Lecture 1.1) Why Model?

From Coursera's "Model Thinking" course.

Hi, my name is Scott E. Page.

I'm a professor of complex systems, political science and economics

at the University of Michigan in Ann Arbor.

And I'd like to welcome you to this free online course
called Model Thinking.

In this opening lecture, I just want to do four things.
The first thing I want to do is I want to

sort of explain to you why you know, I
personally think it's, it's so important

and fun to take a course in models.
Second, what I'd like to do is, I want to

give you a sense of the outline of the
course—like, what we're gonna cover—a

little bit, and how it's gonna be
structured. Third thing is, I'll talk a

little bit about an online course that
you, I've never taught an online course

before, you probably haven't taken one.
So, let's talk a little bit how it's, just

how it's structured, how it's set up, you
know, what, what's out there on the web,

that sort of thing. And then the last
thing I'll do is I'll talk about, sort of,

how I'm gonna structure particular units.
Each unit will focus on a single model or

a class of models. I wanna give you some
sense of exactly how we're gonna unpack

those things, analyze them and think about
them, alright? Okay, so let's get started.

Why model? First reason, I think,
is this. In order to be an intelligent

citizen of the world, I think you have to
understand models. Why do I say that?

Well, when you think about, like, a
liberal arts education, I think some of us

classically think of, sort of, the great
books, like, this long shelf of books that

everyone should know. And when the great
books curriculum was formed, right, and

I'll talk about this some in the next
lecture, you know, most of human knowledge

didn't have models in it. Models are a
relatively new phenomena. Right? So, if

you take, you know, whether you go from
anthropology to zoology, anywhere in

between. When you go to college, you'll
sorta find, like, oh my gosh, I'm learning

models in this course. And we'll talk, in
a minute, about some of the reasons why

we're using models, right? But models are
everywhere. And so in order to just be

involved in a conversation, it's important
these days that you can use and understand

models. Alright. Reason number two. The
reason models are everywhere, the reason

they're everywhere from anthropology to
zoology is, they're better, right?

They sort of make us clearer, better thinkers.
Anytime anybody's ever run a horse race

between models making, you know, people
using models to make decisions, and people

not using models to make decisions, the
people with models do better. So models

just make you a better thinker. The reason
why is that they sort of weed out the

logical inconsistencies. They're a crutch,
right, they just, you know, we sort of are

crazy, you know, think silly things, can't
think through all the logical

consequences. Models sort of tie us to the
mast a little bit. And in doing so, right,

we think better. We get better at what we do.
All right. Reason number three to use and

understand data. So. There's just so much
data out there, right? When I first became

a social scientist, I mean, it was, it
would be a real effort for somebody to go

grab a data set. Now there's just a ton of
it. I like to think of it as a fire hose

of data, but my friends who are computer
scientists, they call it a hairball of

data, right, cuz it's just sort of all
mangled and messed up. So, models, they'll

just take that data, right, and sort of
structure it into information, and then

turn that information into knowledge. And
so, without models, all we've just got is

a whole bunch of numbers out there. With
models, we actually get information and

knowledge and eventually maybe even some
wisdom. At least we can hope, right? Okay.

Reason number four: last piece of main
category of reason.

And by the way, [i]n the next four lectures I'm going to work through and unpack each of

these four reasons in more depth. But I
just sorta want to lay them out there,

this first lecture. So, reason number
four: to decide, strategize, and design.

So, when you've gotta make a decision,
whether it's, you know, whether you're the

President of the United States or whether
you're running your local PTO

organization, it's helpful to build or
structure that information in a way to

make better decisions. So we'll learn
about things like decision trees and game

theory models and stuff like that, to just
help us make better decisions and to

strategize better. And also, at the very
end of the class, we'll talk about design

issues, right? You can use models to
design things like institutions and

policies and stuff like that. So, models
just make it better at making choices,

better at taking actions. Okay, so those
are the big four. Now let's talk a little

bit about, the outline of the course, what
it's like. So, this isn't gonna be a

typical course, not just because it's
online, but because the structure of the

course is very different. So most courses,
like if you take a math course, it sort of

starts here and moves along, right, with each thing building on the thing before it.

Now the difficulty with a course like that is if you ever fall off the train—right? fall behind—

that's it, you're just lost.

Because everything, what I'm doing in lecture six you need to know lecture five,

and for lecture five you need to know lecture four. Well this course is going to be very different.

This course is going to be a
little bit more like, a trip to the zoo.

So we're gonna learn about giraffes, and then we're gonna learn about rhinos,

and then we go over the lion cage. So if you didn't quite understand the rhinos,

it's not gonna hurt you too much
when we go over the lion cage, right?

So it’s more like just moving from one topic
to the next.

They're somewhat related in that they're all sort[s] of animals,

but you don't need to fully know the giraffe to move to the rhino,

but obviously like
we're not gonna take like giraffes and

rhinos, we're gonna study models and
[inaudible]. So what kind of models. We're

gonna study models like collective action
models. These are models where individuals

have to decide how much to contribute to
something that's for the public good.

We'll study things like the wisdom of
crowds. Like, how is it that groups of

people can be really smart? We'll study
models that have, like, fancy names like

Lyapunov models and Markov models.
These are models of sort of processes,

right? So they, they sound scary, but
they're actually always sort of fun and

interesting. We'll study game theory
models. We'll study something called the

Colonel Blotto game, which is a game where
you have to decide how many resources to

allocate across different front. So this
can be thought of as a really interesting

model of war. It can also be an
interesting model of, you know, firm

competition or sports, or legal defenses,
all sorts of stuff. So. We're going to

just you know, play with a whole bunch of
moth. Everything from economic growth to

tipping points. You know, a whole bunch in
between. So it should be lots and lots of

fun. Okay. What's the format for this?
How's this going to work? What does an

online course even look like? Okay. Well.
Let's think about it. So first thing,

there's these videos. You're watching one
right now. I'm going to try to keep them

between eight and fifteen minutes in
length. Right? Sometimes I may sneak to

sixteen but mostly I'll be creating
fifteen minutes in length. And inside the

videos there'll be questions. So I may,
all of a sudden the video may stop and

it'll say, what's the capital of Delaware?
Well actually it won't say that, but

something germane, hopefully, you know, to
the, to the lecture. So, there'll be these

fifteen eight to fifteen minute lectures.
Each module, each section will have, you

know, somewhere between like three and six
of those. Right? Okay. In addition,

there'll be readings. So on the wiki
you'll find links to the reading. Not a

bunch of these readings will come out of
some books that I'm, I've written, and

some, one that I'm about to write about
actually this course, and it'll all be

free. So, you'll know that Princeton
University Press has been very generous in

letting a lot of that content of my previous books
be out there. So we're going to you'll be

free to download whatever you need to look
at. All right? There's some assignments.

So there's an assignment on the web page.
You'll see a little assignment thing, so

all sorts of assignments. So, just make
sure you're following what’s going on

with the course, and then finally there
will be some quizzes, right so there are

some quizzes out there just to make sure
you know hey am I really getting this.

You'll, you'll watch me and you'll think,
yea Scott gets these models but that's not

what this is about, right this is about
you understanding the models. So there'll

be some quizzes, right but all in good
fun. Okay, and finally, there's the

discussion form. I mean, there's 40 to
50,000 people in this class, right, so,

office hours can get sort of crowded. So,
we're gonna have a discussion forum where

people are gonna ask questions. I'll
answer some. I've got some graduate

students who'll answer some. Other
students can answer things, but there'll

be a place for people to sorta share
ideas, share thoughts, give feedback and

should be, hopefully, you know, really
useful and structured in a way that will

work for everybody. Okay so how does it
work, what's one of these sections gonna look like?

Well, each section—which [in this] course is going to be 21—is going to be focused on a particular model.

And so, we talk about the model and, say, what is the model?

what are the assumptions? what are the parts? how does it work?

You know, what are the main
results? What are the applications? So, we

just sort of you know talk through how these
thing sort of plays out. Then I'll go

into some technical details. Sometimes in
the same lecture, I present the model.

Sometimes in later lectures. This will be,
you know, more technical stuff. A little

bit more mathematics. Now, I'll try and be
very clear about whether or not the math

is, you know, easy, medium, or hard. You
know, I'll let you know upfront. Like

okay, this may require a lot of algebra or
this is just, you know, sort of simple

logical thinking. Right, so. I'll be
pretty clear about how much effort it's

gonna take to get through, trudge through
some of the examples. And there will be

practice problems you can work on as well.
And the other thing I'm gonna do in every

one of these sections is talk about the
fertility of the models. [Take, remember]

this Colonel Blotto model
that was, could be used to model war or

sports or legal defenses, right. Most of
these models were developed for one

purpose but we can apply them to other
purposes. So we're going to talk a lot

about how, okay, now that we just learned
this model, where can we apply it? where

else does it work? Right? Okay, so that's it. That's

sort of how it's gonna work, right?
Learning models is really important. It

makes you a more intelligent citizen,
probably just, you know, sort of, just a

more engaged person out there in the
world. ’Cause so much of how people think

and what people do is now based on models.
Makes you a clearer thinker. That's why so

many people are using models. It helps you
use and understand data, and it's gonna

help you make better decisions, strategize
better, and even, you know, design things

better. So the course should be really,
really useful. We're gonna cover a lot of

topics, they don't necessarily build on the
one before, there'll be some

quizzes and videos and that sort of stuff,
and this should be just a great time.

Alright. Welcome, and let's get started.
Thank you.