I have a few collections of fonts totaling six or seven thousand different font samples. Of course there is no useful categorization or naming conventions for it. It’s a flat file. All I can do is randomly walk through it looking for something that catches my eye.
Font.com’s Search By Sight promised that by answering some questions it would give me the font I needed. I’ve thought about this idea before, so I was curious to try.
My thoughts are based on the premise that I am not a type designer and am never going to learn the terms and taxonomy of type design. When I read through the fonts, I have a certain impression I’m looking for (’1950s Heavy Industry’, ‘typewriter’, ‘Neuromancer’, ‘old letter’, ‘Soviet military map’, etc) Don’t expect me to want to search for fonts by type feature (serifs, spacing, etc) — I don’t know what they are, and they wouldn’t necessarily help me find what I am looking for.
That’s why this font finding expert system was so disappointing. To test it I decided I’d use it to help me find a font that looked like it came from a galvanometer made in 1935. It was hopeless. The system just asked me fifteen tedious questions about the font I wanted, but never anything that got to the heart of what I wanted. Honestly, the critical element of a 1935 galvanometer font isn’t how the tail crosses the upper-case ‘Q’. It’s probably something more like the font being relatively thin relative to its height, for being very unadorned, for having a consistent line width, etc.
I’m not taking the piss out of the system, but this is literally the recommendation it gave me:

Sinaloa? Please. This is more like 1925 Ritz-Carlton New Year’s Eve drinking champagne in a Dusenberg font, not austere scientific equipment of the 30’s.
I have a better idea for a font finder. The interface would be much easier, too.
The artist gives some sample text, and then is shown a list of ten fonts of a wide range. Click on any ones that, for any reason, are close to what you are looking for. Then the system, sees what you liked, what you didn’t, and shows you another selection, repeating the cycle, and narrowing down to a few best choices for the font you want.
The trick here is that as the system shows many iterations of fonts that users choose/discard, it can imply groupings of fonts that transcend their type family or other standard categorization methods. The categorization is implicit and invisible.
Problems with this?
- Would take a long time to build up enough iterations to get any meaningful grouping. (6000 fonts, in iterations of 10 each, is 600 iterations to see each font just once). One solution would be for the system to have an underlying understanding of type and be smart enough to show a variety of fonts from widely different font types. I don’t need to see six examples of Arial in my initial iterations.
- If you mingle different users’ iterations, you might just turn the grouping data into a murky, gray soup. The categorization might just be too person-specific.
- You’d have to be careful in your seeding of fonts to the users to prevent them from consistently running down the same choice paths and choosing similar fonts every time.
There are probably some good computational methods for doing this sort of matching stuff, but I think the key issue is building up the database of comparison results.