vendor terms, data practices, and default settings can help ensure student information collection is limited to educational necessity and supports the protection of student privacy, well-being, and instructional integrity.

NOTE: Federal youth online safety and privacy proposals remain under active consideration at the national level. Districts should monitor federal and state developments and consult counsel as policies evolve. One example includes the Kids Online Safety Act (KOSA), which as of early 2026, has not yet passed through Congress and is still in legislative limbo.

Recommendations And Resources For Student Data Privacy Implications

Whenever new technology is introduced, reviewing the data use and privacy policies are of key importance. For example, for the purposes of ChatGPT, a starting place is to read the privacy policy of OpenAI, the developer of ChatGPT. The privacy policy includes specific information related to the use of ChatGPT for children:

"7. Children. Our Services are not directed to, or intended for, children under 13. We do not knowingly collect Personal Data from children under 13... Users under 18 must have permission from their parent or guardian to use our Services."

Schools and districts are also encouraged to look over OpenAI’s Educator Considerations for ChatGPT for additional information.

District IT Role: District IT personnel should participate in the establishment of clear approval processes to vet genAI tools for data privacy, security, and compliance before classroom use. This includes reviewing platforms for risks to personal data and personally identifiable information (PII). Teachers play a critical role by ensuring they only use apps, websites, or tools that have been formally approved. Seeking IT approval before adoption not only protects students but also aligns instruction with district policies, federal regulations, and best practices for safeguarding sensitive information. This vetting should also consider browser-based AI extensions, third-party integrations, and tools accessed through personal staff or student accounts that may collect, transmit, or store student data outside district visibility.

Personally Identifiable Information (PII), oversharing and genAI.

ORS 339.329 (c) defines the state of Oregon’s statewide tip line concerning threats or potential threats to student safety. In it Personally Identifiable Information (PII) is defined as any information that would permit the identification of a person… and is not limited to name, phone number, physical address, electronic mail address, race, gender, gender identity, sexual orientation, disability designation, religious affiliation, national origin, ethnicity, school of attendance, city, county or any geographic identifier included in information conveyed… or information identifying the machine or device used by the person…”

Users, both school staff and students, should be cautious when entering any personal information into any and all digital applications, including generative AI tools. Entering Personally Identifiable Information (PII) into any generative AI system should always be avoided. This is a particularly important consideration when using generative AI applications such as ChatGPT, as the information entered by users (including prompts and questions posed, etc.) is stored on the application’s server and integrated into the large language model used to respond to user prompts. Essentially, generative AI tools are learning from every single piece of text or other input typed into their platforms.³² While this statement generally still holds true as of the most recent release of this guidance document, many genAI tools are now offering a 'private mode' and / or education versions in which the companies who own then state that they are not retaining data for model training, though this cannot be independently verified.

Oversharing occurs when individuals share too much of that PII or other sensitive information in inappropriate or unsecured contexts. When we think of genAI tools like ChatGPT specifically, oversharing can lead to significant risks. These risks can potentially include:

Exposure to data breaches
Misuse of information and
Unintended data harvesting

GenAI tools, while powerful in processing and generating content based on vast data sets, can retain or expose information in ways that might compromise privacy. This makes understanding and mitigating oversharing critically important in K-12 educational settings where schools are dealing with minors and the federal privacy regulations cited above, like FERPA and COPPA.

School Staff Oversharing. For school staff, the dangers of oversharing with generative AI tools can have potential professional and legal ramifications. Staff might inadvertently, or even intentionally, enter sensitive information such as student performance data, behavioral reports, or even personal health information into AI systems. Staff should also avoid entering any student information into AI tools when drafting feedback, behavior documentation, communications, or instructional materials unless the tool has been formally approved and vetted for compliance with privacy requirements. All staff need to understand they should not enter this type of personal information into AI systems.

Doing so poses potential risks of violating privacy regulations like FERPA, which could lead to legal consequences for the school and the individual. Moreover, such data breaches can damage the trust between educators and students and potentially harm the school’s reputation. It is crucial for all school staff to be trained on the appropriate use of AI tools and the types of information that should never be entered into such systems.

Student Oversharing

Students are at heightened risk when it comes to data privacy, not because of carelessness, but because they are still developing an understanding of how personal information can be stored, shared, or misused in digital spaces. This is particularly true with genAI chatbots who are programmed and train to respond like humans.^33,34 When students disclose personal anecdotes, family details, or sensitive identifiers in generative AI tools and other online platforms, that information may be retained, logged, or exposed through data breaches, weak security practices, or misuse across platforms. Such exposure can create opportunities for cyberbullying, identity theft, online sextortion, trafficking, or other forms of exploitation. To reduce these risks, educators and schools should proactively teach safe digital practices as a part of a larger effort to teach AI and information literacy, embed privacy awareness into learning experiences, and ensure strong protections through secure platforms, strict privacy settings, and clear usage policies. Safeguarding student data is a shared responsibility that requires both systemic protections and ongoing staff and student guidance. Districts should incorporate explicit instruction on privacy, consent, and digital identity protection into existing digital citizenship, health education, and AI literacy learning so students understand how synthetic media and data sharing can affect their safety and well-being.

While there is a growing number of online resources for teacher professional development resources and K-12 student lessons that focus on these issues, including many listed below, Oregon has a number of resources helpful in this specific area. Oregon’s Health Education Standards include age-appropriate requirements related to social media, AI, and data privacy in order to promote student safety with skills-based education. Also created specifically for Oregon youth, SafeOregon, Oregon’s statewide tipline, provides a curriculum and accompanying teacher’s guide for middle and high school students on topics of recognizing and analyzing risky online behavior and seeking help through trusted adults. These resources, free to all Oregon schools and districts, align to standards and are easily implemented in classrooms. Another valuable resource worth highlighting here is the Commonsense.org Quick Digital Citizenship Lessons for Grades K-12, which includes lessons that are divided up by grade level.

The Implications of Synthetic Media and Deepfakes

Synthetic media refers to digital content that is created using genAI tools like OpenAI’s Dall-E (image generation) and Sora (video generation) to audio tools from Lovo AI (audio generation). GenAI’s ability to make these media appear real (i.e. photorealistic) and / or authentic (i.e. portray known people, events, etc.) is increasing at a rapid pace. These online tools allow anyone to take images, photos, etc. from social media or other online platforms and manipulate them using genAI tools. A 2024 study from the University of Waterloo found that a large number of participants (39%) struggled to correctly identify synthetic media versus real photographs of people and that many participants overestimated their own ability to recognize synthetic media.³⁵

The continued development of genAI tools able to produce realistic synthetic media offers educators some promising opportunities for student learning. For example, teachers could use these genAI tools to:

Create engaging and interactive learning materials, such as virtual simulations and educational videos that can enhance students’ understanding of complex concepts,
Create personalized learning experiences by generating customized content tailored to individual student needs and interests,
Work with students to explore digital storytelling, multimedia projects and other creative endeavors that foster critical thinking as well as digital citizenship and information literacy skills.

Analyzing and understanding synthetic media can help encourage students to think critically about authenticity, bias and manipulation.³⁶

School district leaders can help staff and students alike by prioritizing the understanding of the risks posed by deepfakes and other synthetic media, which include potential risks of harassment, intimidation, bullying and cyberbullying as defined in Oregon’s ORS 339.351. More resources are becoming available regularly around this topic; one good option available from AI for Education is their Classroom Guide on Uncovering Deepfakes.

School district policies, guidance and student codes of conduct designed to address the use and misuse of genAI tools will want to include clear definitions and prohibitions of the creation and dissemination of deepfakes and other synthetic media designed with the intention to harm or harass others. These efforts should include mechanisms for reporting such incidents, as mandated by ORS 339.356, which requires schools to have a uniform procedure for reporting and investigating acts of harassment, intimidation, bullying and cyberbullying. Oregon’s anonymous school safety tip line, SafeOregon, is available to all districts and schools and should be a part of reporting procedures to ensure safety for all students and school communities.

District leaders should be aware that Oregon law (ORS 163.472) prohibits the unlawful dissemination of an intimate image. Recent revisions to this law now include images that have been digitally created, generated, manipulated or altered without consent. This law has implications for school response when AI-generated or manipulated intimate images are created or shared in ways that harm students or staff.

Additionally, school district leaders should be aware of a growing number of cases involving AI-generated media (e.g. video, images, audio etc.) being characterized as “child sexual abuse material” (CSAM). Although Oregon does not currently have laws specifically targeting synthetic or deepfake CSAM, existing federal laws criminalize the creation, distribution, and possession of such material, including 18 U.S.C. § 2256 and the PROTECT Act of 2003. These laws have been used to prosecute individuals even when no real child was involved, and federal law enforcement agencies have affirmed their continued applicability.

In May 2024, the Federal Bureau of Investigation stated, “CSAM generated by AI is still CSAM, and we will hold accountable those who exploit AI to create obscene, abusive, and increasingly photorealistic images of children.”

While several states, such as Pennsylvania with Act 36 of 2024, have enacted laws addressing deepfakes and nonconsensual synthetic media, efforts at the federal level, including the previously introduced H.R. 5586 (DEEPFAKES Accountability Act), have not yet resulted in enacted legislation. In the absence of new federal or Oregon-specific laws, school districts should consult legal counsel regarding related policies and ensure staff are trained to recognize the dangers and legal implications of AI-generated CSAM and other synthetic media.

Specific recommendations for school districts include:

Examining district policies about how permission is obtained and how media (audio, video and digital photographs) of staff, students and other community members is used for posting online through district websites and social media.

Policy makers will want to have clarity and understanding regarding the determination of jurisdiction for how and when a school can investigate cases of potential technology misuse. This includes the basic understanding of whether the incident occurred inside or outside of school hours, whether it was on district equipment and what impact the post potentially had on the school community. Policies and training should also clarify when incidents occurring off campus may still require school response due to impact on student safety, school climate, or the learning environment.

Consulting with organizations that have expertise in harassment, intimidation, bullying, cyberbullying, and child sexual abuse as well as local law enforcement (as appropriate), when developing district plans and policies that relate to artificial intelligence, synthetic media, deepfakes and school safety. Incorporating risks associated with deepfakes, online exploitation and grooming into existing threat assessment efforts.

Ensuring district policies relating to harassment, intimidation, bullying, cyberbullying, and mandatory reporting as required by ORS 339.356 include procedures and consequences relating to incidents involving deepfakes of school staff, students and/or their families or caregivers, including the SafeOregon Tip Line Specifically, connection and possible referral to Behavioral Safety [threat] Assessment Teams or Sexual Incident Response Committees should be considered on a case by case basis. Policy makers and district leaders should ensure the use of inclusive practices when it comes to consequences, supporting student mental health and wellbeing and prohibiting or limiting exclusionary practices such as suspension or expulsion if the law allows.

Implement training for all school staff which focuses on the identification of synthetic media and deepfakes and how to respond appropriately according to district policy and reporting requirements, including details for appropriate reporting when potential incidents occur. Encourage staff to be vigilant in their ongoing monitoring. Because this technology is changing rapidly, training for staff should be provided on a regular and ongoing basis. Training should also address AI-generated voice cloning, impersonation, and manipulated audio/video intended to deceive or harm others.

Ensure that there is a process in place to respond to incidents where non-consensual intimate images have been generated and/or shared to support the person or people harmed, including providing trauma-informed care and accountability. District response procedures should include timely reporting, coordination with families, and consultation with appropriate authorities when non-consensual intimate images or harmful synthetic media are involved, along with trauma-informed supports for impacted students.

Implement regularly occurring learning opportunities for students of all grade levels that emphasize responsible creation and consumption of synthetic media and the risks and ethical implications involved. This should be a part of a larger body of digital ethics and information literacy learning being offered to all students. Lessons may include:

Connecting to student mental health and well-being, incorporating Oregon’s Transformative Social and Emotional (TSEL) framework and Health Education standards whenever possible

Building skills and knowledge related to consent, boundaries, and legal rights that emphasize the importance of consent in all interactions, both online and offline, when sharing images and videos. This content is often included within a district’s comprehensive sexuality education program (OAR 581-022-2050).

Identifying steps to help recognize common signs of deepfakes

Understanding the long-lasting harm that sharing non-consensual intimate images has on the victim, including deep mental health impacts, social harm, privacy violations, and negative academic outcomes.

Understanding restorative justice practices to support the people involved when non-consensual intimate images have been generated and/or shared.

Understanding the potential impact synthetic media and deepfakes can have on misinforming society

Reviewing of student codes of conduct, potential consequences for misuse, privacy violations, expectations around bullying and harassment

Teaching of how students are to report incidents of misuse, bullying and harassment to school staff

Promoting the use of the Safe Oregon tip line safeoregon.com (ORS 339.329).

Plagiarism: A common concern from educators is that generative AI and other AI technologies are being used by students to write essays and complete assignments for them. This is a valid concern.

While generative AI tools were initially blocked or banned in many school districts due to concerns about cheating and plagiarism, many districts across the country have now reversed course and are removing these restrictions. With access increasing, it is critical that districts take a proactive and intentional approach, not just allowing access, but actively teaching students how to use genAI tools productively, ethically, and responsibly.

This includes helping students understand how to use AI tools to enhance learning rather than replace it, in order to avoid overreliance and cognitive offloading. All students should have meaningful opportunities to develop the skills and judgment needed to use genAI as a tool for inquiry, creativity, and deeper learning which will continue to be essential skills in preparation for both college and the future workforce.

Steps to help address plagiarism concerns and avoid the risk of cognitive offloading:

I. Avoid Biased Detection Tools: Be cautious with AI-based plagiarism detectors. At this time, we strongly recommend that educators avoid using AI-based plagiarism detection tools.

Current research consistently shows that these tools produce false positives, especially for multilingual learners, due to language patterns and bias in model training. This is a clear example of how bias continues to persist in generative AI tools and should not be used as a primary method for verifying originality.

II. Design for Authentic Learning: Redesign existing assignments to promote student voice and engaging and authentic learning opportunities.

Rethink assignment structures by focusing on the standards and skills being addressed, rather than the final product alone.

Incorporate durable skills such as collaboration, communication, critical thinking, and adaptability.

Build in opportunities for students to problem-solve, analyze, synthesize, and share their thinking through classroom discussions, presentations, and reflective work.

Use project-based learning and inquiry-driven tasks to encourage deeper engagement and personal relevance.

III. Use Formative Assessment to Understand Student Process

Monitor student learning throughout the writing journey
Embed formative check-ins across the writing process to get a full picture of student growth.
Use strategies like:

Collecting paper drafts or early outlines
Reviewing Google Doc version history to see evidence of revisions
Hosting writing conferences or peer reviews

These practices can help support authentic engagement and help teachers better understand individual student voice and development. It should be noted that some students, according to their IEP or 504 may not be able to submit paper drafts, so teachers should plan accordingly. In addition, genAI tools can be helpful in supporting students as they iterate through ideas and drafts prior to producing a final product.

IV. Develop Strong Policies and Student Expectations: Determine when and how genAI tools can and cannot be used in the classroom. Be sure to discuss the potential risks of using genAI tools with students (e.g. inaccurate information, bias, cognitive offloading etc.) and provide students with digital media and AI literacy curriculum and learning opportunities so that they understand these risks.

Use ODE’s genAI Policy Development guidance document to help support these efforts.
Be sure to review and understand the AI Assessment Scale (AIAS) (original research article here) for potential inclusion in your districts AI policy planning and development. This is a easy-to-use framework helping in guiding both educators and students on the appropriate and ethical use of genAI tools in assessment design.

VI. Support students in sharing their writing process such as discussing how and where they got their information and their strategy for integrating it into their drafts.

Creating discussion opportunities in addition to having students turn in outlines and drafts of their writing along the way helps show that the process is equally as valuable as the final product, which can be supportive in creating strong writers and researchers. Teachers looking at student writing can think about some of the following when determining if a student potentially plagiarized the work:

Does the student's voice come across clearly in the writing?
Are sentences too repetitive? Does the writing include regular use of the em dash (—)?
Does the paper seem too predictable or directionless and not make normal progress?
Design writing assignments that prioritize process over product to help prevent misuse of genAI tools and foster authentic student learning.

When students engage meaningfully in each stage of the writing process from brainstorming, outlining and drafting to revising and reflecting, they are less likely to resort to plagiarism, whether intentional or AI-assisted.

Digital platforms like Google Docs and other similar applications can support this approach through built-in tools such as version history, which allows teachers to see how a document evolved over time. For even greater visibility, consider using browser add-ons like the free Draftback Chrome Extension, which replays a video of a document’s writing history. These tools don’t just serve as deterrents; they can also become an important part of the process and support formative feedback, metacognition, and writing skills development over time.³⁷

Pair this type of approach with intentional instructional strategies:

Have students submit artifacts from each phase of their writing (e.g., annotated sources, hand written outlines, peer feedback, etc.).
Create writing prompts that are personal, specific, or reflective, making them harder to answer meaningfully with AI alone.
Hold brief writing conferences or ask students to explain and reflect on their thinking through oral or written metacognitive reflections.
Above all, shift the classroom culture from policing to coaching, helping students understand not just what plagiarism is, but why authentic work matters in developing their own voice and learning.

VII. Consider how to teach and support students in developing digital media literacy skills. For example, the International Baccalaureate (IB) has determined that rather than banning software, they will support schools in using software to “...support their students on how to use these tools ethically in line with our principles of academic integrity.” ³⁸

Copyright/Licensing Unknowns: Understanding copyright laws is an important element of guiding the use of genAI and other AI technologies in the classroom because this is new technology and there are not yet clear boundaries regarding how AI tools can use copyrighted materials to learn from, nor who owns content generated by AI tools. Recently in September 2025, Anthropic (owner of the Claude chatbot) agreed to pay $1.5 billion dollars to book authors after the judge ruled the company had illegally downloaded and stored millions of copyrighted books. As of the release of this guidance document, AI-generated content cannot be copyrighted unless a human author contributes a measurably significant amount of creative input. As companies continue to develop licenses on their products, it is essential for educators to reflect on the implications of copyright/licensing unknowns. The U.S Copyright Office webpage on Copyright and Artificial Intelligence provides ongoing updates and revisions to copyright law and policy issues related to AI.

Review licensing types on Creative Commons and discuss copyright and licensing information with staff and students.
Review the Copyright Office’s New Artificial Intelligence Initiative, which will continue to have the most up-to-date information on legal developments regarding copyright and generative AI. While not specific to education, as educators often use, curate, and share instructional materials through digital means, understanding copyright laws and how they impact the use of information developed through AI will be essential.

When developing policy around genAI in K–12 classrooms, it is essential to center equity in every decision to ensure that learning experiences reflect and affirm students’ sociocultural identities and lived experiences. GenAI is a component of a larger digital learning ecosystem and trained on data and information that humans helped initially create, including the historical systemic bias of education systems and learning communities.³⁹

Although digital tools, including genAI and other AI tools, can help close opportunity gaps, their use can also risk reinforcing or deepening existing disparities if not implemented with a deliberate equity lens. For example:

AI detection facial recognition programs for student behavior can unfairly single out students of color.
GenAI generated images for projects in the classroom may contain racist, sexist, and/or ableist stereotypes.
An AI application may impede the educational progress of English Language Learners or students with vocal support needs failing to recognize their speech and asking them to repeat or reiterate their input, whereas a human hearing the same speech may understand it the first time.

Staff and students need clear policy and ongoing training around the positive and productive use of these tools. As highlighted in the resource on Avoiding the Discriminatory Use of Artificial Intelligence from the federal Department of Education, the use of AI in schools should align with federal civil rights laws to prevent discrimination and promote equitable access for all students.

Equity implications to keep front and center when designing policy specific to generative AI in K-12 classrooms includes bias, inaccuracy, plagiarism, copyright/licensing unknowns and equity of access. The table below provides examples of strategies to address some of these equity implications.

Given the inherent equity impacts of introducing generative AI into the digital learning ecosystem, educating students, families, and educators (including paraeducators, secretaries, support staff, etc.) on these equity implications can help to move toward using genAI tools in ways that are culturally responsive and sustaining for students, families, and communities.

Access to generative AI, and the lack thereof, can have significant and lasting equity impacts on students, both during K–12 education and in preparation for college, careers, and civic life. This is particularly true for students within the three digital divides, as detailed in the 2024 National Educational Technology Plan (NETP), particularly rural, low-income, newcomer / SLIFE (Students with Limited or Interrupted Formal Education) and migrant students. As districts develop policies around student interaction with AI tools, addressing if, how, and when students have meaningful access to genAI platforms should be a priority. Ensuring equitable access to tools, proactive usage, and sustained teacher training in generative AI will be crucial in the years ahead, and should be an important part of our schools’ collective effort to close these gaps.

Key Equity Considerations for AI Access and Implementation

Assess the impact of the three digital divides: The NETP identifies the divides in access (devices/connectivity), design (inclusive, high-quality learning experiences), and use (the ability to apply technology in creative and meaningful ways).
Highlight vulnerable populations: Students in rural, low-income, multilingual, tribal, and special education settings, and those students considered newcomers, are disproportionately impacted by inequitable access to emerging technologies like genAI.
Emphasize teacher capacity: Equitable access includes supporting educators with the time, tools, and training they need to confidently and effectively integrate genAI into instruction.
Position AI literacy as a right: The ability to understand, engage with, and question AI systems should be seen as a modern civil right, essential to future-ready learning and equity.

Strategies to Address Equity of Access and Implementation Issues:

As AI rapidly reshapes education and the workforce, equity must remain central. Unequal access to these tools could deepen existing gaps, even as proficiency with AI becomes critical for future opportunities. While concerns about AI-driven job loss are real, what we know with certainty is that students need to graduate with durable skills and the ability to use AI responsibly, ethically, and effectively. The imperative is to teach how AI tools work to every citizen and especially to our young people.
Educators, both certified and classified staff, will need training to support their students in the use of this technology. For example, generative AI can be a particularly impactful tool for students with disabilities and multilingual learners. Not using these tools has the potential to limit students’ access to learning opportunities.
Talk to students, educators, families, community members, and industry professionals to better understand the potential uses of generative AI and how it might be used as a skill set for future employment.
Be attentive to the cost of platforms such as ChatGPT. While many of these tools offer limited free versions, full access to higher quality features and functionality now requires paid subscriptions. This creates potential equity implications for students and families who may not be able to afford the associated costs, limiting their ability to benefit from these resources. See ODE’s Digital Instructional Materials (DIM) Toolkit for more information on different tools and platforms.

Bias: GenAI models are trained on vast datasets that reflect historical and systemic inequalities. As a result, they can reproduce or even amplify biases related to race, gender, language, geography, and culture. These biases may appear in subtle ways—such as prioritizing dominant cultural narratives or embedding assumptions in phrasing.

Although developers use fine-tuning, adversarial testing (feeding AI tricky or misleading input to find weaknesses), and bias-mitigation strategies, no AI system can be truly neutral or culturally self-aware. Because these tools lack lived experience and contextual understanding, they may still generate inaccurate or exclusionary responses.
Educators and students should remain critical users of AI by questioning outputs, cross-checking information, and designing prompts and curriculum that center equity, diverse perspectives, and inclusive values.
The Kapor Foundation’s Responsible AI and Tech Justice: A Guide for K-12 Education is an important resource for ethical and equitable considerations of AI in schools.
For updates, visit ODE’s Digital Learning page, sign up for the quarterly Digital Learning newsletter, or contact the team at ODE.DigitalLearning@ode.oregon.gov.

Inaccuracy: Generative AI does not inherently know the difference between fact and fiction, and should not be assumed to provide reliable information.

These tools generate responses from data patterns, not from a verified knowledge base. GenAI is getting better, but is still known to produce plausible but incorrect or fabricated content, often called “AI hallucination.”
Although newer models use techniques like retrieval augmentation and human feedback training, human oversight is still essential. Educators and students must verify claims through trusted sources and treat AI-generated references or citations with caution unless they come from live, linked sources.
Teaching students to identify, question, and validate AI content is a critical component of digital media and AI literacy.

Be sure to also check out:

Resources To Support The Development Of Policies And Protocols For The Use Of Generative AI In K-12 Classrooms

Developing Policy and Protocols for the use of Generative AI in K-12 Classrooms: This document serves as a worksheet style resource for school and district leaders when considering the use of AI in schools. The document highlights policies from across Oregon, the nation and internationally and provides district leaders a genAI-specific policy and protocol development planning tool.

Footnotes are available for all above references.

For more information, please contact ODE’s Digital Learning Team at ODE.DigitalLearning@ode.oregon.gov.

Generative AI Resources

Important News & Resources

Generative Artificial Intelligence in K-12 Classrooms

A. Guiding Principles for Responsible and Ethical Use of GenAI in Education

B. Keeping Humans In The Loop

C. Long-term Impacts of AI On Our Students’ Futures

2. Building GenAI Capacity, Literacy, and Safeguards in Your School

A. Deeper Understanding of Durable Skills

B. Information and AI Literacy as Essential Durable Skills

C. The Risks of Our Students Depending Too Much on GenAI Instead of Their Own Thinking

D. Concerns About Forming Human-Like Relationships with AI

E. Create Policy Guardrails Before GenAI Enters Your Districts Classrooms

A. How GenAI Tools Can Help Support All Students

B. Ensuring Staff and Student Privacy in School Settings

C. Addressing Plagiarism and Other Integrity Concerns in the Age of GenAI

D. GenAI Copyright and Licensing Guidance for School Leaders

E. Understanding Equity Issues Raised by GenAI in K12 Settings