When AI Meets User Experience: Challenges Linger, Opportunities Shine Ever Brighter

While it’s natural to feel overwhelmed or even intimidated by the sheer pace at which Artificial Intelligence (AI) is touching upon every sphere of our personal and professional lives, a perspective shift is what is required to make the most of what technology has to offer today. More often than not, change is uncomfortable, but it can also create new possibilities. How does this extend to UX design? What if embracing AI allows designers to focus on things they never had the chance to do before? Up until now, their attention has been diverted from exploring things they would have liked to do in favor of tasks that must be completed.

The World Economic Forum projects that from 2020 to 2025, the evolution of AI will lead to the disruption of 85 million jobs worldwide, while also generating 97 million new job opportunities. This shift aligns with the growth projections for web developers and digital designers, where the U.S. Bureau of Labor Statistics anticipates a 16% increase in employment from 2022 to 2033, significantly outpacing the average growth rate. That said, in a future where there is a balanced sharing of work between humans and machines, the demand for human skills is likely to see a remarkable increase.

It’s a call to step up, upskill, and reskill

We’re entering an era where being merely a ‘code monkey’ is insufficient. To thrive, professionals must evolve into higher-level thinkers and curators, cultivating an understanding of what constitutes good and bad design. Complacency will find no place in the future— all professionals will need to look at their work with fresh pairs of eyes and approach the dynamic field of AI with an open mindset. That is to say, it’s necessary that we identify ways to work alongside AI and not away from it. What tasks could be automated and what AI tools align with your design goals? What are the limitations of AI? Continuous learning is the way to go.

So, how can UX designers utilize AI?

To make the most out of a human-machine collaboration, consider the latter as a facilitator, not a replacement. In doing so, UX designers can make use of AI for any stage of the design process, right from brainstorming ideas to fine tuning the final product.

One of the most beneficial aspects of incorporating AI into a UX designer’s toolkit is the potential to automate routine tasks, thereby expediting their workflow. For instance, user research is a consequential element of the design process, but it’s also quite time consuming. With the help of AI, tasks like interview debriefs can be streamlined, as customer interviews can be quickly transformed into actionable insights. Similarly, involving AI in categorizing user actions, anticipating future behaviors, and distilling insights from vast amounts of user data allows designers to focus more of their attention and time on other aspects of the design process.

Thanks to the potential of AI algorithms to process information of this magnitude, analyzing consumer sentiments (from social media platforms, forums, etc.) identifying trends, mapping and optimizing user journeys and so on will become significantly easier. This way, AI can potentially make the UX design process more data-driven, where design choices are based on empirical evidence rather than assumptions.

UX design, being an iterative process, can hugely benefit from automating A/B testing processes. This will allow designers to experiment with different design variations and actively measure their impact on user engagement and satisfaction— along with the flexibility to refine designs based on user feedback and observed behaviors. Furthermore, by analyzing user interactions with digital products, tracking user behavior, and identifying patterns, AI algorithms can help designers better understand how users navigate through interfaces, the features they engage with, and the difficulties they encounter.

Today, these AI tools are very much within our reach, easing their way into our workflows. For instance, a wide variety of AI plug-ins are already available on Figma, such as Attention Insight, a tool that predicts where the user’s attention is likely to go, and Font Explorer, aiding designers in finding the perfect font. The list goes on and continues to grow by the day.

AI’s potential impact on accessibility

AI has the potential to improve user experience for individuals with disabilities while also ensuring that businesses adhere to accessibility regulations and standards. Right from the design stage, designers can make use of AI and ML algorithms that can assess website designs and provide recommendations to enhance accessibility, such as enhancing color contrast or incorporating alternative text for images. With the advancement of machine learning algorithms, it’s now possible to identify potential accessibility issues in real time, allowing designers and developers to promptly tackle challenges faced by users with disabilities, including visual and hearing impairments, mobility challenges and cognitive challenges.

Leveraging the capabilities of artificial intelligence technologies, designers will also be able to help users overcome barriers posed by language, old age, and other factors that may alienate certain user groups from accessing digital products. In short, by enabling the creation of more inclusive websites and applications, AI can help designers get things right as they go along with the design process rather than making adjustments only retroactively.

When humans conduct usability testing, they bring uniquely humane nuances of empathy, intuition, and other cognitive aspects into their work. They are capable of paying special attention to ethical considerations when it comes to factors such as inclusivity, fairness, and the impact on different user groups. Nevertheless, there are some potential pitfalls and challenges that accompany humans when they carry out testing. Sometimes, testers may lack a comprehensive understanding of evolving accessibility standards and guidelines, resulting in incomplete assessments. Similarly, limited experience with assistive technologies could hinder an accurate assessment of how users with disabilities interact with the interface. Accessibility testing should be meticulous, and AI can help with that- thanks to its ability to quickly and accurately analyze large amounts of data.

Consider how Natural Language Processing (NLP) algorithms can assist in making written content on the web more accessible by analyzing the text for readability, suggesting simpler language, and identifying any potential issues that may pose challenges for users with cognitive disabilities. This way, elements that are often overlooked such as error-messages, labels, and instructions can also be improved to be more user-friendly and inclusive.

Think about it this way— an ideal collaboration between human intelligence and artificial intelligence where each counterbalances the challenges encountered by the other. Creating a more accessible world together is not a bad idea, is it?

Only humans can create like humans, for humans

Creating an exceptional product goes beyond satisfying present demands. AI relies on historical data, which hampers its capacity for innovation and foreseeing future requirements. The responsibility of thinking ahead and pioneering the next big thing remains with humans. While AI can provide solutions based on past data, it struggles with original, first-principles thinking.

Especially in a field where empathy is indispensable, it’s not difficult to see why human-centered design will ultimately require human beings to drive design processes— which parts of the process they would choose to involve AI is up to them. A knack to discern whether the human or their machine counterpart would do a specific task better in any particular context is worth developing. Picture two members of a team solving a jigsaw puzzle together, where each one does their bit to move further towards the completion of the big picture. The puzzle could be quite complex, requiring a lot of time, effort, and focus to complete- but when two of them work together, the pieces start coming together more quickly and more comprehensively, making the activity more enjoyable and less stressful. That is one way to put what a rewarding human-AI collaboration should feel like.

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