What is Good Design in the Age of AI? | Figma Blog

🌈 Abstract

The article discusses the role of design in the age of AI, exploring how designers can unlock the potential of AI to create rich, intuitive, and user-centric experiences. It highlights the importance of grounding design work in the principles of empathy, creativity, and solving real user needs, rather than chasing the latest trends or building for technology's sake.

🙋 Q&A

[01] Establishing Algorithmic Foundations

1. How did the Figma team approach teaching AI the mechanics of good design?

• The Figma team realized they couldn't just hand off an all-encompassing set of design rules to the AI, as it's impossible to define every detail of "good" design into finite guidelines.
• Instead, they had to reduce the principles of good design to a small but mighty set of guidelines that hold true for any UI, focusing on communicating the highest-leverage design truths to the AI.
• By having the AI master the foundational compositions first, rather than endless permutations, they were able to establish a solid algorithmic baseline as the new creative starting line.

2. What is the role of the designer in this new paradigm?

• As AI will always produce the standard, most conventional approach, it will be the role of the designer to bring new ideas to the table. AI trained on the past cannot invent the future.

[02] Evolving Skill Sets and Collaboration

1. How will the roles of designers and engineers evolve in the age of AI?

• Designers may acquire more technical knowledge to better understand the capabilities and limitations of AI tools, while engineers may develop a stronger grasp of design principles to create more user-centric solutions.
• The boundaries between disciplines will blur, leading to the emergence of a "product builder" archetype - creative individuals who can leverage AI to realize their visions with ease and fluidity.
• However, there will still be a place for specialized roles and skills, as designers will continue to craft exceptional user experiences, and engineers will focus on building robust and scalable systems.

2. How will the design-development process change with the integration of AI?

• AI might assist by generating layout suggestions or code snippets, but the final creative direction and technical implementation will still rely on human expertise.
• As AI becomes more integrated into this process, there can be a more seamless loop between design and development.

[03] Pragmatic and High-Impact AI Integration

1. What are some examples of how AI can be leveraged in pragmatic and high-impact ways?

• AI-assisted search can help designers instantly retrieve the right assets, components, or design explorations just by describing them in plain language or uploading a screenshot.
• This can help designers spend less time searching and more time focusing on the essence of their craft - going deeper on polish and delivering better-informed, more seamless experiences.

2. What is the key to successfully integrating AI into existing design processes?

• The key is to mesh AI into existing processes in a thoughtful, incremental way, focusing on the readily attainable value that AI can reliably provide right now.
• Features like AI-assisted search and automated layer renaming may seem small, but they can provide real, tangible benefits to everyday workflows.
• This incremental approach paves the way for more advanced AI applications in the future, ensuring that designers don't overreach and risk disappointment in the short term.

[04] Towards Co-Creation

1. What is the "co-creation" model that the Figma team is exploring?

• Rather than siloed tools spitting out context-free outputs, the team is exploring AI that intelligently anticipates designers' needs and adapts in a complementary way.
• The key is for the AI to be aware of the designer's specific goals, established design systems, past work, and project contexts, so that it can enhance the creative process rather than simply automating it.

2. What are some examples of how this co-creation model could work in practice?

• The AI could instantly grasp the meeting notes, priorities, and action items from a planning session, and then intelligently suggest next steps like creating a roadmap or a presentation deck, infusing those outputs with the team's actual styles, methods, and visual language.
• The AI would not just regurgitate generic templates, but extend the team's specific way of working, truly collaborating with the designers.