# Towards no-math, graphical instructions for prediction markets

You are probably familiar with prediction markets. As of the last [general update](http://www.overcomingbias.com/2017/09/prediction-markets-update.html), Robin Hanson notes that while there is increasing research interest and a few general platforms are coming soon, the real goal of implementing inside organizations remains elusive.

I strongly suspect that it will remain so until companies are founded which use them from the beginning. This is because introducing people to new tools is hard. Introducing them to new tools that don’t even have a direct bearing on doing their jobs is even harder. We know that [trivial inconveniences](https://www.lesswrong.com/posts/reitXJgJXFzKpdKyd/beware-trivial-inconveniences) are important; it was the dominant theme of the [crypto autopsy](https://www.lesswrong.com/posts/MajyZJrsf8fAywWgY/a-lesswrong-crypto-autopsy). If it happens in an environment like Lesswrong with crypto, I expect it will be worse in virtually all other contexts.

If prediction markets are going to be widely adopted, they need to be widely applicable, which basically means that any given schlub needs to be able to make a bet in a market without any math/economics/computing background. Happily, we have extremely robust evidence that any given schlub is perfectly capable of making a bet, courtesy of casinos.

One way to help with this problem is to make it as easy and intuitive as possible to learn. To wit: interactive visualizations. The biggest inspirations are [Up and Down the Ladder of Abstraction](http://worrydream.com/LadderOfAbstraction/) by Brett Victor, and [Metaculus](https://www.metaculus.com/questions/?show-welcome=true). The first is about exploring system behavior without math, and the training for the second does a pretty good job of letting you make predictions based on the _shape_ of the probability curve (though this doesn’t work as well for understanding the payoffs). Another relevant tool is the [Sankey Diagram](https://en.wikipedia.org/wiki/Sankey_diagram), which makes the relative sizes of flows apparent at a glance. I don't know of anything which makes such a thing interactive though - which is a shame, because I bet it would make controls comprehensible to people who don't know any differential equations or linear algebra. I am currently impressed by [Seeing Theory](https://seeing-theory.brown.edu/#firstPage). I ran across a few other websites which are designed to communicate math, and even one about risk, but for some reason all these savages are using Flash.

However, all of these is mostly for teaching math, and that is not actually the goal. Fundamentally the idea is information flows into the market, and only payments need to flow back out. So what we need is a way for people to specify what they think the outcome will be, with what confidence, without numbers.

Naively I am leaning in this direction:

*   Numbers are presented as areas
*   Functions are presented as shapes
*   Operations show up as transformations of the areas/shapes (for example, showing how a given bet affects the overall market, or maybe combining sub-bets).
*   We want people to be able to translate their beliefs this way pretty easily. Stuff like "the more sure you are, the narrower the shape should be," where the shape is the distribution curve, is intuitive.

I feel like the instructions could be collapsed into a few drag-and-drop shapes, and a few heuristic guidelines for how to manipulate them to represent a belief accurately. Training people how to do this should easily fit into a single-session course, not more than a day if we include motivation, the payoffs, and a bunch of trial runs.