looking at typography developed by artificial intelligence is like looking at letters submerged in deep water, deformed and blurred. It looks like a copy of a copy of a copy. The words are barely recognizable, but the original form has been lost. The AI typography is, charitably, bad.
A recent example of this phenomenon is Word as image for semantic typographya paper in which anonymous authors propose a tool that transforms text into an image of what that text represents. Type “yoga,” for example, and the word will appear adorned with wobbly vectors of women stretching. The resulting jagged, blurry text is emblematic of the AI type’s shortcomings. This experiment sacrifices readability and accessibility, two of the cornerstones of good type design, in a misguided attempt to innovate. However, we could hardly expect much more from AI, when it only has a superficial understanding of how humans read.
As a designer and typographer for over 10 years, I have watched the progress of AI-powered design with a mix of playful curiosity and subtle awe. When it comes to typography, it’s becoming clear that AI innovations are targeting the wrong ideas. Right now some are toying with the use of this technology to try and redefine the visual language, in the case of our set of Latin letters, one that has been around for over 2000 years, but ultimately this is a path non-viable. The key to putting AI typography on a better and more accessible path is to think of it as assistive rather than generative.
word as picture Not Novel After the Industrial Revolution brought machines to the forefront of manufacturing, designers in post-war Europe began to explore how technology might shape the future of art and type design. In his 1920 book Sprache and Schrift, engineer Walter Porstmann proposed that the language could be amplified by introducing a character for each sound, ordered by pitch, sound duration, strength, and voice. Later, László Moholy-Nagy at the Bauhaus adopted and refined Porstmann’s concept, anticipating in 1925 that typography would be supplanted by advances in film and especially sound. In response, he suggested, typography needed to evolve to express these new technologies.
Perhaps the most interesting response to the Moholy-Nagy phonetic proposal was that of Kurt Schwitters. systemschrift. First published in 1927, it was a unicase alphabet that used character weights to denote phonetic stress, conveying vowel sounds boldly. This experiment was notable for its visual eccentricity; he stood out in a school that favored a more standardized typeface. But that doesn’t mean it was effective. Not even Schwitters used these phonetic elements in his own work.
Looking at both AI type and these 20th century typographic innovations, one can reasonably ask: Who is this for? Readers, certainly not. But like previous experiments that melded technology and typography, it’s possible that AI could lead designers to create better type. If AI can be used to aid typographers, rather than trying to supplant them, generative models could just be a bump in the road to a more efficient and accessible use of this technology as a tool to assist in the type design process.
Think about how the digital revolution put typography in the hands of everyone with a computer and made the creation process more efficient than ever. AI could be applied in a similar way, helping typographers and making their work more accessible. But it’s important to keep in mind where to place that assistance.
—————————————————-
Source link