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Duolingo, Gamification and Habit Formation

Ashish1 Comment

I got “promoted” on Duolingo recently, and today’s blogpost is about how weirdly happy I feel about it.

I am an incredibly lazy person. We all are to varying degrees, I suppose, but I’m convinced that I do putting off and procrastrination better than most. There are a few things that I do with enthusiasm and something approaching regularity (writing here being one of them) but with most things in life, tomorrow is a better day for me than today.

There is a very short list of things I am compulsively addicted to doing on a daily basis, There’s Wordle, for example. Reading blogs, for another. The NYT mini crossword, and some other stuff. But there is a clear winner on this list: Duolingo.

On Duolingo I have a 753 day streak, and counting. That is, I have practised on the Duolingo app for 753 days and counting. And it’s not because I am awesome at showing up regularly – it is because Duolingo has incentivized me to show up regularly, and here’s how they do it.

First, peer pressure. Duolingo allows you to follow people in your contact list who are also on Duolingo, and it’s a two way street. That is, they can follow you too:

AshishKulk is my user ID on Duolingo, and please feel free to “add” me to your network if you are so inclined. I can always do with more peer pressure! Knowing that my friends are practising more than I am is a great incentive to try and keep up – which, of course, is what peer pressure is all about.

The score-keeping mechanism in Duolingo is XP. The app tells you how much XP you “acquired” on a daily, weekly, monthly and all-time basis.

Each of these frequencies is gamed differently. For the all time streak, you can check where you rank among your friends (I’m third, if you’re wondering). For the monthly score, Duolingo hands out “badges” if you earn a certain number of XP in a month:

For weekly streaks, you get promoted to different “leagues” based on how many points you score on a weekly basis. It is a double edged sword: you also get “demoted” if you don’t practise enough in a week. The leagues start and finish every Sunday afternoon India time, and I’m typing this out on a Sunday morning – wish me luck!

And the daily basis is perhaps the best gamification of them all, because you end up in a contest with yourself. How long can you keep your daily streak going? Like I said, mine is at 750 odd days, and I got “promoted” for it:

There are also daily quests, friend quests, stories involving characters that build a more personalized, relatable learning experience, and recently, learning paths that use spaced repetition to make sure that weaker concepts are revised and firmed up over time. You can “buy” streak freezes to “protect” your streak in the Duolingo store. These artefacts can be “purchased” using “gems”, and that’s yet another gamificaiton story.

Long story short, the Duolingo team goes out of its way to try and keep you hooked on to learning, and I’m here to tell you that it has definitely worked in my case.

And that’s the point of this post, really. I think Duolingo to be an exemplar when it comes to gamification, but the meta-point here is an obvious one: how do we all go about gamifying activities in our life that we wish would turn into habits? How about a Duolingo experience for exercise? Meditation? Learning cooking? Financial habits?

There are those among us who can build out habits in their lives without gamification, of course, and I envy them for it. But for those of us who are paashas of procrastination, such a tool can help us get better at showing up more regularly.

I speak from personal experience when I say this, though: Duolingo has done it better, and been more effective, than any other habit forming app that I have tried.

Now, excuse me while I go and try to stay in the Diamond League!

Lenny’s Newsletter on Reigniting Duolingo’s User Growth

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I’ve written about Duolingo before, and I have no doubt that I will write about it again.

Why? Because I am a very lazy person, and I appreciate all the help I can get when it comes to building good habits. Writing daily on this blog is a good habit – it is, alas, not one that I have perfected yet. Taking my dog out for a walk everyday is a good habit – a necessary one for the dog, and so also for me now. Practicing a language (currently Italian) daily on Duolingo is a good habit, and while I’m not at 1435 days yet, I’m a little more than halfway there, and hey, that’s progress!

Exercising daily is a habit I’ve tried to build and failed at (one day, one day). Eating healthy on a daily basis is a habit I don’t want to build, but eating mostly healthy on a weekly basis is something I’ve more or less succeeded at – and that’s good enough for me. The point is that given that I’m so lazy, building up a habit is the only way to stick at doing something. And anything that helps me enjoy getting into a habit is, to me, a fascinating thing to study.

Which is why I have no doubt I will write about Duolingo again.

Lenny’s newsletter is worth reading in any case, but his latest post is really very, very good. It’s not written by him – this one is a guest post by Jorge Mazal – but that’s all the more reason to read it. If you’re interested in learning about metrics, user retention, driving growth, this article is self-recommending – and that would be a good reason to read it carefully.

But even if you are not interested in any of those things, it still makes sense to read it. My framing of my own incentive while reading it was “Can this article teach me how to gamify my life?”, and from this perspective, it is an eminently readable article.

I had a very interesting conversation with a friend this past Sunday, and his take on habit formation and productivity techniques was that this has perhaps been taken a little bit too far in today’s day and age. I actually agree with him on that point – we try to wring every little bit out of every little hack, to our overall detriment. But that being said, I think it makes sense to take a look at our own lives and ask to what extent we could make our lives a little bit better along dimensions of our choosing. To each one of us goes the right to choose which dimensions, and to each one of us goes the right to choose how to improve our life along those dimensions, and finally, to each one of us goes the right to choose the magnitude of improvements.

But once you’ve answered those questions – which dimensions, how to improve, and to what extent – you could do with help regarding tips and tricks re: Making It Happen. And that’s where this article is worth reading.

My key takeaways:

  1. Gamification matters, and it helps. Try gamifying those aspects of your life that you want to get better at.
  2. A blind CTRL-C CTRL-V of gamification done well elsewhere is a pretty poor way to go about it. Think carefully about which incentives matter to you, and design your gamification strategy accordingly.
  3. These three questions are a good way to frame this:
    Why is this feature working in this product? | Why might this feature succeed or fail in my context? | What changes do I need to make to make this feature succeed for me?
  4. Compounding the benefits of a habit is an excellent, always underrated idea.
  5. We like to win. Set up a competition for yourself, and make sure there are tangible rewards (and punishments!)
  6. Reminders help, but don’t end up irritating yourself out of a habit.
  7. Streaks are a great way to compete with yourself (related to pt. 5), and preserving that which you have is a great motivator (the endowment effect matters)
  8. The social aspect matters – get other people to join you on your journey (hello to all of my friends on Duolingo, and thank you!)

The Economics of ReCAPTCHA

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This has been doing the rounds on my Whatsapp groups recently, and maybe you’ve seen it too:

Mildly funny, but the story behind it is quite something.

Bots have been a problem for many many years – much before Elon Musk thought of buying Twitter. And as long as sixteen years ago, folks were trying to solve the problem of stopping bots from signing up for services. So how does a computer make sure that the entity trying to sign up for a service actually is a human?

Well, by showing images such as these, and asking the entity on the other side to make out what the word is:

We’ve all been subjected to a variant of this, haven’t we.

Now, one of the folks who came up with this system – it’s called Captcha (say it out aloud and you can figure out the reason behind the name) ran the numbers:

And at some point I did a little back of the envelope calculation about how many of these were typed by people around the world, and it turns out the number I came up with was about 200 million.
So about 200 million times a day somebody would type one of these CAPTCHAs, and that’s when I started thinking, “I wonder if we can do something with this time.” Because the thing is each time you type one of these, not only are they annoying but also they waste about ten seconds of your time, and if you multiply ten seconds by 200 million, you get that humanity as a whole is wasting like 500,000 hours every day typing these annoying CAPTCHAs.

https://tim.blog/wp-content/uploads/2018/08/135-luis-von-ahn.pdf

Work that will gladden the heart of any economist. And so the guy who did these back of the envelope calculations tried to figure out how these 500,000 hours might be put to better use. Thus was born reCAPTCHA. And the idea was a very, very good one.

When you digitize, or scan books for the first time, there will be books with old fonts, outdated fonts. And therefore there will be a fair few words that computers will not be able to decipher. And not just books, this is also true of newspaper archives.

So if we have scanned books and newspaper archives that are non-machine-readable, and we have humans spending 500,000 hours every day… what about connecting the two, and having humans read these words, one at a time?

Scanned text is subjected to analysis by two different OCRs. Any word that is deciphered differently by the two OCR programs or that is not in an English dictionary is marked as “suspicious” and converted into a CAPTCHA. The suspicious word is displayed, out of context, sometimes along with a control word already known. If the human types the control word correctly, then the response to the questionable word is accepted as probably valid. If enough users were to correctly type the control word, but incorrectly type the second word which OCR had failed to recognize, then the digital version of documents could end up containing the incorrect word. The identification performed by each OCR program is given a value of 0.5 points, and each interpretation by a human is given a full point. Once a given identification hits 2.5 points, the word is considered valid. Those words that are consistently given a single identity by human judges are later recycled as control words. If the first three guesses match each other but do not match either of the OCRs, they are considered a correct answer, and the word becomes a control word. When six users reject a word before any correct spelling is chosen, the word is discarded as unreadable.

https://en.wikipedia.org/wiki/ReCAPTCHA

The system has evolved since then, and this version of reCAPTCHA (known as reCAPTCHA v1) is no longer around. We now have reCAPTCHA v2 and reCAPTCHA v3, and if you’re curious, you can learn more about it here.

But I really like the idea behind reCAPTCHA v1, even though it is no longer in use. It used the opportunity presented by a necessary but time-consuming activity by matching it with a necessary but money-and-effort-consuming activity, to the benefit of all concerned.

Turns out the person who came up with the idea has been thinking about computers and human brains as being complementary to each other for a fairly long time, even writing a PhD thesis about it:

Von Ahn’s Ph.D. thesis, completed in 2005, was the first publication to use the term “human computation” that he had coined, referring to methods that combine human brainpower with computers to solve problems that neither could solve alone. Von Ahn’s Ph.D. thesis is also the first work on Games With A Purpose, or GWAPs, which are games played by humans that produce useful computation as a side effect. The most famous example is the ESP Game, an online game in which two randomly paired people are simultaneously shown the same picture, with no way to communicate. Each then lists a number of words or phrases that describe the picture within a time limit, and are rewarded with points for a match. This match turns out to be an accurate description of the picture, and can be successfully used in a database for more accurate image search technology. The ESP Game was licensed by Google in the form of the Google Image Labeler, and is used to improve the accuracy of the Google Image Search. Von Ahn’s games brought him further coverage in the mainstream media. His thesis won the Best Doctoral Dissertation Award from Carnegie Mellon University’s School of Computer Science.

https://en.wikipedia.org/wiki/Luis_von_Ahn

There’s an old talk by Louis von Ahn on the topic as well, if you’re interested.

And here’s the kicker: the same idea, human computation, is at work another venture that Louis von Ahn has started. You may have heard of it, it has got this cute little green owl as its mascot:

So the way this works is whenever you’re a just a beginner, we give you very simple sentences. There’s a lot of very simple sentences on the web. We give you very simple sentences along with what each word means. And as you translate them and as you see how other people translate them, you start learning the language. And as you get more advanced, we give you more complex sentences to translate. But at all times, you’re learning by doing.

https://www.ted.com/talks/luis_von_ahn_massive_scale_online_collaboration/transcript?language=en

Both reCAPTCHA v1 and Duolingo have different business models now, of course. But as students of economics, its’s worth appreciating the idea of complementarity between humans and computers, and the idea of turning a necessary but time intensive activity into a socially useful one.

It may be a funny Whatsapp forward, sure, but as it turns out, there’s quite a story behind it. No?

How Might You Use Incentives in Your Own Life?

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It’s all very well to dispense gyaan about incentives, but what is the TMKK?

For those of you new in these parts, TMKK stands for To Main Kya Karoon? Learning about economics for its own sake only make sense in terms of scoring marks in an examination. But a subject truly comes alive when you are able to understand its relevance and importance to your own life – preferably directly, but at the very least tangentially. Don’t get me wrong, I am not at all suggesting that intellectual pursuits for their own sake are not worth it. But I am very much suggesting that the ability to answer a TMKK for oneself makes it much more interesting.

So how should once use incentives in one’s own life?

  1. You can make museum visits less boring.
  2. You can lose weight. I cannot find the reference I’m looking for right now, but Tim Ferriss once spoke about how you can send a truly embarassing pic of yourself to a friend, with instructions to post it on social media by the end of the month – unless a certain amount of weight loss has been achieved. If pics on social media is not your thing, give an amount of money that will truly pinch you to your friend, with instructions to donate it to a cause/political outfit that you truly loathe – again, unless a certain amount of weight loss has been achieved.
  3. What is the Pomodoro technique if not an incentive mechanism? There is more to it, sure, but incentives are certainly involved, no?
  4. If you have a gym buddy, yes, that too is an incentive mechanism. There is another phrase for it – peer pressure. That simply means that it’s not so much about you missing gym, but about the pressure you feel for letting your friend down. But the underlying mechanism? Incentives! In this case, it is a non-monetary, negative incentive.
  5. In my opinion, nobody does gamification using non-monetary incentives better than Duolingo.
  6. Ask ChatGPT3 for more examples! I could have done this myself, of course, but you really should get in the habit of using ChatGPT3 as a tool to do all kinds of research – it’s what you’re going to be doing in your careers in many different ways, so the correct time to get started is yesterday.
  7. Think about examples from your own life where you’ve tried to design incentives for yourself. Ask yourself which ones worked and which ones didn’t, and then ask yourself if we humans treat positive and negative incentives the same way.
  8. Best of all, try designing incentives for somebody in your family. See how they respond to your incentive mechanism, and see if you can iterate it (the mechanism) for the better. If you’re looking for an example – what if you promise to make breakfast in bed for a family member who promises not to look at their phone after dinner throughout the week. Will this work? Try it out! (Note: not a single “I just need to do this one little thing” allowed!). Try the same experiment the next week, but this time, use a “punishment” instead. Say, a fine of a thousand rupees, payable to you, if they break the rule.
  9. If you do “run” the experiment in pt. 8 above, ask yourself if Goodhart’s Law applied.
  10. Get better with every passing week at designing incentives, refining them and implementing them, both for yourself and for others. You’ll be surprised in two regards. First, you’ll be surprised at how easy it is to design better and better incentives. And second, you’ll be surprised to learn that GoodHart’s Law is always applicable. Tricky little beasts, incentives.