- Simon Khuvis
- Brooklyn, NY
- United States
Student B.S. Engineering, Cooper Union for the Advancement of Science and Art
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How can computer models help us build intuition?
The use of visual diagrams to explain and understand difficult concepts is as old as history itself, but in the twentieth century, for the first time, engineers and scientists were able to enlist the help of computational tools to represent systems with greater clarity and detail. While computers, with the right peripherals, are able to present data to all the senses, in two or three dimensions and through time, perhaps their greatest pedagogical virtue is their interactivity. People learn by doing: young children internalize Newton's Laws long before their first formal physics class by manipulating the world around them. Computers offer the promise of similar interactivity for systems which are less readily accessible, or even entirely esoteric. In my Bioelectricity class, for example, we have been using computer simulations of the complicated Hodgkin-and-Huxley membrane equations to gain insight into neural reactions to various experimental stimuli. How can computer models be used to learn, understand and ultimately build intuition about systems in nature and science?
Rhona Pavis 50+
Andrew Leader 50+
This is where many researchers see the problem as one that people must solve, with imagination and intuition based on years of experience and knowledge of how atoms and molecules tend to move. At Weill-Cornell Medical college, Prof. Jason Banfelder has build "The Cave," a room outfitted with screens covering the ceiling, floor, and three walls, used in conjunction with a supercomputer. Large amounts of funding have been poured into this project which serves simply as an advanced visualization tool, with which researchers can visualize protein structures to gain intuition about reactivity and function of different biological entities.
This is this first really cool use of advanced visualization that I can think of. What other cool uses can you think of?
Steven Nikolidakis 50+
Simon Khuvis 50+
It is interesting that you say that this software is oversimplifying our lives as engineers, and that programs can simply give you the right answers when it comes to simulations of load-bearing structures. Do you think that perhaps, in this case, computers have replaced the need for human intuition in the field?
Maria Georgescu 50+
Matthew Wieder 50+
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Joanna Cruz
I completely agree with you that we need to trust our intuitions provided that we figure out how to increase our intuitions. Increasing our intuition can come from rigorously struggling and studying concepts and making familiar connections through analogies and simulations. This should be a constant learning and growth process.
I feel like intuition is something that should be developed and nurtured early on in life through education in schools and homes. Families and educators should feel compelled to insure that children grasp full understanding of concepts whether it is through computer models or through some other means of teaching concepts so as to increase intuition.
Harry Banaharis
shani rassin
you ask "how can we gain insight" and later you mention intuition as the cognitive skill you seek to acquire. ill assume you mean the action of grasping something .in some languages the word learning also means taking or catching. if this is indeed what you meant i would like to define it in another way as well. intuition is what we have when we are committed to the whole. it is when our perspective of a system is as broad as possible.
the model should always be a system because reality is. but what would be a model worth studying? one idea could be a machine that is man made, but than we would miss out on all the juicy reality we left outside of it.
i think the best way to have intuition for something is to be immersed in it, and than fully communicate it through another system that is rich. the distance between the two is always mind blowing like learning a new language. the two systems are the same yet different.
to be more concrete, as for science class, i know mostly this. i wouldnt start with asking what a computer can do, i would ask what is the thing that needs grasping and also "what is it like to grasp it". i would treat the model like a game and different parts of the system like "stories" or characters with a biography. "game" and "story" should be regarded broadly.
if you know the system well enough to teach it you will get the tone of the stories right and the feel of game. if you are only discovering the system this would make a thinking exercise in empathy. im sure there is a special place in the world for ppl who identify with scientific factors. anyway thank you for this question.
Andrew Tam
I like the analogy you have made between model and story: we really need to understand each "character," and their "biographies" in order to create a successful "story."
The model is helpful because it allows us to put the story on paper. Because some models can have so many variables, it often gets confusing, and difficult to remember relationships between things. The model helps us build this intuition because it organizes all of our thoughts - its like writing the story on paper, as opposed to recalling it from memory all of the time.
We no longer risk getting lost in our thoughts as often because we have put them all into the model. The program helps by automating one step of our thinking process so that we may focus on another, and further our intuition or understanding of the problem at hand. Assuming that we have put the proper work and preparation into the model, I believe that models are certainly beneficial in developing intuition.
S Lam
Harnsowl Ko 50+
The issue isn't that we need computers to have intuition. It is so that we can use technology in order to develop our own intuition. If you watch this TED talk about how complexity leads to simplicity: http://www.ted.com/talks/eric_berlow_how_complexity_leads_to_simplicity.html , you'll see that breaking down complex models is actually less cumbersome than originally thought. However, what is important is that Eric Berlow has had multiple dealings with such issues so that he has developed an intuitive sense as to where patterns may emerge. This intuition definitely wasn't something that he one day woke up; it is something that was developed over time. And he wasn't alone on stage; he used technology to map out the web of complexities. We do not need computers to have intuition; we simply need them to provide us with models that simplify complex ideas so that we develop a certain feel, an intuition, regarding the topic in order to make our lives like you said better and less destructive.
Harry Banaharis
By definition, intuition is knowledge without inference or reason yet from a neuroscience perspective it follows that such knowledge does not spontaneously manifest but rather is the product of cognitive processes, which are themselves a product of neural circuit function. I would think that rather than propagating and being reliant on "intuition" and it's perceived benefits we should aim to understand the underlying cognitive processes that yield superior understanding compared with traditional reasoning approaches.
November Howard
Simon Khuvis 50+
The brain is an inherently stochastic organ -- in fact, computer models show that without a healthy dose of noise, neurons would only be able to respond in a nearly on-off fashion to graded stimuli. That noise, in combination with population-averaging effects, allows for the generation of a graded, smooth output in response to varying stimuli. While it might be uncomfortable to accept any level of randomness in our thinking, I would argue that that this is necessary for any real innovation to take place. As Albert Einstein said: "imagination is more important than knowledge. Knowledge is limited. Imagination encircles the world."
David Wees
http://davidwees.com/classroomsim/
There is a lot of work that would need to be done to work on this simulation (it has some pretty serious bugs at this point). For example, it ignores the idea that given the right conditions, students can spontaneously discover ideas on their own (without relying on outside information necessarily) and the variables related to transmission of knowledge are incomplete. It is an unfinished attempt to look at information transfer theory as it would apply to education, and to see if we can gain any insights as to appropriate arrangements of classes (and pedagogical styles) based purely on information theory.
Obviously, I'm sharing this example as a sample of something we could attempt to use the power of computing to solve (whether we would be successful is entirely a different matter).
Andrew Kiang 50+
Samantha Massengill 50+
MARC DE FAOITE
Intellect is limited.
Intuition is boundless.
Left brain/Right brain in simplistic terms.
Intuition largely (if not entirely) depends on dropping any rational/analytical/linear approach.
It seems to me that computer models (or technology in general) can help us test the validity of our hunches or intuition.
The phone rings - "Oh hi, how are you? I was just thinking about you."
Technology confirms a connection between individuals that seems to be based on intuition.
Perhaps this validation of our intuition will allow us to trust and use it more.
Do you choose between your head or your heart? Do we have to choose? Maybe we can have both.
We live in a fundamentally left brain/right-handed world. This has lead to a 'civilization' in crisis, in a severe state of imbalance.Perhaps technology can bolster our innate intuitional abilities and help us as a species to become more human again..
That said, I realize I may be misinterpreting the crux of the ambiguously worded premise of this debate.
I am interested in technology in the service of human kind - in using these models to help in building intuition in human beings, in human hearts.
Looking at some of the comments below (a few of which admittedly went right over my head) perhaps you are talking about building intuition in machines.
If that's the case then we are more lost than I thought.
Veronica Shalotenko 50+
You bring up a good point about computer modeling giving validity to our intuition. My first inclination was to disagree with you and say that computer simulations can, in fact, build our intuition. However, I then started thinking about the process of coding and running a simulation from scratch (as an engineer or scientist might do).
Being an engineering student, this process is something that is familiar to me. In order to program such a simulation, it is necessary to have insight into the subject. Hence, the simulation is not a means of building intuition, but rather a means of testing intuition.
There is a TED talk by Eric Berlow called “How complexity leads to simplicity” in which he argues that trends and patterns are easier to discern in larger amounts of data. The beauty of the computer simulation is that it lets us generate large amounts of data in a very short time. Again, though, in order to generate useful data, we have to go into the simulation with some pre-existing knowledge (or, at least, an intuitive guess) of the final outcome.
James McGuiness
I have labored long to develop a grip on how to "model" new relationships with computers, with each other using the full spectrum of non-linear digital media devices including computers, and we with ourselves with as well using such technologies--and yes, incorporating formal sensitivity to neuroplastic dynamism that if, put into a supplanting system could force the establishment and people to choose between continued dysfunction and new function. But trying to convey the details has proven a exercise in exercise. Now if I could just dictate and have artists and scientists do what I say, we could reform education and change the future. Tough deal when everyone else wants to change the world to in their own way.
November Howard
Shashank Rao
November Howard
Augmented reality seems like a promising approach, its already being used a bit in interactive visualisations. Being able to overlay internal views of things onto the things themselves, or deal with models of things interactively with gestures or occular control or neuro control seems useful.
Being able to modify or tag models with meta-data collaboratively might help people build different visualisations based on the tags. Like people might tag all the possible tumors they see in some high resolution scan of a patient, and a doctor might check the spots that are getting multiple hits by having them stand out in some way, as a heat map skinned over the model or something.Some of this kind of stuff, after you've gathered enough human data you can start training neural nets to identify features based on identifications made by people.
I like the idea of using data hiding in 3d models a lot. Being able to open up a thing and dig into it with more complexity or pack it down to a simpler form means you can kind of tweak which aspects of the representation you need to see in how much detail. This is also a pretty good way to simulate and blueprint stuff, since the highest level blocks of your simulation can be dummy modules until their details are filled in.
Since lots of different kinds of systems interact with each other, I'd suggest a kind of universal modular simulation system, where users could get on and collaboratively apply detail, that was in some way tagged or connected to physical scans or models if possible, with a lot of different views that a person can arrive at, and with the ability to take the model part of it and hide it completely, or make it as abstract as possible, or dig into specific details as deep as necessary. modules might also be linked to media that can explain how that component works. And if all the people using the model can communicate with each other, they can all share intuition.
Sue Cook
Yu-An Chen 50+
Sophie Rand 50+
what's exciting about this is that if you've done everything syntactically correctly and you still see something you didn't initially expect, you're forced to change up your understanding of whatever it is you are modeling, thereby developing (correct) intuition for how some system or mechanism works.
for say, the hodgkin huxley model which we just learned, the equations that govern it may not mean anything to us in terms of visualizing how the equations behave and how they act dynamically, but when you turn that into a model, you can actually get a clear picture of what's going on. also if you have a generally correct intuition for the characteristics of a dynamic model, turning that into a computer model can help to point out nuances that you didn't initially think of...
Ariel Habshush 50+
Coding up computer simulations can help us better understand concepts that we think we know pretty well. For example, last semester in my neuroscience class I was simulating the development of ocular dominance in the primary visual cortex using Hebbian plasticity learning. The mathematical model and equations that simulate this phenomenon are composed of first order differential equations and matrix algebra. When reading this math in textbooks I thought I understood what was going on and that I followed everything completely. However, when it came to simulating these equations on a computer, I realized I did not fully grasp all the ideas. I had to reread the material over and over again and re-derive all the equations in order for me to know how to make use of them. What took me only a couple of hours in reading took me a few weeks to simulate. Making a computer simulation forced me to understand the material much better and to attain a better intuition for what was going on.
James Patten 100+
Simon Khuvis 50+
You can find the paper here: http://www.physics.emory.edu/~weeks/lab/papers/wolf-ajp96.pdf
Sophie Rand 50+
David Wees
However, you do really need to ensure that you are thoughtful in your use, and you don't assume that what you have provided is an accurate measure of reality; you need to check.
Josh Mayourian 50+
I agree with your point and would like to expand on it. As you state, "you don't assume that what you have provided is an accurate measure of reality." I believe one would need a pretty solid basis of certain material before using simulations. The solid basis would allow one to have an intuitive understanding by interpreting the material "with a grain of salt".
Sometimes these models aren't the best way to have an intuitive understanding. For example, when talking about having an intuitive understanding with science, lab work and hands on work lets you see exactly how much of an assumption you must make. Lab work lets you see how a real life application can lead to different results than expected. I believe the struggle of hands on work can lead to a better understanding than just a computer model.
Howard Yee 50+
For example, I've had someone ask me where they can get an ethernet "y-splitter". They wanted to share their network connection by using a y-adapter for ethernet. Intuition from other devices (rca, bnc, stereo, etc) tells us we can do this. One may argue, "of course!, networking is complex and it requires two way communication, so of course you can't split the cable that easily". But, before ethernet, there was thicknet, which was essentially one giant coaxial cable shared by multiple computers, yet they can do two-way comm. (so with thicknet, you can use a y-splitter). Rather, one needs to know how ethernet protocol works. One would have to understand how it works before they can conclude that these mystical ethernet y-splitters do not exist. However, even after having that knowledge, one cannot use intuition to construct their own network hub. Ok, say they learn how network protocols work, they still cannot construct their own network hub, they need to learn about signal propagation to know that certain long wires need to be in twisted pairs. One can find similar kinds of issues with any topic of study.
We may say intuition is useful, but to me, it's not any better than a coin toss (that is unless you have more knowledge, but by then it's not intuition)
November Howard
Nicolette Sinensky 50+
While what you and Simon are saying about simulations incorrectly portraying the information may be somewhat correct, the overall point of them is to simulate, not give a 100% accurate representation. It's this simplification that allows us to develop intuition for such things, since our minds can have a hard time building such complicated models on their own. Using the example of Professor Wolf's paper on electric field lines, we all admit that the current diagrams are flawed. But it's these flawed pictures that help us gain intuition of how electric fields act in general, and we can then extend this understanding to a full three dimensional picture of electric forces and fields. I think as long as we remember not to take a simulation to be the reality, they can be an invaluable tool.
James Patten 100+
One of the most powerful things about interactive computational simulation is the ability to perform these same sorts of experiments on all kinds of systems that we can't normally directly manipulate with our hands. But for this type of interactivity to be most successful as a learning tool, its feedback has to be immediate and engage the senses in a rich way. WIthout this rich, immediate feedback, people have a much harder time understanding and internalizing causal relationships.
Here's something I built to explore how these ideas could be used to teach kids about chemistry:
http://pattenstudio.com/projects/chem
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Simon Khuvis 50+
See: http://www.youtube.com/watch?v=XkAPv5s92z0&feature=related
I wonder if there is a more accurate way of visually representing four dimensions with a computer simulation?
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Simon Khuvis 50+
One can know how to work a computer -- that is, if one presses a series of keys, one can perform a certain action, but that knowledge is of limited value. If someone understands the workings of a computer, he or she can explain the purpose of each of those keystrokes. Finally, if one is wise, one can do things on the computer that one has never seen, and even extend that expertise beyond the world of computers.
Fritzie Reisner 100+
Jordan Reeves 50+
http://www.affectiva.com/affdex/#pane_overview
This might not be exactly what you're looking for, but maybe it will spur some ideas...