Vox

Leitura de 17 min

The Einstellung Effect

Summary

In this episode of Developer Tea, host Jonathan Cottrell explores the Einstellung effect, a cognitive bias identified in psychological studies from the 1940s. The effect describes our tendency to apply previously successful solutions to new problems, even when simpler or more efficient alternatives exist. Cottrell explains the original experiment involving water jugs, where participants often used a complex method learned from an earlier problem to solve subsequent ones, missing more straightforward approaches.

Cottrell details key findings from the research: the effect worsens with age, as older individuals become more set in their ways, while younger people remain more adaptable. Interestingly, the ability to rebound from the effect—recognizing and correcting for it—peaks around age 21. Intelligence (IQ) does not influence susceptibility; anyone can fall prey to it. Time constraints and stress exacerbate the tendency, a particularly relevant point for developers working under deadlines.

The episode emphasizes that the Einstellung effect isn’t about avoiding reusable solutions altogether, but about cultivating a mindset that treats each problem as fundamentally new, evaluating the best approach rather than defaulting to past patterns. Cottrell shares a practical intervention from the study: a simple written reminder, “don’t be blind,” significantly improved participants’ ability to overcome the bias. He encourages listeners to create their own systematic reminders to approach problems with fresh eyes, ultimately conserving mental energy and arriving at better solutions.

Topic Timeline

  • 00:00:00 — Introduction to the Einstellung effect and its origin — Jonathan Cottrell introduces the episode’s topic: the Einstellung effect, a cognitive bias studied in the 1940s by Abraham Luchin. He explains the study aimed to understand how solving one problem affects the approach to subsequent problems.
  • 00:01:11 — Description of Luchin’s water jug experiment — Cottrell describes the methodology of Luchin’s study, where participants used three jugs of different capacities to measure out a target amount. He illustrates how participants often reused a complex method from a prior problem, missing a simpler solution available in the new context.
  • 00:02:16 — Defining the Einstellung effect and its mechanism — The host defines the Einstellung effect, from the German word for ‘attitude,’ as the mind’s tendency to reuse old solutions for new, similar-looking problems without evaluating if they are the most efficient. This mental shortcut can lead to suboptimal resource use.
  • 00:03:41 — How the effect changes with age and other factors — Cottrell discusses findings that susceptibility to the Einstellung effect increases with age but is not linked to IQ. He notes that time pressure and stress make people even more likely to default to previous solutions, a critical point for developers working under deadlines.
  • 00:09:19 — Applying the concept to software development and problem-solving — After a sponsor break, Cottrell clarifies that the episode isn’t about abandoning proven tools but about cultivating better thinking behaviors. He warns against blindly applying past solutions (like learning a new framework for every problem) and encourages treating each problem as fundamentally new to manage resources better.
  • 00:12:21 — The simple intervention that counteracts the effect — Cottrell reveals the one intervention from Luchin’s study that improved recovery from the Einstellung effect: writing ‘don’t be blind’ on the problem sheet. This simple reminder prompted participants to think more critically. He suggests listeners use this episode or create their own systematic reminders to approach problems with fresh perspective.

Episode Info

  • Podcast: Developer Tea
  • Author: Jonathan Cutrell
  • Category: Technology Business Careers Society & Culture
  • Published: 2017-02-01T13:42:00Z
  • Duration: 00:15:31

References

Podcast Info

Transcript

[00:00:00] Hey everyone and welcome to Developer Tea. My name is Jonathan Cottrell and in today’s

[00:00:07] episode we’re talking about the Einstellung effect. If you’ve never heard of the Einstellung

[00:00:12] effect, don’t worry, you’re probably in the majority. Most people are not sitting around

[00:00:18] reading Wikipedia articles about these cognitive studies that were done decades ago. But this

[00:00:24] particular study was done back in the 40s by a scientist named Abraham Luchen. And I

[00:00:31] hope I’m saying that correctly. It’s either Luchen or Luchen. We’re going to go with Luchen.

[00:00:35] But Abraham Luchen did this study to understand how people solve problems and not just how

[00:00:42] they solve one problem, but how they solve multiple problems and how the preceding problems

[00:00:49] affect the way that they solve the following problems.

[00:00:53] So the study was intended to understand the effects of solving one problem and then

[00:01:00] solving a next problem. How did that first problem’s solution affect the way you solved

[00:01:06] the second problem? Now there were some very interesting findings. The way that the study

[00:01:11] was conducted was they gave the participants three jugs, three jugs of water or jugs that

[00:01:19] hold water. And each of those jugs hold a different amount of water.

[00:01:23] That amount was labeled on the jug. And they would have to use those jugs in order to arrive

[00:01:30] at a particular amount in the largest jug. So let’s say, for example, and these numbers are

[00:01:36] not correct, but let’s say that they had one jug that had three ounces, one jug that had seven

[00:01:41] ounces, and one jug that had 12 ounces. And their job was to end up with 10 ounces in the 12-ounce

[00:01:49] jug. So the participants experienced a lot of difficulty in solving the problem. And they

[00:01:53] had a series of these same, of these similar types of problems where you have to end up with

[00:01:58] a particular amount in the jug. Now the Einstellung effect is named after the German, the German word

[00:02:06] Einstellung, which means attitude or predisposition, right? So what Luchin found in his study was that

[00:02:16] the way that people solved the first problem, okay, the actual solution to the first problem,

[00:02:23] very often was used to solve the second problem. This is a very interesting finding. Basically,

[00:02:32] what he found was that participants, they had the ability with the jars that they had in hand

[00:02:39] to solve a second problem with much simpler procedure, right? In other words, much less

[00:02:46] work. But because they already had in their minds the solution to a previous problem,

[00:02:53] they had already found the same number that they’re looking for in problem number two,

[00:02:58] they had run across that number in problem number one, their minds kind of short-circuited

[00:03:04] to that solution, even though it wasn’t the most efficient solution. It wasn’t the best

[00:03:10] solution to the problem, given the resources available. So the Einstellung effect is really

[00:03:17] a label for our mind’s tendency to reuse the same solution over and over again. And so,

[00:03:22] the Einstellung effect is really a label for our mind’s tendency to reuse the same solution over and over again.

[00:03:23] solutions that we’ve used in the past on similar problems in the future without evaluating whether

[00:03:30] or not those solutions are the most efficient or the best solutions for that matter. Now,

[00:03:36] there’s even more interesting findings that go along with Luchin’s study. One of them,

[00:03:41] for example, is that this worsens with age. This is something we’ve talked about

[00:03:46] on the show before. It’s just more evidence to show that our minds become kind of set in

[00:03:52] their ways as we get older, right? When we’re very young, we are much more in learning mode,

[00:03:59] and our minds haven’t learned how to overly optimize what we’re trying to solve, right? So

[00:04:05] we’re evaluating all the time. We’re re-evaluating, re-evaluating the problems

[00:04:10] that we’re faced with, and we aren’t reusing solutions as much because we’re still in that

[00:04:15] evaluation mode. And what Luchin’s study showed was that as people were, as people

[00:04:22] aged, the older they became, the more likely they were to fall prey to the Einstellung effect,

[00:04:29] right? So in other words, younger children were much less likely to fall prey to the

[00:04:34] Einstellung effect. Now, there’s another very interesting finding from Luchin’s study.

[00:04:39] He found that people are able to rebound from the Einstellung effect, and perhaps most

[00:04:46] importantly, that the highest ability to rebound is found in people aged about,

[00:04:52] 21 years old. In other words, once you recognize that you have reused a solution that wasn’t

[00:05:00] optimum, then the next problem that you face, you are much more likely to actually rebound and

[00:05:07] create a novel solution for that problem, rather than once again using a previously found

[00:05:14] solution. And this likelihood to rebound is greatest around the age of 21. Now, you may be

[00:05:22] thinking, well, I’m too smart to fall prey to the Einstellung effect. Well, they did this study

[00:05:28] and eliminated differences between IQ as a statistical differentiator. In other words,

[00:05:36] your IQ level, your measured IQ doesn’t change how susceptible you are to the Einstellung effect.

[00:05:46] One final interesting thing that I want to point out about Luchin’s study, when people were,

[00:05:52] for example, constrained to a certain amount of time. In other words, when they weren’t given

[00:05:56] an unlimited amount of time to solve the water jar problems, they were even more susceptible

[00:06:03] to the Einstellung effect. Now, all of us know that this has great implications for the type

[00:06:09] of work that we do, because most of us, if not all of us, are probably under some kind of time

[00:06:16] constraint, right? We don’t have an endless amount of time to deliver the code that we’re working on.

[00:06:22] We don’t have an endless amount of time to deliver features or to fix bugs, usually. More often than

[00:06:28] not, we are time constrained in one way or another. So with the added dimension of stress,

[00:06:35] we are even more likely to fall susceptible to the Einstellung effect. And why is this such a

[00:06:40] problem? We’re going to talk about that after a quick sponsor break. And we’re also going to share

[00:06:45] the one thing that actually made a difference, a positive difference in Luchin’s studies. The one

[00:06:52] that actually kind of gave an uptick in people who were responding and rebounding from the

[00:06:58] Einstellung effect. We’re going to talk about that right after our quick sponsor break.

[00:07:02] Today’s sponsor is a very familiar sponsor to the show, Linode. Linode is such a great product

[00:07:10] because it’s built on a very simple platform. And it’s one that you’ve used whether or not you know

[00:07:16] it. Most of the web is arguably powered by Linux. And the simplicity of it is that it’s built on a

[00:07:22] of Linux is mirrored by the simplicity of Linode. You can get a Linux box up and running in the

[00:07:28] cloud in under a minute. This gives you the power of networked Linux. And it’s only $10 a month for

[00:07:36] their introductory plan, which gets you, by the way, a very powerful box. It’s not like you’re

[00:07:42] buying a crippled box. It’s a two gigabytes of RAM worth of a box. And it runs on an Intel E5

[00:07:50] processor stack.

[00:07:52] It also runs on an internal network that is 40 gigabits, which means it’s super fast. If you ever

[00:07:58] networked two Linux boxes together, they’re going to be talking to each other very quickly. So

[00:08:04] that latency is not going to be an issue if you end up running a networked system of servers,

[00:08:10] which of course you can do because Linux is incredibly flexible. You can do anything that

[00:08:15] you can do with Linux. You can do on Linode. Once again, their monthly plan starts at $10 a month.

[00:08:21] They do have

[00:08:22] caps on all of their plans. They have long view, tons of great features. You can go and check out

[00:08:27] more about what Linode has to offer to you at spec.fm slash Linode. Now here’s another very

[00:08:33] important thing. One more thing I forgot to mention here is that all of these servers are

[00:08:37] running on SSDs, by the way. So you have solid state, very fast servers for just $10 a month.

[00:08:44] But if you use the special code developer T2017 at checkout, you’re going to get $20 worth of credit.

[00:08:52] That’s two months effectively for totally for free just for using the code developer T2017. That’s

[00:08:58] two zero one seven. Go to spec.fm slash Linode to learn more about what Linode has to offer

[00:09:04] to you so you can start solving problems that really require your brainpower like we’re talking

[00:09:12] about in today’s episode, the Einstellung effect. So we’ve already explained kind of what it is.

[00:09:19] We have a tendency, a measurable tendency,

[00:09:22] that gets worse as we get older. We have a measurable tendency to solve problems that

[00:09:28] look similar the same ways, right? So as a developer, hopefully you’ve identified in

[00:09:34] your mind at least 20 different things that look very similar that you’ve used the same solutions

[00:09:39] for. Now, I want to make sure that you’re hearing me correctly. There are many problems that can be

[00:09:46] solved by very similar solutions, right? What we’re not saying,

[00:09:52] in this episode, is that you need to use a new tool every single time you solve a problem that

[00:09:59] is similar to one that you’ve solved in the past. There are different classes of solutions to

[00:10:04] problems, and you shouldn’t view this episode as an excuse to go out and try a new tool every

[00:10:10] single time you encounter a new problem. That’s not the point of today’s episode. Instead,

[00:10:15] we’re talking about thinking behaviors, right? We’re talking about the way your mind approaches

[00:10:21] fundamentalism.

[00:10:22] Fundamentally new problems. And really what we’re talking about is the conservation of resources

[00:10:28] during the solution process, right? In other words, in the Einstellung effect, the thing that

[00:10:36] is lost isn’t the actual solution being correct or incorrect. It’s how much work did it take to

[00:10:42] get there? How much harder is it to get to the problem’s best solution if we use the same thing

[00:10:51] we’ve used in the past?

[00:10:52] So, an example of the Einstellung effect could be that you learned a new framework in order to solve

[00:10:59] a previous problem. So, in order to solve this problem, you will learn another new framework.

[00:11:06] This is an example of using extra resources where it’s not necessarily the best place to

[00:11:12] use those resources, right? Just because learning a framework previously opened you up to the

[00:11:19] correct solution doesn’t mean that learning a framework is not the best place to use it.

[00:11:22] The same thing is true if you want to, for example, get a raise, right? Let’s say that you’re

[00:11:33] seeking a raise in your job. And the last time you got a raise, you did X, Y, and Z. If you do X, Y,

[00:11:41] and Z again, that doesn’t mean that you’re going to get a raise again, right? The situation is

[00:11:46] different. The problem is different. And you should look at it from a new, a brand new perspective.

[00:11:52] This is why this is such an important thing to understand. Our minds have a tendency to think

[00:11:57] that all things being equal, we can treat our problems very systematically. And usually,

[00:12:03] we’re going to fail at some really important piece of this, in particular, spending too much

[00:12:10] resources or arriving at the problem after a very long detour around a previous solution.

[00:12:17] So, I told you that one thing did make a difference in Luton’s study,

[00:12:21] and hopefully, that’s what this episode is going to act as for you today. Luton wrote the words,

[00:12:29] don’t be blind, on some of the participants’ secondary and tertiary problems, right? And

[00:12:36] for those people who he wrote the words, don’t be blind, at the top of their paper that had the

[00:12:43] problems outlined on the paper, for those people that he wrote that message to, he saw a significantly

[00:12:51] better recovery rate from the Einstein lung effect. In other words, people who saw a simple

[00:12:58] reminder, don’t be blind, people who saw a simple message reminding them to think a little bit

[00:13:04] harder about this problem, when they saw that, they actually did that. So, let this episode be

[00:13:11] that reminder for you today, but in the future, you’re not going to have this episode to listen

[00:13:16] to unless you go back and remind yourself of the Einstein lung effect by re-listening to this

[00:13:21] episode in the future. So, I hope you enjoyed this episode. I hope you enjoyed it. I hope you

[00:13:21] that’s perfectly fine as well, but you may need to set up some sort of systematic way to remind

[00:13:30] yourself when you go into problem-solving mode, when you encounter a new problem. This should

[00:13:35] become a habit to remind yourself very simply to treat this problem as a fundamentally new problem.

[00:13:43] Treat this as a new class of problems. Very often, what you will find is that even though

[00:13:49] your solution may look similar, you’re not going to be able to solve it. You’re not going to be

[00:13:51] to a solution in the past. You’re going to arrive at that solution with much better resource

[00:13:58] management. In other words, you’re going to use less energy by simply using more of your brain

[00:14:06] earlier in that process. Hopefully, this has been an enlightening discussion on the Einstein lung

[00:14:13] effect. I was lucky enough to receive a tip on the Einstein lung effect from a listener. If you

[00:14:19] want to send me something that you’d like to hear about, please do so in the comments section below.

[00:14:21] If you want to send a question, just an idea, or a story, I love getting all of your stories.

[00:14:28] You can send those to me by going to spec.fm slash slack. You can join our Slack community.

[00:14:33] You can also send them to me directly at developertea at gmail.com. That email address

[00:14:41] has questions from hundreds of listeners at this point. I’m so excited to connect with you all on

[00:14:47] a personal level. I’m very excited to get your stories and your questions.

[00:14:51] Thank you so much for listening to today’s episode of Developer Tea.

[00:14:54] Don’t forget, if you are looking for a cloud Linux solution, a solid state drive in the cloud

[00:15:02] with two gigabytes of RAM for only 20 for free in credit,

[00:15:10] just for being a Developer Tea listener, use the code developertea2017 at checkout.

[00:15:15] Go to spec.fm slash Linode. Thank you again to Linode for sponsoring today’s episode of Developer

[00:15:20] Tea.

[00:15:21] Until next time, enjoy your tea.

Visão de gráfico