Certainty/Uncertainty
A Dive Into Visual Perceptions
By: Daniel Iván JiménezThis project was conceived with the aim of creating a typology of certainty and uncertainty in visual language.
To accomplish this, we gathered various drawings from 24 students hailing from different countries. These drawings captured their unique interpretations of certainty and uncertainty. Additionally, we interviewed these students to inquire about the visual artists and painters who influenced their work, resulting in a selection of 12 artists.
Utilizing the insights gained from the students' drawings and their artistic references, we employed Artificial Intelligence to generate a collection of 1153 images. These images now serve as the foundation of our typology, providing a diverse and comprehensive exploration of certainty and uncertainty in visual communication.
CERTAINTY AI-Generated Images
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UNCERTAINTY AI-Generated Images
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OUTCOME
Below you can see some of the images generated with artificial intelligence. In the following video, it is also possible to understand how this typology is formed and the original images that gave way to this work.
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Below you can see some of the images generated with artificial intelligence. In the following video, it is also possible to understand how this typology is formed and the original images that gave way to this work.
VISUAL LANGUAGE
For this work, we use a form of visual communication, where the final audience can understand the results and probe more deeply into how we visually conceive of certainty and uncertainty.
For this work, we use a form of visual communication, where the final audience can understand the results and probe more deeply into how we visually conceive of certainty and uncertainty.
DATA COLLECTION
For collecting the 24 initial images, every student was given the following task:
Using one form: a line, a circle, a square, or a triangle, and one material (such as a pen, paint, a pencil) and one color, create 20 versions of that form with a visual language that moves sequentially from certainty to uncertainty.
This is one example of the collected data:
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After that, we collected the top left and bottom right corner visualizations of certainty and uncertainty from every student. We also asked them about their favorite painter or drawer or a reference in the topic of certainty and uncertainty.
For collecting the 24 initial images, every student was given the following task:
Using one form: a line, a circle, a square, or a triangle, and one material (such as a pen, paint, a pencil) and one color, create 20 versions of that form with a visual language that moves sequentially from certainty to uncertainty.
This is one example of the collected data:
After that, we collected the top left and bottom right corner visualizations of certainty and uncertainty from every student. We also asked them about their favorite painter or drawer or a reference in the topic of certainty and uncertainty.
DATA PROCESSING
In order to generate the images, we used Stable Diffusion and created a new image considering the image created by the student and a prompt text.
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We ran different tries several times to get an output that fulfilled our requests. However, some artists considered by the students had to be left aside since the AI didn't have enough information about them and the changes in the final outcomes were not good enough.
For the rest of the images, we ran them with the same seed and some minor changes in the rest of the parameters that generate the image to maintain consistency among the project (e.g., how much importance was given to the original image).
The rest of the processing was made in Python and Adobe Premiere.
The artist considered in this project were:
Kazimir Malevich
Vincent van Gogh
Hilma af Klint
Mark Rothko
Sol LeWitt
Leonardo da Vinci
Piet Mondrian
Georges Seurat
Alfons Mucha
Egon Schiele
Cai Guo-Qiang
Zhang Daqian
In order to generate the images, we used Stable Diffusion and created a new image considering the image created by the student and a prompt text.
For the rest of the images, we ran them with the same seed and some minor changes in the rest of the parameters that generate the image to maintain consistency among the project (e.g., how much importance was given to the original image).
The rest of the processing was made in Python and Adobe Premiere.
The artist considered in this project were:
Kazimir Malevich
Vincent van Gogh
Hilma af Klint
Mark Rothko
Sol LeWitt
Leonardo da Vinci
Piet Mondrian
Georges Seurat
Alfons Mucha
Egon Schiele
Cai Guo-Qiang
Zhang Daqian
CERTAINTY Original Images
UNCERTAINTY Original Images
DESIGN PROCESS
During our project, we developed different exercises where we tried to understand how everyone conceived via visual language, different things, such as certainty, proximity, or machine-made, for example.
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During our project, we developed different exercises where we tried to understand how everyone conceived via visual language, different things, such as certainty, proximity, or machine-made, for example.
