Introduction to AI in Design
Design, a discipline that interlaces creativity and technology to shape our environments, crafts experiences, and transmits messages, has witnessed transformative paradigms that have radically altered its processes and avenues for practice. Changes range from technologically-enhanced work, in which technology assists designers; cybernetic design, where human and machine collaborate; and novel areas of practice, which have critically reviewed the more historical forms of the relationship with technology such as mass production, using disallowed or novel forms of resolution, for instance, recycling and generative design, that retake the long history of Nature in the pursuit of models. However, the infusion of Artificial Intelligence (AI) technologies in design is, by far, one of the most radical and talked-about transformations, whether it is in modelling visual communications, product design, or websites, and discussions regarding its legal, economic, philosophical, social, and environmental ramifications have abounded.
From the commercial point of view, it has been forecast that the use of generative AI in design will be widely embraced in a short lapse of time. It is estimated that around 92% of designers will use such tools in the near future to assist them in carrying out their tasks more efficiently. For us, the reason for this critical interest goes beyond these purely pragmatic considerations. Indeed, as noted before, design is a discipline that combines typology, technology, culture, and economy, and it is precisely in this facet of a technology at the intersection of culture, typology, and economics as to which we would like to describe the effect of AI in design, more specifically, about how AI-driven tools impact one specific area, that is, poster design. Designers and non-designers alike create their communications today on a plethora of online tools, a significant proportion of which embeds Artificial Intelligence technologies, taking care of more specialized tasks while their users perform the simpler steps. While this kind of AI-driven tools has existed for some time in other areas like photography or video editing, more generalized and novel syntactic algorithms and transformer-based models have only recently made their incursions under the most well-known platforms.
Overview of Adobe Express
Summary
Adobe Express, the creative editing tool developed by Adobe, showcases the company’s latest design innovations, heavily based on their AI technology. It arrived at a moment when other graphic design editing tools that provided simpler systems, faster professional results, and with the help of large language models started to compete with Adobe’s main professional editing tools – Photoshop, Illustrator, and InDesign. The research developed on Adobe Express brings insights for the design industry, academia, and the company itself.
The Role of AI in Creative Processes
Even if it takes AI poster maker in minutes, the relationship between AI and human creativity is a complex and invariably debatable one. Nevertheless, technologies are here to be integrated into our media-making relations. The word artificial may indicate that AI is not natural in a way that answers the questions of why and how it produces content. In its absence of subjectivity, some may understand it as a sign of inferiority, yet others may suggest that AI reaches levels of aestheticization of visual products that surpass the majority of media makers. Because many become dependent on the products, or sometimes seek to remain at the surface of the product, Algorithmic Aestheticization seems to be a natural result of the sovereignty of designers. This is the opposite of Algorithmic Imposition, which could be sought to be overcome by design network platforms, as they consider a more collaborative, community-oriented, reflexive-paced production.
Thus, we risk creative processes being deterministic. Yet, we talk about an additional layer that is unique to the human creative factor – the ability to analyze and brainstorm about the influences, and process the cultural meanings of the graphic that result from algorithmic computing and aestheticization. When the creative designer and colleague AI are both positioned to act in a free will, expressive relationship, co-creation may open up a more complex discussion on the ability to print and upload cultural meaning and therefore deal with the values of a collective celebration of community and individuality.
Streamlining the Design Workflow
Like most creative activities, design is a process that requires the investment of time and effort to be successful. Traditionally, the workflow of graphic design involves a number of different steps — brainstorming; the creation of initial drafts; critiques or other forms of feedback; and the incorporation of that feedback in subsequent design iterations. In this section, we describe how their AI poster maker changes the design workflow and affects the nature of the designer’s work. These changes, in turn, may have implications for the work of professional designers, as well as for the quality of work produced using the tool.
Adobe Express employs three classes of AI-driven functionalities that fundamentally streamline certain parts of the design process: Find it Fast, for the searching and sourcing of design assets; Magic Design, for generating design drafts; and Resize, for quickly generating variations of the same design. Collectively, these tools may change the way designers work by allowing them to generate more drafts and design variations faster than ever before. In so doing, they may change the ways in which brainstorming and ideation occur. AI-driven features may also reduce the overall complexity of the design process for novice users, either by automating decisions or minimizing the number of design decisions that they need to make. While Express’s AI tools are primarily built to serve entry-level users, many of their novel affordances challenge the normative conventions of graphic design — especially the imperative for designs to be unique solutions to a given problem. Thus, there are rich avenues for future research on the creative potential of design users with less expertise.
Automating Design Elements
Various design components vary in the work of poster design. The design has to deal with composing several colors into harmony; selecting typefaces that express the intention; identifying image contents that aid the intention; searching for the fitting geometry to express the intention; selecting layout to organize all components; and generally creating a proper atmosphere. Although each component is important, the color choice may feel overly complicated at the start. As selecting colors from a wide range of variations is difficult, the designers often utilize a palette consisting of five to seven colors for a limited region of the poster. To ease this color decision, a system automatically generates color palettes based on the selected image. The selected photo will be used to create a mood for the poster design, and the system finds five color samples that appear in the photo.
A color palette drawn from the poster should also be fitting. In the current version of the Adobe Express AI poster maker, several default and popular template posters are provided. Different from photo-drawing color samples, the palette color selection will be automatic when starting from an existing poster. If the intent is to modify an already created design, the designer is offered only four swatches in grayish typefaces. In this selection case, the only poster-based palette is being used. On the poster, the parameter for palette color samples is maximized, meaning that the common colors in posters correspond to the low-dimensional subspaces in color space and palette generation from the poster should explore this property.
Conclusion
In this study, we examined the effect of AI-driven tools particularly the Adobe Express AI poster maker with emphasis on higher education students, whose main activity is to produce content as future specialists. The study started from the assumption that AI-driven tools would help realize concepts faster, as well as support realism in details, textures, and colors, but AI-driven tools designed posters would be more predictable, as well as poor in visual flow, tension, and balance, and would eliminate all emotional traces from design. The results did not confirm our hypotheses connected to visual flow, emotion, and detailing. However, the results do not give conclusive evidence of AI-driven tools having the upper hand or being a bad option; rather, both alternatives offer similar results in different contexts. Here, the AI-driven tools present as a big help in the repetition of the processes of poster designing and producing but lack essential decision-making capabilities. The aim of our study was to gain a deeper understanding of designing and teaching using generative AI; thus, narrowing our context down to informal and non-commercial sites in digital higher education design. The second aim of the article was to reflect on the design teaching challenges and tools offered by the rise of generative AI in the higher education learning environment in the area of design. As such, more in-depth education studies are required to prepare educators for taking on the role of techno-ethos reporters, design literacies supporters, and pathfinders to preserve education and degree value among employers in a world where the learning environment is coherently changing with the introduction of generative AI.
