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In Neal Stephenson's 1995 science fiction novel, The Diamond Age, readers meet Nell, a young girl who comes into possession of a highly advanced book, The Young Lady's Illustrated Primer. The book is not the usual static collection of texts and images but a deeply immersive tool that can converse with the reader, answer questions, and personalize its content, all in service of educating and motivating a young girl to be a strong, independent individual.

Such a device, even after the introduction of the Internet and tablet computers, has remained in the realm of science fiction-until now. Artificial intelligence, or AI, took a giant leap forward with the introduction in November 2022 of ChatGPT, an AI technology capable of producing remarkably creative responses and sophisticated analysis through human-like dialogue. It has triggered a wave of innovation, some of which suggests we might be on the brink of an era of interactive, super-intelligent tools not unlike the book Stephenson dreamed up for Nell.

Sundar Pichai, Google's CEO, calls artificial intelligence " more profound than fire or electricity or anything we have done in the past." Reid Hoffman, the founder of LinkedIn and current partner at Greylock Partners, says, "The power to make positive change in the world is about to get the biggest boost it's ever had." And Bill Gates has said that "this new wave of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone."

Over the last year, developers have released a dizzying array of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. These technologies are rapidly improving, and developers are introducing capabilities that would have been considered science fiction just a few years ago. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism.

In the realm of education, this technology will influence how students learn, how teachers work, and ultimately how we structure our education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to effect "probably the biggest positive transformation that education has ever seen." But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm.
What Is Generative AI?
Artificial intelligence is a branch of computer science that focuses on creating software capable of mimicking behaviors and processes we would consider "intelligent" if exhibited by humans, including reasoning, learning, problem-solving, and exercising creativity. AI systems can be applied to an extensive range of tasks, including language translation, image recognition, navigating autonomous vehicles, detecting and treating cancer, and, in the case of generative AI, producing content and knowledge rather than simply searching for and retrieving it.

" Foundation models " in generative AI are systems trained on a large dataset to learn a broad base of knowledge that can then be adapted to a range of different, more specific purposes. This learning method is self-supervised, meaning the model learns by finding patterns and relationships in the data it is trained on.

Large Language Models (LLMs) are foundation models that have been trained on a vast amount of text data. For example, the training data for OpenAI's GPT model consisted of web content, books, Wikipedia articles, news articles, social media posts, code snippets, and more. OpenAI's GPT-3 models underwent training on a staggering 300 billion "tokens" or word pieces, using more than 175 billion parameters to shape the model's behavior-nearly 100 times more data than the company's GPT-2 model had.

By doing this analysis across billions of sentences, LLM models develop a statistical understanding of language: how words and phrases are usually combined, what topics are typically discussed together, and what tone or style is appropriate in different contexts. That allows it to generate human-like text and perform a wide range of tasks, such as writing articles, answering questions, or analyzing unstructured data.

LLMs include OpenAI's GPT-4, Google's PaLM, and Meta's LLaMA. These LLMs serve as "foundations" for AI applications. ChatGPT is built on GPT-3.5 and GPT-4, while Bard uses Google's Pathways Language Model 2 (PaLM 2) as its foundation.

Some of the best-known applications are:

ChatGPT 3.5. The free version of ChatGPT released by OpenAI in November 2022. It was trained on data only up to 2021, and while it is very fast, it is prone to inaccuracies.

ChatGPT 4.0. The newest version of ChatGPT, which is more powerful and accurate than ChatGPT 3.5 but also slower, and it requires a paid account. It also has extended capabilities through plug-ins that give it the ability to interface with content from websites, perform more sophisticated mathematical functions, and access other services. A new Code Interpreter feature gives ChatGPT the ability to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends.

Microsoft Bing Chat. An iteration of Microsoft's Bing search engine that is enhanced with OpenAI's ChatGPT technology. It can browse websites and offers source citations with its results.

Google Bard. Google's AI generates text, translates languages, writes different kinds of creative content, and writes and debugs code in more than 20 different programming languages. The tone and style of Bard's replies can be finetuned to be simple, long, short, professional, or casual. Bard also leverages Google Lens to analyze images uploaded with prompts.

Anthropic Claude 2. A chatbot that can generate text, summarize content, and perform other tasks, Claude 2 can analyze texts of roughly 75,000 words-about the length of The Great Gatsby -and generate responses of more than 3,000 words. The model was built using a set of principles that serve as a sort of "constitution" for AI systems, with the aim of making them more helpful, honest, and harmless.

These AI systems have been improving at a remarkable pace, including in how well they perform on assessments of human knowledge. OpenAI's GPT-3.5, which was released in March 2022, only managed to score in the 10th percentile on the bar exam, but GPT-4.0, introduced a year later, made a significant leap, scoring in the 90th percentile. What makes these feats especially impressive is that OpenAI did not specifically train the system to take these exams; the AI was able to come up with the correct answers on its own. Similarly, Google's medical AI model substantially improved its performance on a U.S. Medical Licensing Examination practice test, with its accuracy rate jumping to 85 percent in March 2021 from 33 percent in December 2020.

These two examples prompt one to ask: if AI continues to improve so rapidly, what will these systems be able to achieve in the next few years? What's more, new studies challenge the assumption that AI-generated responses are stale or sterile. In the case of Google's AI model, physicians preferred the AI's long-form answers to those written by their fellow doctors, and nonmedical study participants rated the AI answers as more helpful. Another study found that participants preferred a medical chatbot's responses over those of a physician and rated them significantly higher, not just for quality but also for empathy. What will happen when "empathetic" AI is used in education?

Other studies have looked at the reasoning capabilities of these models. Microsoft researchers suggest that newer systems "exhibit more general intelligence than previous AI models" and are coming "strikingly close to human-level performance." While some observers question those conclusions, the AI systems display an increasing ability to generate coherent and contextually appropriate responses, make connections between different pieces of information, and engage in reasoning processes such as inference, deduction, and analogy.

Despite their prodigious capabilities, these systems are not without flaws. At times, they churn out information that might sound convincing but is irrelevant, illogical, or entirely false-an anomaly known as "hallucination." The execution of certain mathematical operations presents another area of difficulty for AI. And while these systems can generate well-crafted and realistic text, understanding why the model made specific decisions or predictions can be challenging.
The Importance of Well-Designed Prompts
Using generative AI systems such as ChatGPT, Bard, and Claude 2 is relatively simple. One has only to type in a request or a task (called a prompt), and the AI generates a response. Properly constructed prompts are essential for getting useful results from generative AI tools. You can ask generative AI to analyze text, find patterns in data, compare opposing arguments, and summarize an article in different ways (see sidebar for examples of AI prompts).

One challenge is that, after using search engines for years, people have been preconditioned to phrase questions in a certain way. A search engine is something like a helpful librarian who takes a specific question and points you to the most relevant sources for possible answers. The search engine (or librarian) doesn't create anything new but efficiently retrieves what's already there.

Generative AI is more akin to a competent intern. You give a generative AI tool instructions through prompts, as you would to an intern, asking it to complete a task and produce a product. The AI interprets your instructions, thinks about the best way to carry them out, and produces something original or performs a task to fulfill your directive. The results aren't pre-made or stored somewhere-they're produced on the fly, based on the information the intern (generative AI) has been trained on. The output often depends on the precision and clarity of the instructions (prompts) you provide. A vague or poorly defined prompt might lead the AI to produce less relevant results. The more context and direction you give it, the better the result will be. What's more, the capabilities of these AI systems are being enhanced through the introduction of versatile plug-ins that equip them to browse websites, analyze data files, or access other services. Think of this as giving your intern access to a group of experts to help accomplish your tasks.

One strategy in using a generative AI tool is first to tell it what kind of expert or persona you want it to "be." Ask it to be an expert management consultant, a skilled teacher, a writing tutor, or a copy editor, and then give it a task.

Prompts can also be constructed to get these AI systems to perform complex and multi-step operations. For example, let's say a teacher wants to create an adaptive tutoring program-for any subject, any grade, in any language-that customizes the examples for students based on their interests. She wants each lesson to culminate in a short-response or multiple-choice quiz. If the student answers the questions correctly, the AI tutor should move on to the next lesson. If the student responds incorrectly, the AI should explain the concept again, but using simpler language.

Previously, designing this kind of interactive system would have required a relatively sophisticated and expensive software program. With ChatGPT, however, just giving those instructions in a prompt delivers a serviceable tutoring system. It isn't perfect, but remember that it was built virtually for free, with just a few lines of English language as a command. And nothing in the education market today has the capability to generate almost limitless examples to connect the lesson concept to students' interests.

Chained prompts can also help focus AI systems. For example, an educator can prompt a generative AI system first to read a practice guide from the What Works Clearinghouse and summarize its recommendations. Then, in a follow-up prompt, the teacher can ask the AI to develop a set of classroom activities based on what it just read. By curating the source material and using the right prompts, the educator can anchor the generated responses in evidence and high-quality research.

However, much like fledgling interns learning the ropes in a new environment, AI does commit occasional errors. Such fallibility, while inevitable, underlines the critical importance of maintaining rigorous oversight of AI's output. Monitoring not only acts as a crucial checkpoint for accuracy but also becomes a vital source of real-time feedback for the system. It's through this iterative refinement process that an AI system, over time, can significantly minimize its error rate and increase its efficacy.
Uses of AI in Education
In May 2023, the U.S. Department of Education released a report titled Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. The department had conducted listening sessions in 2022 with more than 700 people, including educators and parents, to gauge their views on AI. The report noted that "constituents believe that action is required now in order to get ahead of the expected increase of AI in education technology-and they want to roll up their sleeves and start working together." People expressed anxiety about "future potential risks" with AI but also felt that " AI may enable achieving educational priorities in better ways, at scale, and with lower costs."

AI could serve-or is already serving-in several teaching-and-learning roles:

Instructional assistants. AI's ability to conduct human-like conversations opens up possibilities for adaptive tutoring or instructional assistants that can help explain difficult concepts to students. AI-based feedback systems can offer constructive critiques on student writing, which can help students fine-tune their writing skills. Some research also suggests certain kinds of prompts can help children generate more fruitful questions about learning. AI models might also support customized learning for students with disabilities and provide translation for English language learners.

Teaching assistants. AI might tackle some of the administrative tasks that keep teachers from investing more time with their peers or students. Early uses include automated routine tasks such as drafting lesson plans, creating differentiated materials, designing worksheets, developing quizzes, and exploring ways of explaining complicated academic materials. AI can also provide educators with recommendations to meet student needs and help teachers reflect, plan, and improve their practice.

Parent assistants. Parents can use AI to generate letters requesting individualized education plan (IEP) services or to ask that a child be evaluated for gifted and talented programs. For parents choosing a school for their child, AI could serve as an administrative assistant, mapping out school options within driving distance of home, generating application timelines, compiling contact information, and the like. Generative AI can even create bedtime stories with evolving plots tailored to a child's interests.

Administrator assistants. Using generative AI, school administrators can draft various communications, including materials for parents, newsletters, and other community-engagement documents. AI systems can also help with the difficult tasks of organizing class or bus schedules, and they can analyze complex data to identify patterns or needs. ChatGPT can perform sophisticated sentiment analysis that could be useful for measuring school-climate and other survey data.

Though the potential is great, most teachers have yet to use these tools. A Morning Consult and EdChoice poll found that while 60 percent say they've heard about ChatGPT, only 14 percent have used it in their free time, and just 13 percent have used it at school. It's likely that most teachers and students will engage with generative AI not through the platforms themselves but rather through AI capabilities embedded in software. Instructional providers such as Khan Academy, Varsity Tutors, and DuoLingo are experimenting with GPT-4-powered tutors that are trained on datasets specific to these organizations to provide individualized learning support that has additional guardrails to help protect students and enhance the experience for teachers.

Google's Project Tailwind is experimenting with an AI notebook that can analyze student notes and then develop study questions or provide tutoring support through a chat interface. These features could soon be available on Google Classroom, potentially reaching over half of all U.S. classrooms. Brisk Teaching is one of the first companies to build a portfolio of AI services designed specifically for teachers-differentiating content, drafting lesson plans, providing student feedback, and serving as an AI assistant to streamline workflow among different apps and tools.

Providers of curriculum and instruction materials might also include AI assistants for instant help and tutoring tailored to the companies' products. One example is the edX Xpert, a ChatGPT-based learning assistant on the edX platform. It offers immediate, customized academic and customer support for online learners worldwide.

Regardless of the ways AI is used in classrooms, the fundamental task of policymakers and education leaders is to ensure that the technology is serving sound instructional practice. As Vicki Phillips, CEO of the National Center on Education and the Economy, wrote, "We should not only think about how technology can assist teachers and learners in improving what they're doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI."

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The leap into a new era of machine intelligence carries risks and challenges, but also plenty of promise

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The potential of using artificial intelligence in education to enhance learning, assist teachers and fuel more effective individualized learning is exciting, but also a bit daunting. To even have an intelligent conversation about AI in education, one must first push past imaginary science-fiction scenarios of computers and robots teaching our children, replacing teachers and reducing the human element from what is a fundamentally human activity.

One of the leading writers on the benefits of artificial intelligence in education, Matthew Lynch ( "My Vision for the Future of Artificial Intelligence in Education"), is careful to explore the potential pitfalls along with the benefits, writing that "the use of AI in education is valuable in some ways, but we must be hyper-vigilant in monitoring its development and its overall role in our world."

The ethical considerations are profound, as they are when it comes to using artificial intelligence in any type of setting. AI lacks a so-called "moral compass." So, by one way of looking at it, AI programming is "as ethical as its developer," according to TowardsDataScience, in an article about AI ethics that prescribes two important recommendations moving forward:

1. We need to have ethics built into the idea of why a certain piece of technology, equipped with AI, is being developed.

2. We need to monitor/check/police the outcomes of that specific piece of technology in order to fully understand its behavior and make sure that it's not violating our (human) moral compass.

There is robust debate throughout the technology community and beyond about ethics in artificial intelligence and most university degree programs are integrating courses on AI ethics into their curriculum. There, now that we have identified the ethical elephant in the room, let's talk about the exciting possibilities of AI in education.

The Potential Benefits of AI in Education

Ideally, writes Lynch in The EdAdvocate, "AI does not detract from classroom instruction but enhances it in many ways." He summarizes five intriguing potential pluses of integrating AI in education:

Personalization: "It can be overwhelmingly difficult for one teacher to figure out how to meet the needs of every student in his/her classroom. ... AI systems easily adapt to each student's individual learning needs and can target instruction based on their strengths and weaknesses."

Tutoring: AI systems can "gauge a student's learning style and pre-existing knowledge to deliver customized support and instruction."

Grading: Sure, AI can help grade exams using an answer key; but it can also "compile data about how students performed and even grade more abstract assessments such as essays."

Feedback on course quality: For example, if many students are answering a question incorrectly, "AI can zero in on the specific information or concepts that students are missing, so educators can deliver targeted improvements in materials and methods."

Meaningful and immediate feedback to students: Some students may be shy about taking risks or receiving critical feedback in the classroom, but "with AI, students can feel comfortable to make the mistakes necessary for learning and receive the feedback they need for improvement."

Much of the potential envisioned for AI in education centers on reducing time spent by teachers on tedious tasks to free up time for more meaningful ones.

Automating administrative tasks is also one of five potential benefits spotlighted by Bernard Marr, an author, futurist and technology advisor who cites figures forecasting 47.5% growth from 2017-2021 in the use of artificial intelligence in education in the U.S.

In a video on the potential of AI in education, Marr explains why he sees AI having a "massive impact" in education - emphasizing that "AI is not a threat to teachers; it is not there to replace teachers," but rather to deliver a better education to our children." He envisions a future hybrid model that is designed to "get the best out of our artificially intelligent-enabled systems and our teachers." Marr outlines the potential of AI to help our education provide enhanced:

Differentiated and individualized learning

Automation of administrative tasks

Tutoring and support outside the classroom

Universal access for all students

43 Examples of AI in Education

Inspired by a challenge from "an old school teacher who thinks that AI is ruining education," Matthew Lynch reviews a wide range of topics in a piece titled "26 Ways That Artificial Intelligence Is Transforming Education For The Better." For example:

Adaptive Learning: "Used to teach students basic and advanced skills by assessing their present skill level and creating a guided instructional experience that helps them become proficient."

Assistive Technology: AI can help special needs students access a more equitable education, for example by "reading passages to a visually impaired student."

Early Childhood Education: "AI is currently being used to power interactive games that teach children basic academic skills and more."

Data and Learning Analytics: "AI is currently being used by teachers and education administrators to analyze and interpret data," enabling them to make better-informed decisions.

Scheduling: Helping administrators to schedule courses and individuals to manage their daily, weekly, monthly or yearly schedules.

Facilities Management: AI is effective at "monitoring the status of power, Wi-Fi and water services; alerting the facilities management workers when problems arise."

Overall School Management: AI is currently being used to manage entire schools, powering student records systems, transportation, IT, maintenance, scheduling, budgeting, etc.

Writing: Not only does Lynch assert that AI is already at work helping students improve their writing skills, he confesses, "I am currently using a grammar and usage app to help me write this article."

Running down his list, Lynch also cites current uses of AI in education that include:

Classroom/Behavior Management

Lesson Planning

Classroom Audio-Visual

Parent-Teacher Communication

Language Learning

Test Prep

Assessment

Learning Management Systems

Gamification for Enhanced Student Engagement

Staff Scheduling and Substitute Management

Professional Development

Transportation

Maintenance

Finance

Cybersecurity

Safety and Security

Examples of how artificial intelligence is currently being used in higher education include:

Plagiarism Detection

Exam Integrity

Chatbots for Enrollment and Retention

Learning Management Systems

Transcription of Faculty Lectures

Enhanced Online Discussion Boards

Analyzing Student Success Metrics

Academic Research

Connected Campuses

In terms of AI-infused specific technologies now being used in education, the list grows longer every day. Here are just a few:

Thinkster Math: described by its creators as a "math tutoring program leverages human interaction and groundbreaking artificial intelligence to create personalized learning programs"

Jill Watson: an AI-enabled virtual teaching assistant introduced by the Georgia Institute of Technology in 2016

Brainly: a social media site for classroom questions

Nuance: speech recognition software used by students and faculty; capable of transcribing up to 160 words per minute; especially helpful for students who struggle with writing or have accessibility needs

Cognii: AI-based products, including a virtual learning assistant, for K-12 and higher education institutions, as well as corporate training organizations

KidSense: AI educational solutions designed for children, including a voice-to-text tool with algorithms built to recognize the sometimes harder-to-translate speech of young learners

Content Technologies: instructional design and content application solutions fueled by artificial intelligence research engines

As explained by CEO Dr. Scott Parfitt ( see video), Content Technologies Inc. develops AI learning systems that are focused on "turning big data into information, and information into knowledge."

"We send an engine out, it starts reading at light speed every article it can read. It's learned its own material," says Parfitt. The company's education-focused solutions include:

Palitt: built to help instructors easily create "your own custom lecture series, syllabus or textbook"

Cram101: AI technology that can "turn any textbook into a smart study guide complete with chapter summaries, unlimited true-false and multiple choice practice tests and flashcards all drilled down to a specific textbook, ISBN number, author and chapter."

JustTheFacts101: intended to function as the AI equivalent of an old-fashioned yellow marker, instantly highlighting and generating book and chapter-specific summaries

AI in Education [Inclusion and Universal Access]

Bernard Marr explains that AI tools can enhance inclusion and universal access to education in a number of ways, including:

Helping to "make global classrooms available to all, including those who speak different languages or who might have visual or hearing impairments"

Creating access for "students who might not be able to attend school due to illness"

Better serving "students who require learning at a different level or on a particular subject that isn't available in their own school"

Overall, it is hoped that AI will ultimately help educators make continued progress in addressing the broad range of physical, cognitive, academic, social and emotional factors that can affect student learning and ensure that all students have equal opportunity in education, regardless of their social class, race, gender, sexuality, ethnic background or physical and mental disabilities.

AI in Education [Individualized Learning]

There is also considerable optimism around the idea that, as artificial intelligence becomes a more integral part of the classroom, teachers will be better equipped to offer an individualized learning experience for every student.

According to an article in The Atlantic, ( "Artificial Intelligence Promises a Personalized Education for All"), artificial intelligence holds the potential to "enhance human teachers' abilities to tailor lessons to each student without knocking their class schedule off track," eliminating the need for educators to "teach to the middle," as often happens when their students have a range of skill levels and learning abilities.

Rose Luckin, a professor of learning-centered design at University College London, is quoted as saying that, "The real power of artificial intelligence for education is in the way that we can use it to process vast amounts of data about learners, about teachers, about teaching and learning interactions." Ultimately, AI can "help teachers understand their students more accurately, more effectively."

The Future of AI in Education

Though there continues to be widespread debate over the pros and cons of deploying AI technology in the field of education, including the concerns about depersonalization and the ethical considerations cited above, there is an emerging consensus that the extraordinary range of current and future benefits will carry the day.
This report on Artificial Intelligence in Education was developed by the University of San Diego's innovative, online Master of Science in Applied Artificial Intelligence program, an AI industry thought leader and education partner.

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43 Examples of Artificial Intelligence in Education

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The potential for using artificial intelligence in education to assist teachers and enhance learning is profound. Here's an overview, plus examples of how AI is being used in education today.

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AI Will Transform Teaching and Learning. Let's Get it Right.

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At the recent AI+Education Summit, Stanford researchers, students, and industry leaders discussed both the potential of AI to transform education for the better and the risks at play.

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Today, many priorities for improvements to teaching and learning are unmet. Educators seek technology-enhanced approaches addressing these priorities that would be safe, effective, and scalable. Like all of us, educators use AI-powered services in their everyday lives, such as voice assistants in their homes; tools that can correct grammar, complete sentences, and write essays; and automated trip planning on their phones. As a result, educators see opportunities to use AI-powered capabilities like speech recognition to increase the support available to students with disabilities, multilingual learners, and others who could benefit from greater adaptivity and personalization in digital tools for learning. They are further exploring how AI can enable writing or improving lessons, as well as their process for finding, choosing, and adapting material for use in their lessons.

Educators are also aware of new risks. Useful, powerful functionality can also be accompanied with new data privacy and security risks. Educators recognize that AI can automatically produce output that is inappropriate or wrong. They are wary that the associations or automations created by AI may amplify unwanted biases. They have noted new ways in which students may represent others' work as their own. They are well-aware of "teachable moments" and pedagogical strategies that a human teacher can address but are undetected or misunderstood by AI models. They worry whether recommendations suggested by an algorithm would be fair. Educators' concerns are manifold.

Everyone in education has a responsibility to harness the good to serve educational priorities while also protecting against the dangers that may arise as a result of AI being integrated in educational technology.

NEW!! Report on AI and the Future of Teaching & Learning

Key Insights

AI enables new forms of interaction. Students and teachers can speak, gesture, sketch, and use other natural human modes of communication to interact with a computational resource and each other. AI can generate human-like responses, as well. These new forms of action may provide supports to students with disabilities.

AI can help educators address variability in student learning. With AI, designers can anticipate and address the long tail of variations in how students can successfully learn-whereas traditional curricular resources were designed to teach to the middle or most common learning pathways. For example, AI-enabled educational technology may be deployed to adapt to each student's English language abilities with greater support for the range of skills and needs among English learners.

AI supports powerful forms of adaptivity. Conventional technologies adapt based upon the correctness of student answers. AI enables adapting to a student's learning process as it unfolds step-by-step, not simply providing feedback on right or wrong answers. Specific adaptations may enable students to continue strong progress in a curriculum by working with their strengths and working around obstacles.

AI can enhance feedback loops. AI can increase the quality and quantity of feedback provided to students and teachers, as well as suggesting resources to advance their teaching and learning.

AI can support educators. Educators can be involved in designing AI-enabled tools to make their jobs better and to enable them to better engage and support their students.

Recommendations: Call to Action for Education Leaders

Recommendation #1: Emphasize Humans in the Loop

We reject the notion of AI as replacing teachers. Teachers and other people must be "in the loop" whenever AI is applied in order to notice patterns and automate educational processes. We call upon all constituents to adopt Humans-in-the-Loop as a key criteria.

Recommendation #2: Align AI Models to a Shared Vision for Education

We call upon educational decision makers, researchers, and evaluators to determine the quality of an educational technology based not only on outcomes, but also based on the degree to which the models at the heart of the AI tools and systems align to a shared vision for teaching and learning. The figure to the right describes the important qualities of AI models for education leaders to consider.

Recommendation #3: Design Using Modern Learning Principles

Achieving effective systems requires more than processing "big data"-it requires more than data science. Applications of AI must be based on established, modern learning principles, the wisdom of educational practitioners, and should leverage the expertise in the educational assessment community around detecting bias and improving fairness. Going forward, we also must seek to create AI systems that are culturally responsive and culturally sustaining, leveraging the growth of published techniques for doing so. Further, most early AI systems had few specific supports for students with disabilities and English learners and we must ensure that AI-enabled learning resources are intentionally inclusive of these students.

Recommendation #4: Prioritize Strengthening Trust

Technology can only help us to achieve educational objectives when we trust it. Yet, we learned through a series of public listening sessions that distrust of educational technology and AI is commonplace. Because trust develops as people meet and relate to each other, we call for a focus on building trust and establishing criteria for trustworthiness of emerging educational technologies within the associations, convenings, and professional organizations that bring educators, innovators, researchers, and policymakers together.

Recommendation #5: Inform and Involve Educators

We call on educational leaders to prioritize informing and involving educational constituents so they are prepared to investigate how and when AI fits specific teaching and learning needs, and what risks may rise. Now is the time to show the respect and value we hold for educators by informing and involving them in every step of the process of designing, developing, testing, improving, adopting, and managing AI-enabled educational technology. This includes involving educators in reviewing existing AI-enabled systems, tools, and data use in schools, designing new applications of AI based on teacher input, carrying out pilot evaluations of proposed new instructional tools, collaborating with developers to increase the trustworthiness of the deployed system, and raising issues about risks and unexpected consequences as the system is implemented.

Recommendation #6: Focus R&D on Addressing Context and Enhancing Trust and Safety

Research that focuses on how AI-enabled systems can adapt to context (diversity among learners, variability in instructional approaches, differences in educational settings) is essential to answering the question "Do specific applications of AI work in education, and if so, for whom and under what conditions?" We call upon researchers and their funders to prioritize investigations of how AI can address the long tail of learning variability and to seek advances in how AI can incorporate contextual considerations when detecting patterns and recommending options to students and teachers. Further, researchers should accelerate their attention to how to enhance trust and safety in AI-enabled systems for education.

Recommendation #7: Develop Education-Specific Guidelines and Guardrails

Data privacy regulation already covers educational technology; further, data security is already a priority of school educational technology leaders. Modifications and enhancements to the status quo will be required to address the new capabilities alongside the risks of AI. We call for involvement of all perspectives in the ecosystem to define a set of guidelines (such as voluntary disclosures and technology procurement checklists) and guardrails (such as enhancements to existing regulations or additional requirements) so that we can achieve safe and effective AI for education.

Listening Sessions

The U.S. Department of Education's Office of Educational Technology, with support from Digital Promise, held listening sessions about Artificial Intelligence (AI). We connected with all constituents involved in making decisions about technology in education, including but not limited to teachers, educational leaders, students, parents, technologists, researchers, and policy makers.

The goal of these listening sessions were to gather input, ideas, and engage in conversations that will help the Department shape a vision for AI policy that is inclusive of cutting-edge research and practices while also informed by the opportunities and risks.

Blog Posts

Need More Info?

Contact ed.tech@ed.gov with questions.

Please Include "OET AI" in the Subject Line

For a print-out and summary of the Artificial Intelligence Initiative, please review our AI One-pager

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Artificial Intelligence - Office of Educational Technology

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OET is working to develop policies and supports focused on the effective, safe, and fair use of AI-enabled educational technology.

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Artificial Intelligence in Education: Our Vision

Digital Promise's vision for artificial intelligence (AI) in education puts people first:

Safe, equitable, and meaningful AI in education uses emerging technologies to improve education by enhancing how we teach and learn. Grounded in inclusive innovation, Digital Promise pursues AI in education to foster a future where every person engages in sustained and impactful experiences of powerful learning that lead to a life of well-being, fulfillment, and economic mobility.

We observe a race to launch AI tools at scale before agreeing on what problems people want to solve, what values educators must protect, and what goals educational systems should be designed to achieve. Shared vision, values, and goals arise from people working together. Our human-centered approach emphasizes how the increasing capabilities of computers can augment human intelligence, enabling people to engage in teaching and learning experiences more deliberately. Working across research, edtech, and practice, Digital Promise:

Builds partnerships among educators, innovators, researchers, and other impacted community members to establish a shared vision of powerful learning in an AI-enabled world

Defines core values including anti-racism and anti-bias and finds ways to hold AI-enabled products accountable

Engages in research partnerships and hosts research communities to investigate how and whether AI can help us to achieve our goals, and

Works with policymakers to safeguard learners' rights, data privacy, and to ensure equitable opportunities to learn.

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Artificial Intelligence in Education - Digital Promise

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Will A.I. Take Your Job - or Make It Better? : The Pulse

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Whether you're a student or a doctor, a plumber or a truck driver, a university lecturer or a radio reporter, artificial intelligence is changing the way we work. For some workers, A.I. is taking over tedious and time-consuming tasks, freeing them up to focus and get more done.

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Is that text written by a human?

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ChatGPT is incredibly popular online, boasting more than 100 million monthly active users within just two months of its launch in November. It took Instagram two and a half years to reach that number.

The program is powered by a language model that is programmed to produce human dialogue. Users can feed it a prompt, and ChatGPT will predict how it should respond.

This makes teachers nervous. Concerns about plagiarism among teachers have motivated the Los Angeles Unified School District and New York City Public Schools to ban its use. Educators are concerned the application will fundamentally change how writing is taught and will impact students' abilities to craft ideas on their own.

Daniel Herman is a teacher at Maybeck High School in the Bay Area. He detailed his concerns in an essay in The Atlantic.

If you're looking for historical analogues, this would be like the printing press, the steam drill, and the light bulb having a baby, and that baby having access to the entire corpus of human knowledge and understanding. My life-and the lives of thousands of other teachers and professors, tutors and administrators-is about to drastically change.

Other teachers are getting creative with the technology. Kelly Gibson, an English teacher in rural Oregon, is having her students analyze essays written by ChatGPT and find ways that they can be improved.

We assemble a panel of guests to discuss the impact of artificial intelligence on our schools. It's part of our series Know It All: 1A and WIRED's Guide to AI.

Senior Digital Producer at Wired Pia Ceres; GPTZero Creator Edward Tian; Professor of Technology and Education at Columbia University's Teachers College Lalitha Vasudevan, and High School Teacher Daniel Herman join us for the conversation.

WIRED also has a newsletter if you want to learn more about how technology is changing our lives. It's called "Fast Forward". It explores the latest advances in AI, as well as other technologies. You can sign up at: wired.com/newsletter.

Like what you hear? Find more of our programs.

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Know It All: ChatGPT In The Classroom : 1A

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ChatGPT is incredibly popular online, boasting more than 100 million monthly active users within just two months of its launch last November.The program is powered by a language model that is programmed to produce human dialogue. Users can feed it a prompt, and ChatGPT will predict how it should respond.

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High schoolers can do...

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With new technology comes new options for employers, some that reduce their need for human workers...

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U.S. employers are using AI to essentially reduce workers to numbers in the workplace

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NPR’s Steve Inskeep talks with Ifeoma Ajunwa, author of The Quantified Worker, about how work lives have become quantified for the benefit of employers.

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The information AI models, like Google Bard, put out is not always correct! Read about AI Halucinations here!

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Not Bard, Google VP also said that the company encourages users to use Google Search for accurate information and references. (Bloomberg)

Not Bard, Google VP also said that the company encourages users to use Google Search for accurate information and references. (Bloomberg)

At a time when conversations around 'hallucinations' of artificial intelligence are becoming increasingly frequent, Google VP and managing director of Google UK, Debbie Weinstein gave a shocking statement in an interview where she said that the company's AI chatbot Google Bard is not meant to be used for accurate information, and that users should instead use Google Search for that. She also highlighted that Google Bard is an 'experiment' and is not meant for specific information.

In an interview with BBC's Today program, Weinstein was responding to the question of AI hallucinations with Google's in-house chatbot Bard. She said, "I would say Bard is used differently from how Google Search is traditionally used. Bard is, first of all, an experiment in how you can collaborate with large language model. It is really for collaboration around problem-solving, ideation, and creating new ideas. It is not really the place you go for specific information".

Google Bard's unreliability issue

Answering another question on the unreliability of Google's AI chatbot and whether the company feels comfortable having a product in the public domain that can give out misleading information, she said, "At the bottom of it, you have the option to give us feedback and give it a thumbs up or thumbs down when it is not delivering for you. We also have a link that says Google It. We know that people count on Google for accurate information and we are encouraging people to actually use Google Search to reference information they found".

Google does in fact give this information. On the homepage of Google Bard, it says, "I have limitations and won't always get it right, but your feedback will help me to improve". However, there is no mention that a user should cross-check the information from Google Search.

AI chatbots: Handle with care?

The issue of AI hallucination is not exclusive to Google Bard. On occasions, both Bing AI and ChatGPT have also given either incorrect or misleading information. The problem appears to be consistent across different LLMs and AI foundational models.

So, is there even a point to use them? The Google VP asserts that it can be a good collaborative tool and can refine your search experience and help in problem-solving and ideation. And that seems to be true to a certain extent. Most chatbots do a decent job of analyzing large chunks of text, help in suggesting improvements in an essay, and have passable performance when it comes to subjective answers such as tips, how-to's, and more.

But for more objective questions, where specific information is needed, you are better off with a search engine, at least that's what the Google VP believes.

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Shocking reason why you need Google Search if you use Google Bard

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Google VP Debbie Weinstein said in an interview that its AI chatbot Google Bard is an "experiment" and "not for specific information", so users should go to Google Search and verify the information as it may not be correct!