Table of Contents
Question
Your company produces science fiction and fantasy graphic novels. One of your top illustrators has developed a style that is very strongly associated with your brand. Your company decides to create a generative AI model to mimic their illustrations. This new model can create new graphics in their style in seconds. Now the company will have better control over their brand and increase productivity.
What is one of the main challenges with this approach?
A. The generative AI model will always need to be further trained, so it doesn’t save any time.
B. It will “normalize mediocrity”—the graphics will look the same and lack a creative spark.
C. It is currently illegal in the United States to mimic the style of working illustrators.
D. Current generative AI models are not doing a very good job mimicking creative illustrators.
Answer
B. It will “normalize mediocrity”—the graphics will look the same and lack a creative spark.
Explanation
The correct answer to the question is B. It will “normalize mediocrity”—the graphics will look the same and lack a creative spark. Here’s a detailed explanation to elaborate on this answer:
The described approach of using a generative AI model to mimic the illustrations of a top illustrator in order to have better control over the brand and increase productivity may indeed pose a significant challenge, which is highlighted in option B:
B. It will “normalize mediocrity”—the graphics will look the same and lack a creative spark: When a generative AI model is used to mimic the style of a specific illustrator, there is a risk of producing graphics that lack originality and creative uniqueness.
While the model may be able to replicate the technical aspects of the illustrator’s style, it may struggle to capture the true essence, artistic vision, and creative spark that makes the illustrator’s work stand out.
The strength and appeal of the top illustrator’s style lie not only in the technical execution but also in their artistic interpretation, unique ideas, and creative choices. By solely relying on a generative AI model to replicate their style, there is a possibility that the graphics produced may become repetitive and lack the distinctiveness and originality that are crucial for the success of a brand.
It is important to recognize that creativity and artistic expression are not easily replicable by AI models alone. While AI can assist in generating content, it is challenging for AI models to capture the nuances, subtleties, and creative intuition that human artists bring to their work.
Thus, there is a risk that relying solely on the generative AI model may lead to a loss of the artist’s unique touch and the potential to “normalize mediocrity” in the graphics produced.
Options A and D are incorrect because they do not directly address the challenge mentioned in the scenario:
A. The generative AI model will always need to be further trained, so it doesn’t save any time: While it is true that generative AI models may require ongoing training and refinement, this does not address the main challenge mentioned in the scenario, which is related to the potential lack of creative spark and originality in the graphics produced.
D. Current generative AI models are not doing a very good job mimicking creative illustrators: This option touches on the performance of current generative AI models, but it does not address the challenge of “normalizing mediocrity” or the potential loss of creative uniqueness when relying solely on AI-generated graphics.
In summary, the main challenge with the approach of using a generative AI model to mimic the style of a top illustrator is the risk of “normalizing mediocrity.” The graphics produced may lack the creative spark, originality, and artistic vision that make the illustrator’s work unique and captivating. It is crucial to strike a balance between leveraging AI technology and preserving the distinctive qualities of an artist’s work to maintain the brand’s creative identity and artistic excellence.
Reference
- DALL·E 2 (openai.com)
- How Generative AI Is Changing Creative Work (hbr.org)
- Top 35 Generative AI Tools by Category (Text, Image…) [2023] (aimultiple.com)
- Generative AI: Advantages, Disadvantages, Limitations, and Challenges (fact.technology)
- How generative models can transform the way we discover | IBM Research Blog
- Generative AI Has an Intellectual Property Problem (hbr.org)
- What is generative AI, and will it replace human creativity? – Addepto
- How Generative AI Can Augment Human Creativity (hbr.org)
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