Clara Kliman-Silver: AI & design: imagining the future of UX
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.
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.
At Optimal Workshop, we're dedicated to building the best user research platform to empower you with the tools to better understand your customers and create intuitive digital experiences. We're thrilled to announce some game-changing updates and new products that are on the horizon to help elevate the way you gather insights and keep customers at the heart of everything you do.
What’s new…
Integration with Figma 🚀
Last month, we joined forces with design powerhouse Figma to launch our integration. You can import images from Figma into Chalkmark (our click-testing tool) in just a few clicks, streamlining your workflows and getting insights to make decisions based on data not hunches and opinions.
What’s coming next…
Session Replays 🧑💻
With session replay you can focus on other tasks while Optimal Workshop automatically captures card sort sessions for you to watch in your own time. Gain valuable insights into how participants engage and interpret a card sort without the hassle of running moderated sessions. The first iteration of session replays captures the study interactions, and will not include audio or face recording, but this is something we are exploring for future iterations. Session replays will be available in tree testing and click-testing later in 2024.
Reframer Transcripts 🔍
Say goodbye to juggling note-taking and hello to more efficient ways of working with Transcripts! We're continuing to add more capability to Reframer, our qualitative research tool, to now include the importing of interview transcripts. Save time, reduce human errors and oversights by importing transcripts, tagging and analyzing observations all within Reframer. We’re committed to build on transcripts with video and audio transcription capability in the future, we’ll keep you in the loop and when to expect those releases.
Prototype testing 🧪
The team is fizzing to be working on a new Prototype testing product designed to expand your research methods and help test prototypes easily from the Optimal Workshop platform. Testing prototypes early and often is an important step in the design process, saving you time and money before you invest too heavily in the build. We are working with customers and on delivering the first iteration of this exciting new product. Stay tuned for Prototypes coming in the second quarter of 2024.
Workspaces 🎉
Making Optimal Workshop easier for large organizations to manage teams and collaborate more effectively on projects is a big focus for 2024. Workspaces are the first step towards empowering organizations to better manage multiple teams with projects. Projects will allow greater flexibility on who can see what, encouraging working in the open and collaboration alongside the ability to make projects private. The privacy feature is available on Enterprise plans.
Questions upgrade❓
Our survey product Questions is in for a glow up in 2024 💅. The team are enjoying working with customers, collecting and reviewing feedback on how to improve Questions and will be sharing more on this in the coming months.
Help us build a better Optimal Workshop
We are looking for new customers to join our research panel to help influence product development. From time to time, you’ll be invited to join us for interviews or surveys, and you’ll be rewarded for your time with a thank-you gift. If you’d like to join the team, email product@optimalworkshop.com
The user research landscape has evolved significantly in recent years, but not all platforms have adapted at the same pace. UserTesting for example, despite being one of the largest players in the market, still operates on legacy infrastructure with outdated pricing models that no longer meet the evolving needs of mature UX, design and product teams. More and more we see enterprises choosing platforms like Optimal, because we represent the next generation of user research and insight platforms: ones that are purpose-built for modern teams that are prioritizing agility, insight quality, and value.
What are the biggest differences between Optimal and UserTesting?
Cost
Optimal has Transparent Pricing: Optimal offers flat-rate pricing without per-seat fees or session units, enabling teams to scale research sustainably. Our transparent pricing eliminates budget surprises and enables predictable research ops planning.
UserTesting is Expensive: In contrast, UserTesting has very high per user fees annually plus additional session-based fees, creating unpredictable costs that escalate the more research your team does. This means that teams often face budget surprises when conducting longer studies or more frequent research.
Return on Investment
The Best Value in the Market: Optimal's straightforward pricing and comprehensive feature set deliver measurable ROI. We offer 90% of the features that UserTesting provides at 10% of the price.
Justifying the Cost of UserTesting: UserTesting's high costs and complex pricing structure make it hard to prove the ROI, particularly for teams conducting frequent research or extended studies that trigger additional session fees.
Technology Evolution
Optimal is Purpose-Built for Modern Research: Optimal has invested heavily over the last few years in features for contemporary research needs, including AI-powered analysis and automation capabilities. Our new Interviews tool exemplifies this innovation, transforming hours of manual video analysis into automated, AI-powered insights that surface key themes, generate highlight reels, and produce timestamped transcripts in a fraction of the time.
UserTesting is Struggling to Modernize: UserTesting's platform shows signs of aging infrastructure, with slower performance and difficulty integrating modern research methodologies. Their technology advancement has lagged behind industry innovation.
Platform Integration
Built by Researchers for Researchers: Optimal has built from the ground up a single, cohesive platform without the complexity of merged acquisitions, ensuring consistent user experience and seamless workflow integration.
UserZoom Integration Challenges: UserTesting's acquisition of UserZoom has created platform challenges that continue to impact user experience. UserTesting customers report confusion navigating between legacy systems and inconsistent feature availability and quality.
Participant Panel Quality
Flexibility = Quality: Optimal prioritizes flexibility for our users, allowing our customers to bring their own participants for free or use our high-quality panels, with over 100+ million verified participants across 150+ countries who meet strict quality standards.
Poor Quality, In-House Panel: UserTesting's massive scale has led to participant quality issues, with researchers reporting difficulty finding high-quality participants for specialized research needs and inconsistent participant engagement.
Customer Support Experience
Agile, Personal Support: At Optimal we pride ourselves on our fast, human support with dedicated account management and direct access to product teams, ensuring fast and personalized support.
Impersonal, Enterprise Support: In contrast, users report that UserTesting's large organizational structure creates slower support cycles, outsourced customer service, and reduced responsiveness to individual customer needs.
The Future of User Research Platforms
The future of user research platforms is here, and smart teams are re-evaluating their platform needs to reflect that future state. What was once a fragmented landscape of basic testing tools and legacy systems has evolved into one where comprehensive user insight platforms are now the preferred solution. Today's UX, product and design teams need platforms that have evolved to include:
Advanced Analytics: AI-powered analysis that transforms data into actionable insights
Flexible Recruitment: Options for both BYO, panel and custom participant recruitment
Transparent Pricing: Predictable costs that scale with your needs
Responsive Development: Platforms that evolve based on user feedback and industry trends
Platforms Need to Evolve for Modern Research Needs
When selecting a vendor, teams need to choose a platform with the functionality that their teams need now but also one that will also grow with the needs of your team in the future. Scalable, adaptable platforms enable research teams to:
Scale Efficiently: Grow research activities without exponential cost increaeses
Embrace Innovation: Integrate new research methodologies and analysis techniques as well as emerging tools like AI
Maintain Standards: Ensure consistent participant, data and tool quality as the platform evolves
Stay Responsive: Adapt to changing business needs and market conditions
The key is choosing a platform that continues to evolve rather than one constrained by outdated infrastructure and complex, legacy pricing models.
Natalie and Lulu have forged a unique team culture that focuses on positive outputs (and outcomes) for their app’s growing user base. In doing so, they turned the traditional design approach on its head and created a dynamic and supportive team.
Natalie, Director of Design at Hatch, and Lulu, UX Design Specialist, recently spoke at UX New Zealand, the leading UX and IA conference in New Zealand hosted by Optimal Workshop, on their concept of “radical collaboration”.
In their talk, Nat and Lulu share their experience of growing a small app into a big player in the finance sector, and their unique approach to teamwork and culture which helped achieve it.
Background on Natalie Ferguson and Lulu Pachuau
Over the last two decades, Lulu and Nat have delivered exceptional customer experiences for too many organizations to count. After Nat co-founded Hatch, she begged Lulu to join her on their audacious mission: To supercharge wealth building in NZ. Together, they created a design and product culture that inspired 180,000 Kiwi investors to join in just 4 years.
Radical Collaboration - How teamwork makes the dream work 💪💪💪
Nat and Lulu discuss how they nurtured a team culture of “radical collaboration” when growing the hugely popular app Hatch, based in New Zealand. Hatch allows everyday New Zealanders to quickly and easily trade in the U.S. share market.
The beginning of the COVID pandemic spelled huge growth for Hatch and caused significant design challenges for the product. This growth meant that the app had to grow from a baby startup to one that could operate at scale - virtually overnight.
In navigating this challenge, Nat and Lulu coined the term radical collaboration, which aims to “dismantle organizational walls and supercharge what teams achieve”. Radical collaboration has six key pillars, which they discuss alongside their experience at Hatch.
Pillar #1: When you live and breathe your North star
Listening to hundreds of their customers’ stories, combined with their own personal experiences with money, compelled Lulu and Nat to change how their users view money. And so, “Grow the wealth of New Zealanders” became a powerful mission statement, or North Star, for Hatch. The mission was to give people the confidence and the ability to live their own lives with financial freedom and control. Nat and Lulu express the importance of truly believing in the mission of your product, and how this can become a guiding light for any team.
Pillar #2: When you trust each other so much, you’re happy to give up control
As Hatch grew rapidly, trusting each other became more and more important. Nat and Lulu state that sometimes you need to take a step back and stop fueling growth for growth’s sake. It was at this point that Nat asked Lulu to join the team, and Nat’s first request was for Lulu to be super critical about the product design to date - no feedback was out of bounds. Letting go, feeling uncomfortable, and trusting your team can be difficult, but sometimes it’s what you need in order to drag yourself out of status quo design. This resulted in a brief hiatus from frantic delivery to take stock and reprioritize what was important - something that can be difficult without heavy doses of trust!
Pillar #3: When everyone wears all the hats
During their journey, the team at Hatch heard lots of stories from their users. Many of these stories were heard during “Hatcheversery Calls”, where team members would call users on their sign-up anniversary to chat about their experience with the app. Some of these calls were inspiring, insightful, and heartwarming.
Everyone at Hatch made these calls – designers, writers, customer support, engineers, and even the CEO. Speaking to strangers in this way was a challenge for some, especially since it was common to field technical questions about the business. Nevertheless, asking staff to wear many hats like this turned the entire team into researchers and analysts. By forcing ourselves and our team outside of our comfort zone, we forced each other to see the whole picture of the business, not just our own little piece.
Pillar #4: When you do what’s right, not what’s glam
In an increasingly competitive industry, designers and developers are often tempted to consistently deliver new and exciting features. In response to rapid growth, rather than adding more features to the app, Lulu and Nat made a conscious effort to really listen to their customers to understand what problems they needed solving.
As it turned out, filing overseas tax returns was a significant and common problem for their customers - it was difficult and expensive. So, the team at Hatch devised a tax solution. This solution was developed by the entire team, with almost no tax specialists involved until the very end! This process was far from glamorous and it often fell outside of standard job descriptions. However, the team eventually succeeded in simplifying a notoriously difficult process and saved their customers a massive headache.
Pillar #5: When you own the outcome, not your output.
Over time Hatch’s user base changed from being primarily confident, seasoned investors, to being first-time investors. This new user group was typically scared of investing and often felt that it was only a thing wealthy people did.
At this point, Hatch felt it was necessary to take a step back from delivering updates to take stock of their new position. This meant deeply understanding their customers’ journey from signing up, to making their first trade. Once this was intimately understood, the team delivered a comprehensive onboarding process which increased the sign-up conversion rate by 10%!
Pillar #6: When you’re relentlessly committed to making it work
Nat and Lulu describe a moment when Allbirds wanted to work with Hatch to allow ordinary New Zealanders to be involved in their IPO launch on the New York stock exchange. Again, this task faced numerous tax and trade law challenges, and offering the service seemed like yet another insurmountable task. The team at Hatch nearly gave up several times during this project, but everyone was determined to get this feature across the line – and they did. As a result, New Zealanders were some of the few regular investors from outside the U.S that were able to take part in Albirds IPO.
Why it matters 💥
Over four years, Hatch grew to 180,000 users who collectively invested over $1bn. Nat and Lulu’s success underscores the critical role of teamwork and collaboration in achieving exceptional user experiences. Product teams should remember that in the rapidly evolving tech industry, it's not just about delivering the latest features; it's about fostering a positive and supportive team culture that buys into the bigger picture.
The Hatch team grew to be more than team members and technical experts. They grew in confidence and appreciated every moving part of the business. Product teams can draw inspiration from Hatch's journey, where designers, writers, engineers, and even the CEO actively engaged with users, challenged traditional design decisions, and prioritized solving actual user problems. This approach led to better, more user-centric outcomes and a deep understanding of the end-to-end user experience.
Most importantly, through the good times and tough, the team grew to trust each other. The mission weaved its way through each member of the team, which ultimately manifested in positive outcomes for the user and the business.
Nat and Lulu’s concept of radical collaboration led to several positive outcomes for Hatch:
It changed the way they did business. Information was no longer held in the minds of a few individuals – instead, it was shared. People were able to step into other people's roles seamlessly.
Hatch achieved better results faster by focusing on the end-to-end experience of the app, rather than by adding successive features.
The team became more nimble – potential design/development issues were anticipated earlier because everyone knew what the downstream impacts of a decision would be.
Over the next week, Lulu and Nat encourage designers and researchers to get outside of their comfort zone and:
Visit customer support team
Pick up the phone and call a customer
Challenge status quo design decisions. Ask, does this thing solve an end-user problem?
