Free preview Getting started with generative AI

Welcome to the course!

These three articles will give you a sense of the scope of this course-in-progress. We're so glad you're here! <3

📄 Welcome to the course!

##What is this course?

There are so many exciting developments in the field of artificial intelligence (AI), and the future remains unwritten.

This course is somewhat unwritten, too!

This course is a work-in-progress!

We've partnered with other thought leaders in educational technology—including Code.org, Common Sense Education, aiEDU, and Professors Ethan and Lilach Mollick—to develop a set of resources to help the world better understand some of the ways that generative artificial intelligence can be used to improve human intelligence and learning outcomes.

As our understanding evolves, so will the course.

We'll learn how some educators are beginning to use generative AI technology with their students, we'll answer some questions, make some suggestions, and we'll attempt to explore two overarching questions:

What potential do generative artificial intelligence tools like large language models (LLMs) hold to transform worldwide education for the benefit of humanity?

How can we maximize the benefits of this emerging technology while minimizing its risks?

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AI's potential in education

We believe AI has the potential to usher in a new age of education and revolutionize the way we learn. We believe that by working with AI, humans will be able to more quickly generate ideas to solve problems, brainstorm and create engaging learning experiences, and find exactly what they are looking for on their learning journeys.

Risks and responsibilities

In this course, we also will discuss some of the risks inherent in working with this rapidly evolving technology. For example, the text generated from LLMs should not be taken at face value, but should rather be independently validated whenever possible. This means that human judgment will remain as important as ever, if not more so!

###Evolving our understanding

AI-powered tools are exciting, but they can also be alarming and strange. As we learn more from our learners, teachers, and parents about what they would like to better understand about AI in education, we’ll continue to build out this course so that you can use AI-powered tools with confidence.

###Embracing change

New developments are calling into question what a formal education should include. By becoming more fluent in the variety of ways AI can be used ethically and responsibly, we can more confidently embrace the change it represents.

We are all still learning about these technologies, but join us—let's learn about them together!

📄 AI in five

##AI in 5 minutes

Get ready for the future in just 5 minutes.

###What does AI mean?

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The term “Artificial Intelligence (AI)” has a lot of different meanings depending on who’s talking.

Yeah, AI can mean “smart creepy robots” sometimes. But technology isn’t quite there yet. It turns out “AI” might mean a lot more than you think.

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When computer scientists and politicians talk about "AI", they usually mean the technologies we use every day like FacelD, TikTok's algorithm, and Google search. And sometimes they mean killer robots, unfortunately.

Computers have a lot of clout in your everyday life: they decide what posts to show you, whether you've been out of school too much, and predict whether you might commit a crime.

But what's special about Al compared with other computer programs? Al allows computers to learn from past experience.

###AI learns from experience

Think about how a person becomes a great musician or gets a top rank in a video game. Practice, practice, practice. Al allows a computer to practice making a decision or taking a guess millions and millions of times until it gets good.

Computer scientists use "data" to train an Al. In short, data just means information. What can data look like?

  • Biometrics
  • Numbers
  • Images
  • Audio
  • Text

We can use these types of data to train computers to do almost anything through practice.

Here are some examples!

Data & Practice | Decision/Prediction

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    Faces: The computer analyzes lots of faces and practices telling people apart. [[☃ image 5]] | Face recognition: The computer can learn your face and say, “Yes, that’s you!" [[☃ image 7]]
    Videos: the computer analyzes millions and millions of videos to see what kinds of people like which types of videos. They figure that out by seeing how long people watch each video. [[☃ image 11]] | Recommendations: The computer learns to make a good guess about what videos you'll like the most, and recommends them in your feed or FYP. [[☃ image 15]]
    Text: the computer analyzes some English words and their translation in Spanish, automatically learning which phrases mean what. [[☃ image 19]] | Translation: The computer learns how to translate almost any text you can throw at it from English to Spanish. [[☃ image 21]]

So all that is pretty cool. But computers make a lot of decisions. There are a couple things we might worry about.

Sometimes those decisions go wrong, so how do we stop that from happening?

And if Al learns from past experiences, how do we make sure we don't repeat the mistakes of the past?

Al must be built and used responsibly

Al isn't all-knowing. And that means it can make mistakes, sometimes even really big, uncomfortable ones.

  • AI predicts whether people will commit crimes.

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  • AI has a harder time recognizing the faces of black people compared to white people.

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  • AI can be used to create false or misleading text that spreads incorrect ideas.

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If we know Al can make mistakes, we need to use and build it responsibly. Here's what you can do right now about that:

  1. Tell other people you know about how Al works and how common it is in real life

  2. Write a letter to your school or representative asking them to help spread the word about Al

  3. Check out podcasts, videos, articles, and classes about Al in your life

📄 New tools for a new age: FAQ

Generative AI: a new tool for a new age

Just as the arrival of calculators made educators ponder the future of math education, the appearance of chatbots driven by large language models has prompted some tough questions.

In this article, we’ll try to answer some of the most urgent questions we’re being asked by students, teachers, parents, and school administrators.

FAQ: Students

How can I use this tool in a way that helps me learn?

There are many different ways AI tools can help you learn. Here are a few examples:

  • Get unstuck on a math problem: If you don’t know what to do first, what the next step is, or just want to check if you are thinking the right way, you can interact with the AI to help.
  • Find out how or why something works the way it does: “Why is the sky blue?” "How does a radio work?" You may not be able to explain, but an AI tool can help you find the information and engage you in a fascinating conversation.
  • Ask it to simplify a confusing concept, and then quiz you on it: With a little practice with your prompting, you can start using an AI-powered chatbot to prepare you for a test.
  • Ask it to brainstorm activities to help you learn: LLMs can provide great ideas for making learning fun and relevant—just ask.

How do I know if what the tool produces is right or wrong?

This is a very important question because AI-powered tools can be wrong. They sometimes make up facts—AI developers call these falsehoods “hallucinations.” They sometimes give wrong math answers and might even tell you your answer is right when it isn’t. How should you deal with this?

  • Never trust that the answer the tool gives you is 100% accurate: Don’t rely on it to give you answers when it is really important for you to be right.

  • Trust your instincts: If you’re saying to yourself, “that doesn’t seem right,” it may not be! It is easy to convince yourself the AI must be right and you must be wrong. Instead, investigate further.

  • Consult other sources: It’s usually a good idea when learning new things to do this anyway, but it’s especially important when learning with AI-based tools. Think like a fact checker. What are the most essential facts to verify? Where else could you verify information?

  • Remember some places the tools are more likely to hallucinate: They won’t know information about current events because they take time to train and are not always up-to-date. As language models, they aren’t always experts at math. They aren’t always able to link to other web sources unless the specific site feeds them.

FAQ: Teachers

Are there ways this can make my job easier?

What are the planning tasks that take you the longest? Could an AI-powered tool that is really good at summarizing and writing help you?

Here are a few ideas to get your creative juices flowing:

  • Generate ideas for lesson hooks: Need an engaging introductory question, or a quick activity to grab attention and spark your students’ curiosity? Ask the bot for some ideas.
  • Compile ideas for hands-on classroom activities: AI-powered tools are incredible idea generators. You won’t like all of their ideas, but it can be fun to pick and choose the ones that are the best match for your classroom, and improve them with your imagination, insight, and expertise.
  • Generate feedback and suggestions for improvement on drafts of student writing: This use case might sound controversial, but it doesn’t have to be. Any feedback the tool offers is yours to consider. You can keep it to yourself, or review and revise it before sending it to the student.

Is there something about interacting with these models that is likely to help my students learn more?

We don’t know yet, but we have some hypotheses that we're testing based on what we already know about how people learn.

Perhaps the biggest potential learning benefit to this technology may be the personalized, differentiated, tutor-like interactions it can generate. With so many different levels of learning in your classroom, you know how difficult it is to reach all students at their level. There are too many students and not enough of you.

Here are some ways AI-powered tools might be able to help:

  • Get your students unstuck: You simply can’t be next to every student as they're working on questions and answering problems. This type of technology can help coach students through a question.

  • Enable deeper conversations: You likely have engaging, deep discussions in your classroom, but does every student participate? With AI tools, each student can engage with deeper questions (How? Why? What if?) and respond and be encouraged and validated.

  • Help your students see relevance, which we know increases motivation: How many times have you been asked, “When will we need to know this?” AI tools can help your students make those personalized connections.

  • Improve student writing by providing feedback on drafts: What will AI’s role be in the future of writing instruction? What writing skills do students really need in an AI Age? These are provocative open questions—we don’t know the answer, but there is much room for experimentation.

What are the implications of these models for academic honesty?

This is definitely a hot topic for academic communities, and each community is developing answers that make the most sense for them. Given that a core principle of academic honesty is to present proper authorship of work, there are a number of paths we are seeing emerge:

  • You can forbid all use of these models: Since might sound straightforward, but then you have to figure out a way to detect when AI is being used. This will become exceedingly difficult as the models become more advanced. Our view is that detection technologies won't be able to keep up.
  • You can allow use of the models but require students to acknowledge their use: In addition, you could ask students to document each prompt they crafted and/or describe how they used the AI tool, then reflect on that experience.
  • You can design assignments that are difficult or impossible to use these tools with: For example: Assignments that rely heavily on in-class discussions or activities of which the model would have no knowledge.
  • You can have students complete assignments in class where you can monitor what tools are used

FAQ: Administrators

How can I understand what these models do?

The best way to understand what large language models do is probably to start by interacting with one, through interfaces like OpenAI’s ChatGPT or Microsoft’s Bing. After you get a better sense of “the What”, you can learn more in this course about how they might apply to education in your community. You can also ask the AI tool itself to explain what it is and how it works.

What are the implications of these models for academic honesty? How should I think about setting policies for the use of these models?

Here’s some great advice from our friends at Montclair State University’s Office for Faculty Excellence:

“Most students who engage in academic dishonesty are doing so impulsively or without reflection. Anticipate this human behavior and engage students in an open discussion about academic dishonesty.”

For a quick update to your anti-plagiarism policies, consider adding a clarifying statement, such as

“Use of an AI text generator when an assignment does not explicitly call or allow for it without proper attribution or authorization is plagiarism.”

We encourage you to engage your numerous stakeholders (parents, teachers, students, school committee) in an open conversation about their questions, concerns, and approaches.

FAQ: Parents

How can I understand what these models do?

This course will give you a pretty good overview, and you can read about large language models elsewhere, but it may remain fairly abstract until you actually interact with one yourself. Models like OpenAI’s ChatGPT, Google’s Bard, and Microsoft’s Bing are being guided by different commands (“prompts”) behind the scenes, so we recommend trying a couple of them out before reading more about how they work.

How can I control or monitor how my child interacts with AI-powered tools?

It is important to know that LLM-based chatbots like ChatGPT are available for use to the public. Monitoring your child’s use of them is dependent on how you monitor your child’s use of the internet or technology generally, and we encourage you to read beyond this course for advice on age-appropriate ways to guide responsible technology use for your child.

Ask other parents, your children's teachers, or school administration to develop a strategy and communicate it out to the school community. We know how hard it can be to keep up, but you're not alone!

How can I guide my child to use these models responsibly?

You should think about using these models responsibly in the same ways you guide your children to use the internet and other technologies. Teach them the WHYs and the HOWs of what responsible use looks like. Guidelines might include:

  • Avoid conversations with it that might be categorized as hate, violence, or sexual in nature
  • Acknowledge using it to help with drafts or feedback on schoolwork
  • Ask their teachers what their policies are about using it, and then comply with the policy

You can also start to help your child learn how the tools can serve as helpful collaborators. To get started, you might try using it to write a story together, or ask it to answer questions your child has about the world and how it works, and then discuss the answers.

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