Creativity in UX Design: How AI Can Help—and Hinder—Innovation
New Research on AI’s Impact on UX Creativity and Practical Tips for UXers
One of the concerns we often hear about Artificial intelligence (AI) is the effect its use could have on the way we work and on certain human skills, such as creativity. I recently came across a new study by Doshi and Hauser (2024), which gives us important information about how AI affects creativity. This post explores what this means for UX. We'll look at what creativity means in our field, review earlier research on AI and creativity, and then examine the new study's findings.
What is Creativity in UX?
Sternberg and Lubart (1999) define creativity as making something both new and appropriate. In UX, we use creativity in several ways:
Framing problems: Dorst and Cross (2001) studied how designers approach problems. They found that creative designers don't just solve given problems; they redefine them. This reframing often leads to more innovative solutions. In their study of nine experienced industrial designers, Dorst and Cross observed that the most creative solutions came when designers continually refined both the problem and the solution together.
Generating ideas: Generating many ideas early in the design process is critical in UX. According to Buxton (2007) the key to finding great design solutions is to create a large quantity of ideas first, then select from among them. He suggests techniques like rapid sketching and parallel prototyping to generate diverse design concepts quickly. This approach allows us to explore a wide range of possibilities before committing to a particular direction.
Combining ideas: Designers create novel solutions by combining seemingly dissimilar concepts. Synthesis can be seen as the process of making sense of research data and transforming it into actionable design insights. For instance, a UX designer might combine insights from user interviews with emerging technology trends to create a unique interface concept. This type of creativity is often where the most innovative ideas emerge.
Innovating user experiences: Norman and Verganti (2014) distinguish between incremental and radical innovation in design. They argue that while user-centred design is excellent for incremental improvements, radical innovation often comes from introducing new technologies or meanings. For example, the shift from button-based phones to touchscreen smartphones represented a radical innovation in user experience. Truly innovative UX design often involves rethinking the fundamental ways users interact with technology.
These are only some examples of the importance of creativity in UX. It helps us make experiences that users like, that solve real problems, and that stand out from other designs.
Previous Research on AI and Creativity
Researchers have been studying how AI tools can help human creativity long before ChatGPT was released and have identified a number of potential uses:
AI as a creative partner: Lubart (2005) proposed four ways AI could enhance human creativity: a) As a nanny, managing and nurturing the creative process b) As a pen-pal, offering fresh perspectives from different cultural viewpoints c) As a coach, providing tailored exercises to enhance creative skills d) As a colleague, actively contributing ideas to the creative process. Lubart's work laid the foundation for understanding AI not just as a tool, but as a collaborative partner in creative endeavours.
AI-generated creative stimuli: A study by Han et al. (2018) recruited 119 participants and asked them to complete a number of creative tasks. They compared the effectiveness of human-created, AI-generated, and random stimuli in inspiring creative ideas. Surprisingly, they found that AI-generated stimuli led to ideas that were judged as more original than those inspired by human-created stimuli. The researchers suggested that the novelty and unexpectedness of AI-generated content might push human thinking in new directions.
Human-AI collaborative creativity: Oh et al. (2018) conducted a series of design workshops where humans and AI worked together on creative tasks. They found that AI could complement human creativity in several ways: a) by providing diverse reference materials quickly b) by generating unexpected combinations of design elements c) by helping to break fixed mindsets and encourage divergent thinking However, they also noted challenges, such as the need for designers to develop new skills in prompt engineering and AI output curation.
These studies collectively suggest that AI has significant potential to enhance human creativity in UX (and beyond). However, they were all conducted before the arrival of popular tools like ChatGPT.
Port ChatGPT Findings
Doshi and Hauser (2024) conducted an experiment with 293 writers and 600 readers to examine how AI-generated ideas affect short story writing. Their main findings are summarised and discussed below:
Better individual creativity: Stories written with AI help were rated as more novel and useful.
Helping less creative writers: AI was especially helpful for writers who were less creative on their own.
More professional results: AI-assisted stories seemed better written and more enjoyable.
Less variety overall: Even though individual stories improved, AI-assisted stories were more similar to each other.
Using AI for Creative UX Tasks
How can we apply the research findings to our everyday practice? Here are few suggestions:
Use AI as a creative partner: We can use AI to help generate initial ideas, like how the writers in the study used AI for story ideas. Keep in mind, however, that AI ideas should be a starting point, not finalised.
Avoid making everything too similar: The study found that AI-assisted stories were more alike. To prevent this in UX:
Use AI ideas as inspiration, not final designs.
Try to move beyond what the AI suggests.
Include different human perspectives to ensure uniqueness.
Use AI for learning and skill development: Less creative writers benefited more from AI in the study. In UX teams, newer professionals could use AI to learn and generate initial ideas, while experienced ones can focus on improving these ideas.
Balance speed and originality: AI can make idea generation faster, but don't sacrifice originality for speed. Create processes that encourage designers to critically evaluate and improve AI-generated ideas.
Promote human-AI teamwork: Encourage a team culture where AI is seen as a tool to help human creativity, not replace it. This fits with the idea of "hybrid intelligence" proposed by Dellermann et al. (2019), where human and artificial intelligence work together.
Conclusion
Recent studies give us important insights into how AI affects human creativity. For UX professionals, it shows both the benefits and risks of using AI in creative work. By carefully using AI as a collaborative tool, avoiding making everything too similar, and keeping focus on human-centred design, we can use AI to improve our work.
What do you think? Here are a few reflection questions to consider:
How do you think AI could change your process? Try incorporating AI tools in your next brainstorming session and note how it changes your approach.
Have you noticed any instances of homogenised designs or ideas when using AI? Share your experiences and any strategies you’ve found for preserving originality.
What are your favourite ways to spark creativity in design? Consider trying a mix of AI-generated and non-AI methods to see what yields the best results.
For further exploration, try experimenting with both AI-assisted and manual workflows on your next project and comparing the outcomes. Did AI add something unique, or did it lead to similar patterns? I’d love to hear your experiences and insights in the comments!