Positron for Babies: Communicating Technical Concepts to all Audiences (Ryan Johnson)
Positron for Babies: Communicating Technical Concepts to all Audiences Speaker(s): Ryan Johnson Abstract: Data science is full of complex topics—Bayesian statistics, neural networks, databases, and more. Now, imagine teaching one of these to a baby. What would you say? How would you say it? This exercise highlights the power of simplification: anyone can teach, and anyone can learn. Breaking down complexity makes data science accessible, impactful, and fosters greater creativity and flexibility. In this talk, I’ll share my approach to simplifying data science education with a playful demonstration using Posit’s new IDE, Positron, as the focus! posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
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Transcript#
This transcript was generated automatically and may contain errors.
Welcome, everybody. As Max mentioned, my title is Positron for Babies.
So if anyone else here in the audience has small children, then maybe you've heard of this book series, For Babies. This particular book, I actually brought it with me right here, it's called Quantum Computing for Babies, if you want to check it out.
And I read this all the time to my almost two-year-old daughter. She loves it. It has really simple, fun visualizations inside of it. But it turns out, I actually really like this book too.
And I'm not a baby. Because it takes this extremely advanced topic of quantum computing, and it breaks it down so essentially anyone can understand it, which I think is so cool.
So, assuming many of you are not quantum computing experts, I want to take two minutes and teach you about quantum computing as if every single one of you is a baby.
Quantum computing for babies
This is a ball. It can be red or blue. It is one bit of information. Eight bits makes a byte. Many bytes makes data. Data lives in a computer. Computers are useful. They solve problems. Problems are solved by changing data. Some problems are easy. Some problems are hard. Some problems are too hard for a computer using bits. But wait. What is this down here? It's a quantum bit. A qubit. It can be red or blue or anything at all. Many qubits makes quantum data. Quantum data lives in a quantum computer. Data cannot be copied. Or data can be copied. Quantum data cannot be copied. And we can watch a computer at work, but we cannot watch a quantum computer at work. We can only see the answer it gives. So, why do we want a quantum computer? Because quantum computers can solve hard problems. Now you know quantum computing.
Now, do I really expect every single one here in the audience to now be an expert on quantum computing? Of course not. That was never the goal of this book. But did you learn something new about quantum computing? Or at least have a pretty high level understanding of what goes into quantum computing? And that is the ultimate goal.
Three techniques for simplifying complex topics
Now, using this book as an example, I started thinking about how I might explain POSIT's new IDE, Positron, to somebody else. How might I explain it to one of my colleagues that works at POSIT? How would I explain it to one of you in the audience, other data science enthusiasts? How might I explain it to my uncle at the Thanksgiving dinner table? And how would I teach it to my 2-year-old daughter?
So, the book that we just read did some really great techniques for breaking down advanced topics so that, again, anyone can understand them. And we're going to talk about three of those techniques today. The first one is called laddering. Then we'll talk about avoiding jargon. And lastly, using metaphors. So, let's start with laddering.
What is it? The whole idea behind laddering is that you, the keeper of this knowledge, is that you know this topic and you're trying to present to an audience or a person that doesn't know this topic. So, they start at the bottom of this ladder. And it is also your job as the presenter to give that learner a little bit more knowledge, a little bit more knowledge, until eventually they know the topic.
Now, in the book that we read previously, here's a really simple example of how laddering was used. We had this advanced topic, not advanced to all of you, but for someone else that's not in the data science field of data. What is data? And this ladder, it started at the very bottom with something we can all relate to. A red ball. We were then told that this ball could actually be red or blue. It's one bit of information. We were then told that eight bits makes a byte and that many bytes makes data. This is a very simple ladder, but again, a very effective way of teaching advanced topics.
Now, let's run through, like, a hypothetical situation. Let's imagine you take this ladder, which breaks down these advanced topics, and you just rip out all the middle runs. Now, just like a real ladder, if I was propping this up against my house and trying to get to my roof, this ladder would be not very fun to climb. It requires a pretty large physical strain.
But what would the book that we read at the very beginning, this quantum computing book, what would it look like if we actually ripped out all the middle rungs? Maybe something like this. We have a cover. The first page is literally just the formal definition of quantum computing, and then you get that nice, happy congratulations. You now know about quantum computing at the very end. This book, it does its job. It teaches you about quantum computing, but it now requires a huge mental strain to get there. And again, it is your job to add these individual rungs to make it easier.
So let's talk about Positron. So this is a snippet from the Positron website. At the very top, it will say, what is Positron, with three bullet points. And if we just focus in on the first bullet point, Positron is a free next-generation data science IDE built by PositPBC. And if we just focus in on the acronym IDE. Again, you all know likely what an IDE is, but most folks not in data science or software engineering probably don't.
So how could we explain IDE using laddering? What I personally like to do when I'm doing my laddering technique is actually start at the top and work my way down. So at the very top of my ladder, this is the goal. I want people to learn and know what an IDE is. So what can we do first? Let's just define it. IDEs are tools that make writing code easy. But what did we do here? We actually, by defining it, introduced another piece of advanced jargon of writing code. Not everyone knows what code is. So what do we do? We can define it. Code is text written in a programming language. But we did it again. What's a programming language? Let's define it. A programming language allows humans to give computers instructions. And this is the perfect starting point. Because for the most part, people are going to know what a computer is. And then we can gradually build up that ladder until we all know what an IDE is.
Avoiding jargon
All right. So that's the first technique. We're going to move on to the second one here. And this is called avoiding jargon. Now, this is a clip from a TV show. One of my favorite TV shows. And we have two of the main actors in the kitchen. We have a son and a mother. And they're cooking something. And part of the recipe requires them to fold in the cheese. Now, if you're not in the culinary field or you don't do a lot of cooking, you might not know what it means to fold in the cheese. And if someone explains it to you as, well, you just fold it in. That's not particularly helpful.
So if at all possible, you want to try to avoid using technical terms, jargon that most folks are not going to understand. But also in our field of data science, sometimes it's unavoidable. And I'm not going to stand up here and say don't use jargon. And in fact, the kids book that we read previously has jargon in it. All right? Qubit, byte, quantum computer. These are all topics, jargon, that most folks don't understand. But what did this book do that was super helpful? It didn't just throw all this jargon at you at the very beginning. It gradually introduced these pieces of jargon at the right time when you had enough context to understand it.
So if you need to use jargon, it is, again, your role to provide enough context so people understand the jargon. And if you need to use it at the very beginning, you simply need to define it.
Now, going back to Positron, now focusing in on just the second bullet point. Positron is an extensible polyglot tool for writing code and exploring data. Now, again, just focusing in on one word there. Polyglot. If you're not in the data science field and you don't know what Positron is, and I told you that Positron is polyglot, you might say to yourself, that's awesome. It can speak French and Spanish and other languages. And as many of you all know, that is not the case. We haven't given this enough context to understand what polyglot means here.
So how can we explain it? Well, we can actually use the laddering technique we talked about previously. Starting at the bottom by defining what a programming language is, that can be a great starting point because we all know it is a way to give computers instructions. And just like people speak actual multiple languages, like Spanish and French and other languages, we can say that people speak multiple programming languages, like R and Python. And then right before you introduce Positron, you just squeeze in the term polyglot here, saying, you know, polyglot IDE, it is a tool that can use both R and Python.
Using metaphors
Now, the last technique we're going to talk about is using metaphors. And I'm actually going to stick with the same clip from that show in the last technique. So if I was to try to explain to you all what does folding in the cheese mean, and if I told you it's similar to replanting a bonsai tree, that's not a particularly helpful metaphor unless you've actually replanted a bonsai tree, in which case that metaphor was designed for you. But for most folks, they're not going to have done this. So this is a poor metaphor because it's a very specific topic to relate to.
So if you're ever struggling to explain an advanced topic and you need like a fallback for something to compare it to, I'm going to give you five great fallbacks. Compare it to the weather. Compare it to exercise. Transportation, food, and tools. These are five things that are great fallbacks because, again, most folks are going to have some high-level understanding of these topics and are perfect for metaphors.
So let's go back to Positron. We now know that Positron is a polyglot IDE. How can we use a metaphor to explain this to someone who's potentially not in the data science field? We're going to use tools for this metaphor here. So I might explain polyglot IDE, Positron, and compare it to maybe a fork. A fork is a really great tool that's used to consume certain types of food, like steak. But there's other tools, like a spoon, which is great for consuming other types of food, like soup. But wouldn't it be really great to have just one multi-food utensil that can be used to consume both food and steak and soup? Does anyone know what this is going to be called? The spork, exactly. So in a lot of ways, Positron, which is a multilingual tool, is kind of like a spork. That's multi-food, designed for eating. Positron is designed for data science.
So in a lot of ways, Positron, which is a multilingual tool, is kind of like a spork. That's multi-food, designed for eating. Positron is designed for data science.
Positron for babies
Okay. So with all those various techniques in mind, I'm going to read you all now another children's book, which was authored by yours truly and will certainly not be published anytime soon. And it is called Positron for Babies. As I go through it, just take note of the various times where I leverage laddering, avoiding jargon, and using metaphors. So let's go ahead and teach you all Positron, again, as if all of you are babies.
This is a fork. People use forks to eat food. This is a spoon. People also use spoons to eat food. A fork is better at eating some food, like steak, and a spoon is better at eating other food, like soup. Wouldn't it be nice to have just one utensil to eat all types of food? And if you combine the bowl of a spoon and the prongs of a fork, you get, again, the spork. The spork is an amazing multi-food utensil designed specifically for eating.
But did you know there is another new tool similar to the spork? And it's the perfect tool for data scientists. But what is a data scientist? Data scientists create insights from data. Look how pretty that chart is. To create insights, data scientists speak a language that computers can understand. This is called a programming language. And just like different languages that people speak, like French and Spanish, data scientists can speak different programming languages, like R and Python. Some data scientists prefer R. Some data scientists prefer Python. Data scientists use tools to speak a programming language. They are called integrated development environments, or IDEs. Some IDEs are multilingual and can be used for R and Python. And other IDEs are good for working with data and creating insights. But wouldn't it be really nice to have just one multilingual IDE for data science? That's what Positron is. Positron is an amazing multilingual IDE designed specifically for data science. Now you know about Positron. My beautiful book.
And again, my goal is just the next time that you have to present to an audience like I am, or just present to a family member or a coworker some advanced topic, that you just keep these techniques in mind.
Now, again, my goal for today's session... My goal is just the next time that you have to present to an audience like I am, or just present to a family member or a coworker some advanced topic, that you just keep these techniques in mind. And I truly believe that there is no topic that's too advanced that you can't explain it to someone else. And again, that person could be a colleague, it could be my two-year-old daughter. Thank you.
I truly believe that there is no topic that's too advanced that you can't explain it to someone else.
Q&A
I think we have plenty of time for questions. So we'll give it a second. And please put in and or upvote any questions.
So here's one for Positron. How do you know what level of background knowledge you can assume for the documentation readers?
For the documentation readers. So I guess I will say I don't write the Positron documentation, so I can't necessarily speak for the ones who do. But even when I'm presenting to anyone, like most of my day at Posit is giving demos, workshops, webinars. And I never assume that someone has ever used the tool or technique that I'm presenting on. That is just my belief. I get a lot of people like, hey, can you do some more advanced presentations, advanced topics? And I'm happy to do that, but I never want to exclude folks. So you definitely have to come to it with the mentality that just can't assume any prior knowledge or any prior understanding that that person or that group of individuals has leveraged that tool before. So this is kind of my two cents.
What does fold in the cheese really mean?
I'm so glad you asked. I actually have no idea what it means to fold in the cheese. I think, and anyone who's done it before, it just means add the cheese slowly? Is that generally? Well, I mean, I know you just fold it in, but I know that's not particularly helpful.
Okay, so instead of stirring, you just kind of like pass. So it's not like folding a towel. Or replanting a bonsai tree. That's good to know. Okay. Please send in some Slido questions.
Let's see. Now they're moving around. Do you think these concepts are useful for more in-depth documentation as well?
Do I think these concepts are useful for more in-depth documentation? I mean, I think hopefully the obvious answer there is yes. If you have advanced documentation, Positron is a relatively advanced tool. I'm not saying my two-year-old daughter should be able to go to the Positron documentation and understand what Positron is, but it certainly needs to be welcoming to anyone who's found themselves using Positron and wants to learn more about it. So it's never good to just dive right into the jargon, super advanced topics, and just expect people to have to learn these topics themselves. Like go out and learn all the various kind of extraneous or context, so to speak, to understand that. So again, there's no topic that's too advanced that people can't understand it, and I think that's a good practice to go into that mentality when creating complex documentation.
Let's do the last one. Do you think these techniques would be helpful for writing better vignettes? Oh yeah, absolutely. Yeah, I mean it's a similar question to like the complex or the documentation. A lot of times when, especially in like the RStudio world with packages, it's always been great for creating these vignettes to help you understand how to use a package and the various functions inside of it. Certainly approaching a very similar mentality of making sure it's not too complex, or you're just not diving straight off the deep end into the various topic you're trying to explain. Keeping it simple, keeping it so everyone can understand it. Yeah, certainly a best practice there. Excellent. All right, let's thank Brian once again. Awesome, thank you everybody.
