In the last few years, the influence of AI has steadily been expanding into various aspects of design. In early 2023, that expansion exploded. AI tools and features are now everywhere, and there are two ways designers commonly react to it:
- With enthusiasm for how they can use it to make their jobs easier
- With skepticism over how reliable it is, or even fear that it could replace their jobs
Google UX researcher Clara Kliman-Silver is at the forefront of researching and understanding the potential impact of AI on design into the future. This is a hot topic that’s on the radar of many designers as they grapple with what the new normal is, and how it will change things in the coming years.
Clara’s background
Clara Kliman-Silver spends her time studying design teams and systems, UX tools and designer-developer collaboration. She’s a specialist in participatory design and uses generative methods to investigate workflows, understand designer-developer experiences, and imagine ways to create UIs. In this work, Clara looks at how technology can be leveraged to help people make things, and do it more efficiently than they currently are.
In today’s context, that puts generative AI and machine learning right in her line of sight. The way this technology has boomed in recent times has many people scrambling to catch up - to identify the biggest opportunities and to understand the risks that come with it. Clara is a leader in assessing the implications of AI. She analyzes both the technology itself and the way people feel about it to forecast what it will mean into the future.
Contact Details:
You can find Clara in LinkedIn or on Twitter @cklimansilver
What role should artificial intelligence play in UX design process? 🤔
Clara’s expertise in understanding the role of AI in design comes from significant research and analysis of how the technology is being used currently and how industry experts feel about it. AI is everywhere in today’s world, from home devices to tech platforms and specific tools for various industries. In many cases, AI automation is used for productivity, where it can speed up processes with subtle, easy to use applications.
As mentioned above, the transformational capabilities of AI are met with equal parts of enthusiasm and skepticism. The way people use AI, and how they feel about it is important, because users need to be comfortable implementing the technology in order for it to make a difference. The question of what value AI brings to the design process is ongoing. On one hand, AI can help increase efficiency for systems and processes. On the other hand, it can exacerbate problems if the user's intentions are misunderstood.
Access for all 🦾
There’s no doubt that AI tools enable novices to perform tasks that, in years gone by, required a high level of expertise. For example, film editing was previously a manual task, where people would literally cut rolls of film and splice them together on a reel. It was something only a trained editor could do. Now, anyone with a smartphone has access to iMovie or a similar app, and they can edit film in seconds.
For film experts, digital technology allows them to speed up tedious tasks and focus on more sophisticated aspects of their work. Clara hypothesizes that AI is particularly valuable when it automates mundane tasks. AI enables more individuals to leverage digital technologies without requiring specialist training. Thus, AI has shifted the landscape of what it means to be an “expert” in a field. Expertise is about more than being able to simply do something - it includes having the knowledge and experience to do it for an informed reason.
Research and testing 🔬
Clara performs a lot of concept testing, which involves recognizing the perceived value of an approach or method. Concept testing helps in scenarios where a solution may not address a problem or where the real problem is difficult to identify. In a recent survey, Clara describes two predominant benefits designers experienced from AI:
- Efficiency. Not only does AI expedite the problem solving process, it can also help efficiently identify problems.
- Innovation. Generative AI can innovate on its own, developing ideas that designers themselves may not have thought of.
The design partnership 🤝🏽
Overall, Clara says UX designers tend to see AI as a creative partner. However, most users don’t yet trust AI enough to give it complete agency over the work it’s used for. The level of trust designers have exists on a continuum, where it depends on the nature of the work and the context of what they’re aiming to accomplish. Other factors such as where the tech comes from, who curated it and who’s training the model also influences trust. For now, AI is largely seen as a valued tool, and there is cautious optimism and tentative acceptance for its application.
Why it matters 💡
AI presents as potentially one of the biggest game-changers to how people work in our generation. Although AI has widespread applications across sectors and systems, there are still many questions about it. In the design world, systems like DALL-E allow people to create AI-generated imagery, and auto layout in various tools allows designers to iterate more quickly and efficiently.
Like many other industries, designers are wondering where AI might go in the future and what it might look like. The answer to these questions has very real implications for the future of design jobs and whether they will exist. In practice, Clara describes the current mood towards AI as existing on a continuum between adherence and innovation:
- Adherence is about how AI helps designers follow best practice
- Innovation is at the other end of the spectrum, and involves using AI to figure out what’s possible
The current environment is extremely subjective, and there’s no agreed best practice. This makes it difficult to recommend a certain approach to adopting AI and creating permanent systems around it. Both the technology and the sentiment around it will evolve through time, and it’s something designers, like all people, will need to maintain good awareness of.
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