Chris Ashton

week11y issue 147

Your weekly frequent11y newsletter, brought to you by @ChrisBAshton:

What makes writing more readable?

A fantastic deep dive into how to write in ‘plain language’. The entire article is written in normal literary style, but every paragraph has a plain language equivalent adjacent to it, which you can toggle to switch to.

The interactivity of this article is a joy to play with and really helps to demonstrate the processes that go into translating text into plain language. We see Rebecca Monteleone’s thought process behind how she translated an example paragraph into plain language.

We then learn about the Flesch-Kincaid formula, which measures readability based on the length of words and sentences. It’s not hugely effective: “the dun fox cleared that slouch of a dog at full tilt” is at a 0.89 (1st grade) grade reading level, compared to the allegedly more difficult 2.34 (2nd grade) reading level for “the quick brown fox jumped over the lazy dog”.

The Dale-Chall Readability Formula considers the proportion of “difficult” words instead. This, similarly, isn’t all that effective. “The quick brown fox jumped over the lazy dog” is at 0.45 (4th grade or below) according to that formula, but drops to 0.25 (also 4th grade or below) by simply prefixing the sentence with “Yes!”.

Finally there is the Lexile Framework for Reading, which is a proprietary scoring system whose exact algorithms are unclear. But it oddly rates The Grapes of Wrath as far easier to read than The Library Mouse (32 page children’s book).

Formulas aren’t a great measure of ease of reading:

None consider how well organized the information is, or whether the sentences and paragraphs are coherent. None consider the role of grammatical tense. None account for the explanation of acronyms and jargon. None would balk at Jack Torrance’s rambling and meaningless draft in The Shining, endlessly repeating “All work and no play makes Jack a dull boy.”

Well worth a read.

How to use the accessibility tree for a11y testing

Giovani Camara uses a simile to describe the accessibility tree’s relationship to the DOM as being like a ‘filter’ for your emails: the DOM contains a lot of information, but the accessibility tree shows only the data related to accessibility.

This article is very short – it describes how to access the accessibility tree in Chrome DevTools, which is to right-click, Inspect, click the double arrow in the bottom right panel and select Accessibility.

What’s more interesting is the embedded video (10m) where Giovani demonstrates this visually, and then goes on to show how he uses the accessibility tree as a development aid, by using it to examine the W3 WAI ARIA example implementation of tabs. He explains how to use it to see the computed properties, ARIA attributes and the child/parent relationships of a component.

AI-Generated Images from AI-Generated Alt Text

Adrian Roselli explores the topic of AI and accessibility, as claims are being made that AI could make up for things like a lack of human-provided alt text. He feeds several different images into the following browsers/software and has them generate alt text descriptions for the images:

  • Microsoft Edge
  • Google Chrome
  • Apple iOS VoiceOver Recognition
  • Microsoft Office

He then feeds the generated alt text into AI image generators, Craiyon and Midjourney, to see what they create from the alt text. He does the same with his own manually created alt text, to compare the image outputs.

This is an exercise to highlight that automated alt text still isn’t particularly good, and that the quality of alt text greatly influences the quality of generated images (a metaphor for how a screen reader user uses the web and relies on good alt text to be able to properly understand an image).

There’s a follow-on article, AI-Generated Images from AI-Generated Prompts, which explores the idea of feeding images into tools that then spout out AI prompts you can use to try to generate new images (very cyclical!).

Also cool to note that the opening image of each article was generated by AI, using the title of the post as the seed phrase.

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