In August 2020 research (UAL, see credits) I examined what would happen if and when writers use a computer text generator to write articles, giving them only an image prompt.
Joy, Fear, Anger, Sadness – emotion charts are after this introduction.
Can text generation help the human writing process? What do actual writers (the study respondents) think of it all?
The research examines creative and ethical concerns around the use of advanced systems, and how they will (or already do) affect stakeholders, both professional writers and serious amateurs.
Here’s the prompt image:
The results are in but I am still writing it up. So I am now dropping a few things on this blog. These are not the final results as many qualifiers need to be added, statistical definitions, significance, etc. There are over 50 charts, which is why the report is taking a long time.
An online multi-mode sequential study.
One question asked was whether they’d used a text generator before, someone replied ‘my unconscious‘.
82 respondents from my own creativity writing app list (see below), and various professional bodies. So much data. So first, here are some fun boxplots.
These are Occupation (type of writer eg, Student, Poet, Journalist etc. – see the left axis)
plotted against amount of Emotion (joy, anger etc.) in their written feedback to all the questions (summed, then scored using a sentiment analyser). (Amateur and Professional are not attached to the actual occupation, so they are on here too.)
Increased emotion values towards the right side of the chart.
So in the boxplot below, the most joy in responses came from Copywriters.
Perhaps they see a fantastic tool to very quickly make more copy.
The most fear in responses came from Poets and Fiction writers. Perhaps fear of losing their respect as creators of strange new worlds were no one has gone before. Or they see a fantastic tool to very quickly make them unemployed. Other and Scribbler also score on this emotion.
Would appear that Other Scribblers are somewhat angry about something or other. More research needed! Poet and Fiction also score one each here.
Perhaps poets know more sad words.
There’s lots more charts but that will do for today. The actual stats with significance, etc., are for future viewing.
One of the simple charts:
Time Average on Study by Occupation
Game writers were 2 outliers, one person was on it for hours. Perhaps text generation is familiar to games content writers as some games have generated scenarios. Or they have a lot of spare time – to play games.
(Possibly) confirms rumour that songs are written quickly, and that lyricists and poets have flashes of inspiration quickly recorded (and so do copywriters and scientists). Or they were in a hurry to get away…
Game and Songs, Lyrics were added by people within Other definition.
Next blog – the text generation itself.
In the experiment, people were advised to use the generator to make completed works. Several people put my name in the generator, so I became the protagonist in the stories. What!
Such as this Fiction entry:
“It was nice to hear from Geoff again. He is a reminder that life is like an ant’s journey on a blade of grass across a puddle. There is no other side to reach, because the ant is surrounded on all sides. Like an ant, like all of us, Geoff has strategies for paddling. One admires only the paddling, and not especially the termination of the journey. And perhaps that’s what should be the focus of our lives: the paddling. Not journey, not the conclusion, but the sheer determination of the paddling. With a surfer, this analogy would not work, but thinking about it, ants can’t surf.”
People used the OpenAI GPT-2 text generator in a two panel design. I’m releasing this setup as a free AI text editor soon. The generator version is Text Synth by Fabrice Bellard, who is very helpful.