Dall-E, despite its impressive capabilities, falls short in certain areas that make human designers invaluable. One key limitation is its inability to fully understand the nuances of a target audience. Human designers have the ability to take into account factors such as cultural context, local preferences, and specific audience demographics, which are critical in creating designs that resonate with the intended audience.
Another important aspect where Dall-E falls behind is the lack of experience and intuition that human designers bring to the table. Human designers have years of experience and a deep understanding of design principles, aesthetics, and trends, which they use to create visually appealing and effective designs. They can also rely on their intuition to make creative decisions that may not be easily captured by an AI system.
Furthermore, human designers have the ability to adapt and turn substandard briefs into remarkable designs, while Dall-E heavily relies on the quality of input or brief it receives. Human designers can also establish and maintain consistent brand identities across various design assets, whereas Dall-E’s generated images may lack consistency with a brand’s identity.
Dall-E, created by OpenAI, is a cutting-edge neural network-powered system that transforms textual descriptions into digital images. Developed by the same team behind ChatGPT, Dall-E leverages a vast dataset of images to generate a wide range of pictures, from simple objects to intricate scenes, including anthropomorphic and surreal imagery. Its remarkable capabilities include rapid image generation, even for complex concepts that may challenge human designers. As a valuable tool, Dall-E can spark new ideas and inspiration for designers, streamline repetitive design tasks like image creation, and ultimately optimize the design process in terms of time and cost savings.
Despite its impressive capabilities, Dall-E does have certain limitations. Notably, it may not be tailored enough to produce designs specifically for marketing purposes. As it relies on human inputs, the quality of its output is contingent upon the quality of the input or brief, similar to human designers. However, human designers can leverage their experience and intuition to transform a mediocre brief into an exceptional design, whereas Dall-E may require multiple refinements to achieve the desired final image.
Human designers possess the unique ability to comprehend the preferences and characteristics of the target audience and the client, enabling them to create designs that effectively appeal to both parties. On the other hand, Dall-E relies solely on textual input to generate images, which means it lacks the capability to capture the nuances of the target audience in the same way.
To exemplify this distinction, an experiment was conducted by requesting Dall-E to create a Facebook ad for the 2023 Toyota Hilux, incorporating a monthly payment price of R8,000. Although the AI came close, the resulting designs did not meet the standards to be presented as advertisements for clients. This underscores the limitations of Dall-E in accurately capturing the complex requirements of marketing designs and the advantages of human designers’ ability to comprehend and cater to the specific needs of the target audience and clients.
Indeed, Dall-E’s limitations become evident in practical scenarios. For instance, in an experiment where Dall-E was tasked with creating a Facebook ad for the 2023 Toyota Hilux, it accurately captured the appearance of the vehicle but failed to include the crucial monthly payment price and overlooked the corporate identity of the Toyota brand. Similarly, in another example where Dall-E was briefed to design a website banner for Black Friday to advertise wedding rings, the AI struggled with incorporating text onto the images. While Dall-E managed to grasp the general look and feel of such banners, the generated outputs were not suitable for a live campaign. This underscores that human designers possess the ability to create consistent brand identities across all design assets, while Dall-E’s unique images may not always align with the brand’s established identity.
Human designers excel in attention to detail, resulting in higher-quality designs that effectively fulfill the client’s requirements. Additionally, human designers possess an understanding of context, nuance, and locality, which enables them to comprehend references that are specific to certain regions or cultures. For example, a South African designer would likely understand that a reference to the “Dombolo” refers to the legendary Mazda 323 from the 1980s. In contrast, Dall-E may struggle to interpret such references accurately, resulting in irrelevant images that may not impress the intended audience on social media platforms like Twitter.
Despite the remarkable advancements in AI, including the impressive capabilities demonstrated by Dall-E, it is clear that there is still room for improvement. Human designers possess a level of expertise and understanding of nuances that are not yet fully replicated in AI systems, indicating that there is still progress to be made in bridging the gap between human creativity and AI-generated designs.
The potential of this technology lies in its ability to be trained with more specific images, including a brand’s corporate identity and previous designs, to build a comprehensive library that can better respond to user prompts, making it a valuable tool for individuals without design skills. This has the potential to be a game-changer for international brands that rely on a consistent corporate identity across multiple agencies worldwide.
AI-supported systems like Dall-E can enable franchisees to easily generate artwork that aligns with the brand’s corporate identity based on text prompts, empowering them to quickly and efficiently produce designs that meet the brand’s standards. This could lead to significant reductions in turnaround times, increased efficiency, and streamlined design processes for companies globally.
As AI technologies continue to advance, they are likely to become increasingly valuable tools for businesses seeking to improve their branding and design processes. However, it is unlikely that AI-driven technology, including Dall-E, will replace human designers in the near future. Dylan Balouza, Head of Digital Operations at CBR Marketing.