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What Gödel Discovered

In 1931, a 25-year-old Kurt Gödel wrote a proof that turned mathematics upside down. The implication was so astounding, and his proof so elegant that it was...kind of funny. I wanted to share his discovery with you. Fair warning though, I’m not a mathematician; I’m a programmer. This means my understanding is intuitive and not exact. Hopefully, that will come to our advantage since I have no choice but to avoid formality 🙂. Let’s get to it.

Unification

For the last 300 years, mathematicians and scientists alike made startling discoveries, which led to one great pattern. The pattern was unification: ideas that were previously thought to be disparate and different consistently turned out to be one and the same!

Newton kicked this off for physicists when he discovered that what kept us rooted on the Earth was also what kept the Earth dancing around the sun. People thought that heat was a special type of energy, but it turned out that it could be explained with mechanics. People thought that electricity, magnetism, and light were different, but Maxwell discovered they could be explained by an electromagnetic field.

Darwin did the same for biologists. It turned out that our chins, the beautiful feathers of birds, deer antlers, different flowers, male and female sexes, the reason you like sugar so much, the reason whales swim differently...could all be explained by natural selection.

Mathematicians waged a similar battle for unification. They wanted to find the “core” principles of mathematics, from which they could derive all true theories. This would unite logic, arithmetic, and so on, all under one simple umbrella. To get a sense of what this is about, consider this question: How do we know that 3 is smaller than 5? Or that 1 comes before 2? Is this a “core” principle that we take on faith (the formal name for this is called an “axiom”) or can this be derived from some even more core principle? Are numbers fundamental concepts, or can they be derived from something even more fundamental?

Crisis

Mathematicians made great progress in this battle for core principles. For example, a gentleman called Frege discovered that he could craft a theory of sets, which could represent just about everything. For numbers, for example, he could do something like this:

A demonstration of how to represent numbers with sets

Here, he represents 0 the empty set. 1 as the set which contains the set for 0. 2 as the set that contains the set for 1 and 0. From this he could set a principle to get the “next” number: just wrap all previous numbers in a set. Pretty cool! Frege was able to take that and prove arithmetic rules like “1 + 1”, “numbers are infinite”, etc.

This looked formidable and cool, but Bertrand Russell came along and broke the theory in one fell swoop.

He used the rules that Frege laid out to make a valid but nonsensical statement. He proved something analogous to 1 + 1 = 3 1. This sounds innocuous; it was after-all just one statement. But nevertheless it was disastrous for a foundational theory of mathematics. If you could prove that 1 + 1 = 3, then you can’t really trust any true statement that results from this foundation.

This put mathematicians on a tail-spin. They even dubbed this period the “Foundational Crisis of Mathematics”

Hilbert’s Program

In an effort to solve this problem, a mathematician called Hilbert laid down some requirements for what a fundamental theory of mathematics had to look like 2. He said that this theory must be a new language, with a set of rules that satisfied two primary constraints:

The theory would need to be able to prove any true mathematical statement. For example, imagine the statement 1 + 1 = 2. If this language can’t prove that statement, then it certainly can’t prove all of mathematics. Hilbert called this quality completeness. The language would need to be complete.

The second hard requirement, as we discussed earlier, was that it could not prove a false mathematical statement. If we could prove 1 + 1 = 3, then all was for naught. Hilbert called this consistency. The language would need to be consistent.

Russell and Whitehead

Bertrand Russell, the gentleman who broke Frege’s theory, worked together with Alfred North Whitehead to develop a theory of their own. They labored for years to craft an immense volume of work, called Principia Mathematica 3.

They started by writing a new language (let’s call it PM) with a few simple rules. They took those rules, and proceeded to prove a bunch of things. Russell and Whitehead took almost nothing on faith. For example, let’s look at this almost-impossible-to-read proof over here (don’t worry, you don’t need to understand the syntax for this essay):

An example, very hard-to-read proof from Principia Mathematica

This proof showed that “1 + 1”, does indeed equal “2”. It took 2 volumes to get here.

Their language was dense and the work laborious, but they kept on proving a whole bunch of different truths in mathematics, and so far as anyone could tell at the time, there were no contradictions. It was imagined that at least in theory you could take this foundation and eventually expand it past mathematics: could you encode in pure logic how a dog behaves, or how humans think?

Gödel Comes Along

It certainly looked like Principia Mathematica could serve as the foundational theory for Mathematics. Until Gödel came along.

He proved that Principia Mathematica did indeed have true mathematical statements which could not be proven in the language. Principia Mathematica was incomplete.

This was startling, but his proof went even further. He showed that the entire enterprise behind Hilbert’s Program — to find a formal foundation for mathematics — could never work.

It’s hard to believe that a person could really prove that something can “never” happen — imagine if someone told you that we could never travel farther than our solar system — you’d look at them with suspicion.

Yet here Gödel was...a 25 year-old who proved beyond a doubt that this enterprise was impossible. He did this by showing that if a language could represent numbers, then unprovable statements would necessarily pop up.

Let’s think about that for a second: Numbers seem so quaint and easy to prove — just “1”, “2”, “3”...so on. People thought we could eventually write down how humans think — imagine how shocked they must have been to see that we couldn’t prove all truths about...numbers.

Let’s see how Gödel did it.

PM-Lisp

Now Russel and Whitehead’s language was hard to read. There’s no harm done in changing some of their symbols around. Let’s map their language to something more amenable to programmers: Lisp!

You can imagine that Russell and Whitehead came up with a lisp-like language. Here’s how their syntax looked:

First, they had a few symbols for arithmetic.

Symbol
Meaning
Example
0
zero
0
next
the next successor
(next 0)
+
plus
(+ 0 (next 0))
*
times
(* 0 (next 0))
=
equals
(= 0 (* 0 (next 0)))

Just from these symbols, they could represent all natural numbers. If they proved that the symbol 0 worked like 0. and the symbol next worked like a successor function, then (next 0) could represent 1, (next (next 0)) could represent 2, and so on.

Here’s how they could write 1 + 1 = 2:

(= (+ (next 0) (next 0)) 
   (next (next 0)))

Now, for the purpose of this essay, I’ll add one rule. If you ever see me using a natural number inside PM-Lisp other than 0 (i.e “15”), you can imagine it’s shorthand to writing (next (next (next ...)))) that many times. In this case, “15” means next applied to 0, 15 times

Symbol
Meaning
Example
<natural-number>
(next (next ...)) applied to 0 <natual-number> times
3

means (next (next (next 0)))

(Next (pun-intended)), they came up with some symbols to represent logic:

Symbol
Meaning
Example
not
not
(not (= 0 1))
or
or
(or (= 0 1) (not (= 0 1)))
when
when ... then ..
(when 0 (or 0 1))

when 0, then there is either 0 or 1
there-is
there is ... such that ...
(there-is x (= 4 (* x 2))

These symbols map closely to the logical statements we are used to in programming. The most unusual one is there-is. Let’s see one of those for an example:

(there-is x (= 4 (* x 2)))

This is making a statement, that there is some number x, such that (* x 2) equals 4. Well, that is indeed true: x = 2. That’s pretty cool — we’ve just made a general arithmetic statement.

Where did the x come from though? Oops, we need to account for that in our language:

Symbol
Meaning
a...z, A...Z
variable

In order to represent general truths, Russell and Whitehead introduced variables. Here’s how they could derive and for example:

(not (or (not A) (not B)))

When this statement is true, both A and B must be true!

Very cool. One more trick for our essay. To make it a bit easier to read, sometimes I’ll introduce new symbols. They won’t actually be a part of the language, but it can make good shorthand for us in the essay

Form
Meaning
example
(def <name> <formula>)
define <name> to represent <formula>
(def and (not (or (not A) (not B)))

same as (and <var-a> <var-b>...)

Now we can write (and 1 2) 🙂

PM-Lisp Axioms

All we saw above were symbols. They had no meaning yet.

Russell and Whitehead needed to prove that 0 works like zero, and that = works like equals. In order to breathe life into those symbols, they started off with some core principles — the axioms.

Here’s what they chose:

Axiom
Example
(when (or p p) p)
when either apples or apples, then apples
(when p (or p q))
when apples, then either apples or bananas
(when (or p q) (or q p))
when either apples or bananas, then either bananas or apples
(when (or p (or q r)) (or q (or p r))
when either apples, bananas, or pears, then either bananas, apples, or pears
(when (when q r) (when (or p q) (or p r))
when apples are a fruit, then bananas or apples implies bananas or fruits

That’s it. This is all we needed to take them on faith for. They took these rules and laboriously combined them in intricate ways to derive everything else.

For example, here’s how they derived =:

(def = (and (when A B) (when B A)))

If A implies B, and B implies A, they must be equal! Imagine this done for hundreds and hundreds of pages.

Note something essential here: their rules are so precise that there is no room for human judgement; a computer could run them. This was a key component for a foundational theory of mathematics: if the rules were so simple that they could be run as an algorithm, then we could side-step errors in human judgement.

Gödel’s First Idea

Now, Gödel wanted to study Russell and Whitehead’s language. But, it’s hard to study symbols. How do you reason about relationships between them?

Well, there there is one thing you can study very well...numbers! So he came up with an idea: what if he could express all of PM-Lisp with numbers?

This is what he did:

Symbols

First, he took all the symbols and assigned a number to them:

Symbol
Gödel Number
(
1
)
3
0
5
next
7
+
9
*
11
=
13
not
15
or
17
when
19
there-is
21
a
2
b
4
c
6
...
...

Now, say he wanted to write when. He could just write 19. This is good but doesn’t cover much: how would he represent formulas?

Formulas

He crafted a solution for formulas too. He made a rule:

Take any formula, like this one:

(there-is a (= (next 0) a))

and convert each symbol to the corresponding Gödel Number:

token
(
there-is
a
(
=
(
next
0
)
a
)
)
Gödel Number
1
21
2
1
13
1
7
5
3
2
3
3

Then take the list of ascending prime numbers, and set each one to the power of the Gödel Number:

primeGödel Number
3²¹
11¹³
13¹
17⁷
19⁵
23³
29²
31³
37³

Multiply them all together, and you get this one huuge number:

25777622821258399946386094792423028037950734506637287219050

There’s something very interesting about this number. Because it is comprised only of ascending prime numbers, it’s guaranteed to be unique! This means that he could represent every formula of PM-Lisp, with a unique Gödel Number!

Proofs

Formulas are great, but they’re not all of PM-Lisp. We’d also want to support proofs. In a proof, we would have a “sequence” of formulas:

(there-is a (= (next 0) a)) 
(there-is a (= a (next 0)))

He applied the same trick again, but this time over each individual formula:

Gödel Formula
(there-is a (= (next 0) a))
(there-is a (= a (next 0)))
Gödel Number
25777622821258399946386094792423028037950734506637287219050
76887114166817775146256448336954145299389470803180389491850
primeGödel Number
225777622821258399946386094792423028037950734506637287219050
376887114166817775146256448336954145299389470803180389491850

Now if we took

2^25777622821258399946386094792423028037950734506637287219050 * 3^76887114166817775146256448336954145299389470803180389491850

We’d have one ginormous number. Just the first term in this calculation has 7 octodecillion digits! (1 octodecillion has 58 digits itself) But we’d have something more. This ginormous number uniquely represents the proof we just wrote!

All of a sudden, Gödel could represent symbols, formulas, and even proofs, uniquely with Gödel Numbers!

PM-Lisp on PM-Lisp

Now, we can use math to study relationships between numbers: for example “how are even numbers and prime numbers related?”, “are prime numbers infinite?” and so on. In the same way that we could use math to study prime numbers, Gödel realized that he could use math to study “all the numbers that represent PM-Lisp proofs”!

Now, what language could he use to study these relationships? Well, Russell and Whitehead made sure PM-Lisp itself was great for studying numbers...and it certainly worked well for studying primes...so why not use PM-Lisp to study “all the numbers that represent PM-Lisp proofs”?

And that’s exactly what Gödel did: he used PM-Lisp...to study PM-Lisp!

It’s certainly not what Russell and Whitehead had intended, but it was nevertheless possible. Let’s take a look at some examples, to get a sense of what we mean.

Describing formulas

Say you had a formula like this:

(there-is a (= (next 0) a)) 

What if we wanted to prove the statement “The second symbol in this formula is ‘there-is’”?

Well, if we had the Gödel Number for this:

25777622821258399946386094792423028037950734506637287219050

All we’d have to do, is to say in PM-Lisp:

“The largest 3* factor of this Gödel Number is 321”.

If we said that...it would be equivalent to saying that the second symbol (the prime number 3), is “there-is” (Gödel Number 21)! Very cool.

Well, that relationship is trivial to say in PM-Lisp. Let’s start by writing a formula to check if a number is a factor of another:

(there-is x (= (* x 5) 30))

This statement says that there is an x such that (* x 5) must equal 30. If x = 6, this works out, so the statement is true. Well, that maps to the idea that 5 is a factor of 30! So let’s make this a “factoring” shortcut:

(def factor? (there-is x (= (* x y) z)))

We can then use factor? for our statement:

(and
  (factor? x 3^21 25777622821258399946386094792423028037950734506637287219050)
  (not (factor? x 3^22 25777622821258399946386094792423028037950734506637287219050)))

This statement says that 321 is a factor of our number, and that 322 is not. If that is true, it means that 321 is the largest 3* factor in 25777622821258399946386094792423028037950734506637287219050. And if that is true, then PM-Lisp just said something about that formula: it said the second symbol must be there-is!

Constructing formulas

We can go further. We can even construct PM-Lisp formulas in PM-Lisp! Imagine we had a bunch of helper statements for primes and exponents:

(def prime? ...) ; (prime? 5) ; true
(def largest-prime ...) ; (largest-prime 21) ; 7
(def next-prime ...) ; (next-prime 7) ; 11
(def expt ...) ; (expt 10 3) ; 1000

Since PM-Lisp is all about math, you can imagine Russell and Whitehead went deep into primes and gave us these handy statements. Now, we could write a formula that “appends” a ) symbol, for example:

(* n (expt (next-prime (largest-prime n)) 3))

Say n was the Gödel Number for (there-is a (= (next 0) a)).

Here’s what that statement says:

  • Find the largest prime for n: 37
  • get the next prime after that: 41
  • Multiply n by 413

Multiplying n by 413 would be equivalent to appending that extra )! Mind bending.

(successor? a b)

Now, Gödel started wondering: what other kinds of statements could we construct? Could we make a statement like this:

(successor? a b)

This would say: “the formula with the Gödel Number a implies the formula with the Gödel Number b.”

It turns out...this is a valid, provable statement in PM-Lisp! The mathematical proof is a bit hard to follow, but the intuitive one we can grasp well.

Consider that in PM-Lisp, to go from one statement to the next statement, it must boil down to one of the axioms that Russell and Whitehead wrote out!

For example from the sentence p, we can apply the axiom (when p (or p q)), so one valid next statement can be (or p q). From there, we can use more axioms: (when (or p q) (or q p) can help us transform this to (or q p). And so on.

We already saw that we can use PM-Lisp, to “change” around formulas (like how we added an extra bracket at the end). Could we write some more complicated statements, that can “produce” the next possible successors, from a statement and those axioms?

As one example, to go from p to (or p q) we’d just need a mathematical function that takes the Gödel number for p, and does the equivalent multiplications that prepend (or, and appends q).

Turns out, this can be done with some serious math on prime numbers! Well, if that’s possible, then we could check whether the next statement in a sequence is valid:

(def successor?
  (one-of b (possible-successors a)))

This statement says “one of the possible successor Gödel Numbers from the formula with Gödel Number a , equals the formula with the Gödel Number b.” If that is true, then indeed b must be a successor of a.

Nice! PM-Lisp can say that one formula implies another.

(proves a b)

If we can prove that that a formula is a successor, can we say even more?

How about the statement (proves a b). This would say: “the sequence of formulas with the Gödel Number a proves the formula with the Gödel Number b."

Well, let’s think about it. Getting a “list” of Gödel Number formulas from a is pretty straight-forward: just extract the exponents on prime numbers. PM-Lisp can certainly do that.

Well, we already have a successor? function. We could just apply it to every statement, to make sure it’s a valid successor!

(and 
  (every-pair sucessor? (extract-sequence a))
  (successor? (last-formula a) b))

There’s a lot of abstraction over there that I didn’t talk about — every-pair, extract-sequence, etc — but you can sense that each one is certainly a mathematical operation: from extracting exponents to checking that a Gödel Number is a proper successor.

The statement above would in effect say:

"Every formula in the sequence with the Gödel Number a are proper successors, and imply the Gödel Number b."

Gödel went through a lot of trouble to prove this in his paper. For us, I think the intuition will do. Using PM-Lisp, we can now say some deep truths about PM-Lisp, like “this proof implies this statement" — nuts!

(subst a b c)

There’s one final statement he proved. Imagine we had this formula

(there-is b (= b (next a)))

The Gödel number would be 26699108848097731568417316859014651425159900891216992323750

This says “There is a number b that is one greater than a.”

What if we wanted to replace the symbol a with 0?

Well, this would be a hard but straight-forward thing: we just need to replace all exponents that equal 2 in this number (remember that 2 is the Gödel Number for the symbol a), with 5. (the Gödel Number for 0 )

(replace-exponent
  26699108848097731568417316859014651425159900891216992323750
  2 
  5)

Again, this seems pretty straight-forward mathematical computation, and we can sense that PM-Lisp could do it. It would involve a lot of math — extracting exponents, plopping multiplications — but all within reasonable logical realms.

Gödel proved that this function was also a provable statement in PM-Lisp. Our expression above for example, would produce the Gödel Number that represented this formula:

(there-is b (= b (next 0)))

Wild! a replaced with 0. PM-Lisp could now make substitutions on PM-Lisp formulas. I imagine that when Russell and Whitehead saw this, they started getting a little queasy.

Suspicious use of subst

If they weren’t already queasy, this certainly would make them so:

(subst 
  26699108848097731568417316859014651425159900891216992323750
  2 
  26699108848097731568417316859014651425159900891216992323750)

This replaces a, with the Gödel Number of the formula itself!

In this case, the formula would now say:

(there-is b (= b (next 25777622821258399946386094792423028037950734506637287219050))) 

It’s weird to use the Gödel Number of a formula itself inside the formula, but it is a number at the end of the day, so it’s all kosher and logical.

Very cool: PM-Lisp can now say if a certain proof is valid, and it can even replace variables inside formulas!

Masterpiece

Gödel combined these formulas into a jaw-dropping symphony. Let’s follow along:

He starts with this:

(proves a b)

So far saying “the sequence with the Gödel Number a proves the formula with Gödel Number b

Next, he brought in a there-is

(there-is a (proves a b))

So far saying “There is some sequence with the Gödel Number a that proves the formula with the Gödel Number b"

Now, he popped in a not:

(not (there-is a (proves a b)))

This would mean

“There is no sequence that proves the formula with the Gödel Number b"

Then he popped in subst:

(not (there-is a (proves a (subst b 4 b))))

Wow what. Okay, this is saying

“There is no sequence that proves the formula that results when we take The Gödel Number for b, and replace 4 (the Gödel Number for the symbol “b”) with the Gödel Number *b* itself!

So far so good. But what is b right now? It can be anything. Let’s make it a specific thing:

What if we took the Gödel Number of

(not (there-is a (proves a (subst b 4 b))))

It would be an ungodly large number. Let’s call it G

Now, what if we replaced b with G?

(not (there-is a (proves a (subst G 4 G))))

Interesting...what is this saying?

Gödel’s Formula

Let’s look at it again:

(not (there-is a (proves a (subst G 4 G))))

This is saying: “There is no proof for the formula that is produced when we take 'the formula with the Gödel Number G'” -- let’s remember that G is the Gödel Number for:

(not (there-is a (proves a (subst b 4 b))))

“And replace b with with G"...which would result in the Gödel number for the formula:

(not (there-is a (proves a (subst G 4 G))))

Hold on there! That’s the formula we just started with.

Which means that

(not (there-is a (proves a (subst G 4 G))))

Is saying: “I am not provable in PM-Lisp”. 😮

What to Believe

Well, that’s an interesting statement, but is it true? Let’s consider it for a moment:

“This Formula is not Provable in PM-Lisp.”

If this was true:

It would mean that PM-Lisp was incomplete: Not all true mathematical statements can be proven in PM-Lisp. This very sentence would be an example of a statement that couldn’t be proven.

But, if this was false:

Then that would mean that PM-Lisp could prove “This Formula is not Provable in PM-Lisp”. But, if it could prove this statement, then the statement would be false! This formula is provable right, so how could we prove that it is not provable? That would make our language inconsistent — it just proved a false statement, analogous to 1 + 1 = 3!

Hence Gödel came to a startling conclusion: If PM-Lisp was consistent, then it would have to be incomplete. If it was complete, it would have to be inconsistent.

Power of Numbers

That was a blow for Russell and Whitehead, but what about Hilbert? Could we just come up with some new language that could avoid it?

Well, as soon as a language can represent whole numbers, it will fall into the same trap: Gödel can just map the language to numbers, create a valid successor? function, and produce the equivalent “I am not provable in X”.

This flew in the face of many a mathematician’s dreams: even arithmetic had a quality to it that could not be reduced to axioms.

In programming, this translates to: there are some truths that you can never write down as an algorithm. This is the essence of what Gödel discovered.

He went on to prove some more surprising things. It turns out that he could write a similar, valid sentence that said “I cannot prove that I am consistent”. This meant that no formal system, could prove by itself, that it could only produce true statements.

Now, this doesn’t mean that all is for naught. For example, it may mean that we can’t write an algorithm that can think like a dog...but perhaps we don’t need to. The way neurons aren’t aware of a dog’s love of toys, our algorithms wouldn’t have to be either: perhaps a consciousness would emerge as epiphenomena in the same way. The idea of “think like a dog” just won’t be written down concretely.

We can’t prove within a system that it is consistent, but we could prove that using another system. But it begs the question of course: how could we prove that other system was consistent? And so on!

I see Gödel’s idea like a guide: it shows us the limit of what we can do with prescriptive algorithms. And I find what he did so darn funny. Russell and Whitehead went through a lot of trouble to avoid self-reference in their work. In a way, Gödel got around that by building the first “meta-circular evaluator” — a language that interpreted itself — and came up with some surprising conclusions as a result.

Fin

I hope you had fun going through this :). If you want to go deeper on Gödel’s proof, there are a few books you may like. Hofstadter’s “I’m a Strange Loop” gives a very friendly introduction in Chapter 9. Nagel and Newman’s “Gödel’s Proof” explains the background, alongside a logical overview very well. For those who want to do go even deeper, I really enjoyed Peter Smith’s “Introduction to Gödel’s Theorems”. He shows much more substantiated proofs for (proves a b) and (subst a b c) — I highly suggest giving that a read too!

Also, if you want to play with creating your own Gödel Numbers, here’s a quick script in Clojure.


Thanks to Irakli Popkhadze, Daniel Woelfel, Alex Reichert, Davit Magaltadze, Julien Odent, Anthony Kesich, Marty Kausas, Jan Rüttinger, Henil, for reviewing drafts of this essay


Thoughts? Reach out to me via twitter or email : )