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Can AI help classify and select typefaces?

Indra Kupferschmidt

Traduit de l’anglais
par l’équipe éditoriale

The first “automated type sorting system” I saw was in 1997 as a pretty green typographer who had newly slithered into type classification, and I wasn’t convinced. Twenty years later, I want to think that artificial intelligence has improved massively and that, with all the ideas and experiments and whatnot behind us we have finally cracked automated type sorting and grouping. As the user interface of IDEO Font Map’s 11 http://fontmap.ideo.com (2017) webpage informs us, it is one of the latest human quests for computed typeface constellations.

What Does the IDEO Font Map Do?

“By leveraging AI and convolutional neural networks to draw higher-vision pattern recognition, we have created a tool that helps designers understand and see relationships across more than 750 webfonts.” 22 IDEO Font Map, ibid. This appears as intriguing as the sea of individual A’s looks pretty at first sight. Click any Google Font 33 Obviously, one of the site’s biggest limitations isthat the selection is only fedby Google Fonts but it is just as obvious why this isthe case so I will leavethis out of my considerations. It is far from easy tomap a comprehensive representation ofthe incredibly dispersed font market and all the different parties one would have to include in this. flying around as astral matter and suggestions of similar fonts appear in the list on the left. Move around the universe by clicking and dragging, zoom in and out and see the letter ‘A’ of typefaces related to your choice displayed adjacent to them. The IDEO Font Map is fun to play with—but alas, completely useless.

As developer Kevin Ho says regarding the project: 

Often, designers fall back on fonts they’ve used before or search within categories like serif, sans-serif, or grotesque. These categories are a useful starting point, but even within a font category there is a wide range of esthetic differences. […] Designers need an easier way to discover alternative fonts with the same esthetic […]. I created a training set of images, one for each font. Leveraging some of IDEO’s in-house expertise, I found that type designers often use the term ‘handgloves’ to examine fonts, so I used this term as well when generating images for the algorithm to use. This allowed each image to contain enough characters to represent the various traits of each font. Once I had a bunch of font images, I used a convolutional neural network […] to generate for each font a list of numbers that represents what the network thought were the notable visual features of the image. 1010 Kevin Ho, “Organizingthe World of Fontswith AI: How we Createda Quick Experimentto Inspire Designers,” Medium, April 2017: http://b-o.fr/ho

In simpler terms, the apparent relation between the A’s placed next to each other is the amount of stroke thickness, stroke contrast and serifs that the system is reading out of an image of one word, ‘handgloves’. Howev…