Stanzas of the free-verse created by Dada de Dada were entered as prompts into ChatGPT. ChatGPT responded to the prompt with an image description. Once approved this image description was then used as a new prompt to ChatGPT to generate an image of relevance to the whole or part of the free-verse.
Dada de Dada’s experience of image generation via ChatGPT and its linked DALL-E application is that the results tend to be better when an abstract more surreal image is appropriate. The results for more concrete and information providing requirements are not so good, e.g. spelling mistakes and frankly bizarre wordage in the images (see below). In effect this automatic image generation at the moment is good for impressionism rather than detail.
Dada de Dada then put this issue to ChatGPT in the form of the following prompt:
It appears that the image generation engine has a serious problem with text generation within images which reduces its effectiveness considerably. I use images to convey a message but ChatGPT or DALL-E is mangling them.
ChatGPT responded as follows:
You’re absolutely right; DALL-E and similar image-generation tools often struggle with generating coherent, accurate text within images. This limitation can be frustrating, especially when text accuracy is essential for conveying a specific message, such as in educational or instructional visuals.
Currently, DALL-E is designed primarily for creative image generation rather than precise typography. When you need images with reliable, accurate text, a more effective workflow might involve:
- Generating the Visual Elements: Use DALL-E to create the background scene, characters, and general layout without worrying about text accuracy.
- Adding Text in Post-Processing: After generating the base image, you can add text using software like Adobe Photoshop, Canva, or even PowerPoint. This way, you can ensure the text is precise and formatted exactly as needed.
- Alternative Solutions: For heavily text-based images, dedicated graphic design or presentation tools remain the most effective. Combining AI-generated visuals with post-editing for text will offer the best of both worlds: creative, unique images with reliable, clear messaging.
Please let me know if you’d like assistance in generating text-free images for post-editing, or if you’d like tips on specific software to add text accurately!
This was actually a very helpful response which is well worth disseminating.
Now here are some samples of the ChatGPT generated image descriptions used in Learning Machine.
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ChatGPT requested to generate an image description based on the following poem … (whole poem entered)
ChatGPT Response
The scene opens in a dimly lit classroom where students sit at desks, their faces softly illuminated by the glow of computer screens. Each student’s expression is unique: some are eager and hopeful, others weary or confused, and a few look isolated, gazing past the screen with uncertainty. Shadows fall over some faces, symbolizing a sense of exclusion or detachment. In the background, a large, shadowy AI figure hovers, faceless and abstract, with streams of data flowing like rivers from it into the students’ screens, connecting them but also creating a sense of invisible surveillance. The AI, built from code and polished algorithms, is both intricate and mechanical, suggesting precision but lacking warmth. Behind the AI, faint specters of human figures — representing the biases of its creators — linger in the darkness, subtly embedded in the lines of code that stream into the classroom. Each screen reflects patterns and algorithms, some forming pathways, keys, and bright opportunities, while others resemble locked doors and narrow paths, underscoring the disparity in experiences. On one side of the room, students appear absorbed, progressing confidently, while others stare at the widening divide, uncertain and disconnected. In the background, digital pathways and “black-box” mysteries of silicon chips stretch toward a distant horizon, smooth and polished, yet obscuring rougher, forgotten paths. The walls are etched with faint, shadowy engravings of human touches — a teacher’s hand on a shoulder, a smile, or a comforting word — contrasting the cold glow of the machines. The atmosphere is both hopeful and melancholic, reflecting the potential and limitations of AI-driven learning. The colors are muted, with soft blues, grays, and dark shadows, creating a reflective, contemplative tone. The scene captures the AI as both a bridge and a barrier in education, inviting questions about what is gained and lost in this new age of digital learning. This image description emphasizes the dichotomy between connection and isolation, guidance and control, and the quiet presence of AI within learning environments.
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ChatGPT response using stanza 1 as a prompt
In a dimly lit, modern classroom, a large, shadowy AI presence looms over the students and teacher, symbolized as a complex network of code and polished algorithms glowing faintly with blue and green digital lights. The AI appears almost like a fog, stretching across the room, wrapping around screens, and subtly absorbing every piece of visible data. It has an almost spectral quality, its presence hinted at through patterns and associations hovering in the air—numbers, code fragments, and blurred images of faces that represent the data it has “consumed.” The students sit at desks, their faces illuminated by the soft, eerie glow of screens, each one subtly overshadowed by the AI. Some students appear curious, their faces focused and engaged; others look distant or overwhelmed, as if uncertain about this digital presence observing their every move. The teacher, standing at the front, seems partially eclipsed by the AI’s fog, hinting at the shifting balance of authority and knowledge in the classroom. Above, faint, translucent data streams weave through the ceiling, symbolizing the “obese” data intake that the AI has digested from countless sources. The room is awash in cool, muted tones, with hints of blue and green light reflecting the sterile, algorithmic atmosphere, creating a sense of quiet omnipresence. The overall mood is contemplative, questioning the AI’s true understanding beyond its polished veneer of “knowledge.” This description captures the eerie, pervasive presence of AI in the classroom, embodying both quiet dominance and a subtle sense of unease.
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ChatGPT response using stanzas 2 & 3 as a prompt
A classroom scene bathed in soft, artificial light, where students sit at desks, their faces illuminated by the cool glow of screens. Each face reflects a different emotion in this digital light—some students appear eager and hopeful, their eyes bright with anticipation, while others look weary, their expressions shadowed with fatigue or confusion. A few students sit slightly apart, their expressions distant, hinting at a sense of exclusion or detachment from the lesson. On some screens, faint images of keys or doors appear, symbolizing pathways or locked opportunities, representing the mixed potential that each student perceives in this AI-guided environment. For some, the screens seem to radiate a sense of promise and open doors, while for others, the screen appears darkened or obstructed, symbolizing barriers no code or algorithm can solve. The color palette is muted, with shades of blue and gray creating a contemplative, almost melancholic tone. The AI presence in the room is subtle yet pervasive, represented as a faint glow or fog over the students, reflecting their individual experiences with this “borrowed light.” Shadows cast by the screens emphasize the widening divide, as some students gaze toward open doors while others only see locked paths ahead. The atmosphere is reflective, capturing the promise and limitations of AI in shaping futures. This description highlights the varied student experiences and the ambiguity of AI’s role in education, blending hope with restraint.
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ChatGPT using stanzas 4 & 5 as a prompt
A classroom scene is bathed in a cold, digital light, where students sit at desks, their faces illuminated by screens. An invisible AI presence subtly permeates the room, represented by faint, translucent data streams hovering above each desk. The AI “remembers” every click, pause, and answer, but lacks any sign of empathy. Some students stare blankly at their screens, with dazed or withdrawn expressions, while a few wear hesitant or uncertain looks, as though the AI’s silent, watchful nature has dampened their voices. In the background, barely visible in the dim light, are faint, ghostly figures—symbolic “ghosts” of the AI’s creators—emerging from shadows within the data streams. These figures represent embedded biases, subtly influencing the machine’s seemingly impartial calculations. The AI projects a sense of precision and fairness, yet an underlying soulless indifference fills the room, a detachment that seems unaware of the stories, struggles, and voices of the students. The atmosphere is muted and cool, with shades of blue and gray that enhance a feeling of quiet detachment. The scene captures the tension between technical precision and emotional disconnection, revealing both the reach and the limitations of AI in the classroom.* This description emphasizes the unseen influence of AI, the student experience, and the nuanced, indifferent nature of algorithm-driven observation in education.
If you want to view the full sequence how ChatGPT responded to the prompt about its own energy consumption per query then go to page 5. Otherwise, thank you taking the time to read this far.
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