Preliminary reading:

- “The Origins and Motivations of Univalent Foundations” by V. Voevodsky’s [PDF]
- “Proofs and refutations” by I. Lakatos [link]
- “On proofs and progress in mathematics” by W. Thurston [link]

I find the recent surge in interest in the use of proof assistants in mathematics exciting. Because of the nature of proof assistants — computer systems by necessity lack mathematical intuition and must be fully formal — there is a renewed interest in logic and foundations of mathematics. What is special this time around is that there seem to be echoes of this interest among mainstream mathematicians. Because history always repeats itself some of the old arguments are being rekindled: ”conceptual” versus “formal” mathematics, or call it “platonism” vs. “logicism” if you have a philosophical bend, or, as G. C. Rota nicely put it “truth” vs. “the game of truth”.

As most philosophical arguments, these arguments arise out of confusion. This is not slagging philosophy, just highlighting its role and methodology: clarifying confused (or confusing) concepts by employing them in dialogue, like new and untested weapons in a military exercise. Once the concepts are clarified they can be passed over to science, mathematics, etc. This passing of the baton is of course not an official ceremony, but it is a slow osmosis of ideas through the many membranes that separate various fields and sub-fields of knowledge. This is my attempted contribution to clarifying the confusion.

There is no need for a conflict between “formal” and “conceptual” mathematics, because there is no need to have only one kind of mathematics. This is as unnecessary as forcing a choice between “constructive” and “classical” mathematics: they simply are two different worlds, as explained very nicely by Andrej Bauer. The universe of mathematics would be poorer without any of them. Similarly, the universe of mathematics would be poorer without “formal” or without “conceptual” mathematics. But what are they and what purpose do they serve?

### ”Conceptual” mathematics

This is the conventional established mathematical tradition that Lakatos and Thurston so beautifully describe in their papers. Somewhat surprisingly, conceptual mathematics is not “just” about formulating and proving theorems. It is not automatically the case that the mathematician who proves the most theorems or the hardest-to-prove theorems is the highest rated. The fascinating beauty of conceptual mathematics comes out of the creative tension between definitions, theorems and proofs. It is not always the case that the definitions are produced, then, using proofs, theorems are churned out. Sometimes the desirable theorems are known well before the definitions have been clarified (see early work on mathematical analysis). Sometimes a proof is so interesting that both definitions and theorems are adjusted to fit it (See “Proofs and Refutations”). Everything is in a state of flux and mistakes are possible but not necessarily devastating: they show room for improvement and further work.

Computer-aided proof assistants can get in the way of conceptual mathematics. Because they force a full formalisation of all concepts, the concepts can become buried under too much book-keeping and thus lose their intuitiveness. Proof assistants are excellent at checking correctness but are not necessarily the best vehicle for communicating ideas. And this is what mathematicians use proofs for: communicating ideas, not checking correctness. This is one of the reason why mathematical papers in any field are so impenetrable even to mathematicians in other fields. They use a specialised language that relies heavily on the social context in which that particular mathematics happens. Lacking the context it is almost impossible to read the papers. The mathematics happen inside mental models that are poorly described by the formalisations used in mathematical papers. Conceptual mathematics requires more than correctness of proof, this is why the Four-Colour Theorem and its proof which relies heavily on computation makes conventional mathematicians scrunch their noses in dismay.

### ”Formal” mathematics

Exploring mathematical concepts is fascinating, but sometimes we really just need to know if a statement is true or not. This is often the case if we build things and we are concerned that these things behave in a desired way. Since mathematics is the language we use to talk about things in the real world (e.g. physics or engineering) there is a practical concern with the validity of mathematical statemants. In the same context, the aesthetics of the definition-proof-theorem interaction are often of no interest.

Software is perhaps the most obvious example in which mathematical concepts are designed and used in a way that has an immediate impact on the real world. A computer program is an abstract mathematical concept that drives the behaviour of a concrete physical device, the computer. Most errors in the behaviour of a program come not from the hardware but from the software itself — they are of a purely mathematical nature. But programming languages and programs (existing ones, not as a matter of necessity) are ugly mathematical objects, devoid of conceptual elegance and encumbered by complications and contingencies. Their genesis is not driven by a taste for elegance, as most conceptual mathematics, but mainly by how efficient they are in driving the physical computer, itself a complicated and ad hoc device, to perform certain tasks. However the correctness of software is of crucial importance, and the only realistic way in which it can be achieved is by using formal mathematics, as embodied by proof assistants.

But it’s not just software. Properties of security protocols and encryption schemes are also examples of mathematical properties where correctness trumps in importance conceptual coherence.

Conceptual mathematicians would of course rather that their theorems were true. This is why computer checking of conceptual mathematics is of some interest. And when a massive formalisation effort such as Gonthier et. al.’s formalisation of the Feit–Thompson (odd order) theorem turns out an insignificant amount of errors there is good reason for high-fives and some sighs of relief.

### ”Formal conceptual” or “Conceptual formal” mathematics

The area of overlap between formal and conceptual mathematics is a fascinating one. This is where the Univalent Foundations project is happening. What is the right foundation for mathematics? Not just in terms of being sound but also in making conceptual mathematics more like formal mathematics (i.e. checkable) and formal mathematics more like conceptual mathematics (i.e. readable).

Other areas of mathematics that should be both formal and conceptual are those where the choice of foundational structure is important: type theory, logic, constructive mathematics. Unlike classical mathematics, which take an everything-goes approach to its logical foundations, these areas must be more discerning in what rules are or are not acceptable. A proof of a property must not trespass into illegal territory, and for informal proofs it can be quite difficult to assess that.

As most computer scientists my own mathematical work has elements of the formal and the conceptual. An example of the mostly formal is recent work on distributing the Krivine machine [link][PDF] whereas an example of the mostly conceptual is work on game semantics [link][PDF]. I cannot brag that I have done a lot of work in mathematics that is both formal and conceptual, but if you forced me to give the best example it’s perhaps work on formalising some of the structures encountered in game semantics to facilitate reasoning [link][PDF].

Hi! I love everything you wrote except this: “What is the right foundation for mathematics?” I don’t think we should expect a single best foundation for mathematics any more than there’s a single best programming language. Indeed I’m trying to get people to stop using the “foundation” metaphor. A building has a foundation, which holds up the rest. It has just one foundation, and if you remove it the whole structure collapses. Mathematics is not like that! There are many ways to reach the full glory of mathematics starting from simple assumptions, and this is a good thing. I would prefer to call these “entrances” rather that “foundations”.