A Small Thought on Meaning, Humans, and Machines

I was attending Mongo Boston this week when a simple typographical oddity sent me on an interesting (and luckily brief) train of thought.

The simple occurence of "mb" on a slide to indiciate "megabytes" (it's in this presentation). First amusement because generally 'm' is milli and 'b' is bits. Of course expressing something in millibits is generally useless. So of course a human reading it (unless you're weird like me) doesn't give it a second thought.

Then I thought about the difference in how quickly I (and everyone else) make the right assumptions on what 'mb' in this context really is intended to mean.

And therein lies the huge challenge on the machine side if you're doing data mining and analytics. How do you infer intention automatically and properly, especially when you don't know ahead of time what type of mistakes or inaccuracies are going to be involved? Just the type of thing I've been having fun figuring out over the past year - at least for a particular problem space.

But something else interesting crystallized for me too at a human level. That this auto-correction that we all do so that we don't sit there confused by how one would break something into 200 millibit chunks is also the cause of many of our problems.

We need to be able to jump to conclusions in order to get past "mb" without having to ask a presenter for clarification, but we also are prone to jump to conclusions when we shouldn't - particularly in judging attributing some intention to someone else's action.

Two side of the same coin, one useful and the other problematic. Mostly we can't have one without the other though. Although I guess with practice we hopefully get better at figuring out when to jump and when not to jump. Though I think way too many people never figure out when not to jump.

If there were any typos above I hope your brain autocorrected them for you so you didn't notice.