Author: Patrick Marsee

I decided to write this one in light of the recent Pokemon Go’s difficulty slope beginning at level 20.  Everybody has a fairly common conception of the ideal difficulty slope which, naturally, looks like y=e^x for 0<x<1 on a graph (pun totally intended).  But as we all know, difficulty curves don’t always actually happen that way.  As we don’t all know, there are sometimes good reasons, or at least understandable reasons, for this.  Oh, and if the math joke didn’t tip you off, I’ve been watching way too much Numberphile lately, so things are going to get mathy.

All graphs were made in Desmos.

Back in the bad old days of the arcades, many games would begin easy,

This article is a bit shorter than usual for three reasons:

1. Rather than actually making an argument (other than the obvious one: Don’t do artificial difficulty, kids!  Artificial difficulty is not cool!), I’m mostly providing a definition.  This is informative, not persuasive.
2. This is practically an addendum to last week’s article, Difficulty Does Not Imply Quality.
3. Currently, I write these on the day that they’re published, and I’m tired of them always going up at 11:59:59.999 p.m. every time.  Sometime in the future, I will probably start writing these the day before, like I should be doing now.

So, what is artificial difficulty?  Sometimes, a certain mechanic will be flawed in a certain way:

There is one fallacy that I tend to hear once in a while. It goes something along the lines of “It’s not that bad; it’s actually pretty difficult.”  The problem that we have here is that this argument assumes that a game’s difficulty is always proportional to fun (including fear or rage-inducing, for horror or rage games, respectively), and that the relationship is causal (not casual) where difficulty always increases fun.  That isn’t always true.