Oct 19, 2024
5min read
How Can Designers Get Ready for the Future?
Last month, I attended CSS Day in Lagos, a two-day event divided into “UI Day,” which explored the overlap of design and development, and “CSS Day,” featuring speakers who delved into advanced, technical CSS topics. The presentations were as varied as the speakers' backgrounds, but a recurring theme stood out: In this fast-evolving era, are we, as product professionals, prepared to design for automation, machine learning, and AI?
What does automation mean for designers?
It’s rare to find a product team that hasn’t embraced automation to boost productivity. By offloading repetitive tasks and heavy lifting to machines, designers can focus on more meaningful and creative work. However, this raises an important question: how do we interact with and utilize the outputs generated by machines?Josh Clark, founder of the design studio Big Medium, explored this idea in his talk, ‘A.I. is Your New Design Material.’ He highlighted how recent breakthroughs like facial recognition, predictive text, and image search—all driven by machine learning—have transformed technology. Yet, at their core, these systems are still built on code, operating with precision and free from emotional interference or human bias.But when systems like facial recognition fail, we often assume the technology itself is flawed. Is that assumption accurate? According to Josh, this misunderstanding is crucial. A machine’s inability to meet human expectations doesn’t automatically mean it’s defective. Built on logic, machines don’t feel or make subjective decisions, which begs the question: Can a machine’s solution truly be "wrong"?The purpose of integrating machine learning into products was never to have machines handle everything. Instead, algorithms are meant to enhance human insight, enabling us to make better, faster decisions.By understanding how users interact with technology, we can build better products. For example, if a computer can teach itself to walk, it’s worth exploring the reasons behind its approach. Investigating these underlying mechanisms can reveal insights into why and how these solutions emerge, ultimately improving our designs and strategies.
How do we design for the unknown future?
Stephen Gerrard, Co-Founder of Geebaba, poses a thought-provoking question: “What was the most important thing you learned yesterday, and how will it impact what you do in the future?”
As designers and researchers, we constantly need to balance designing for the future while meeting the immediate demands of today’s challenges—a daunting task, especially with the rapid pace of change over the past decade.
Gerrard suggests starting by reflecting on how our design processes have evolved. Consider a time when UX/UI wasn’t a priority for most companies. As a consultant during the early days of the internet, Gerrard helped guide organizations toward a mindset that prioritized user experience.
This historical perspective offers valuable insights into how UX and UI have transformed over the years and can inform where they’re headed next. Jared introduces the concept of “The UX Tipping Point”—a framework with actionable steps to help organizations fully embrace UX design.
In the past, designers had to fight for recognition and a voice in decision-making. If an organization today isn’t starting from a place where user experience is central, they’re likely far from reaching that tipping point. Designers must continue to advocate for the maturity of UX within their companies and deepen the understanding of its significance.
When an organization reaches the final stage of fully integrating UX design into all aspects of its operations, it achieves The UX Tipping Point—a state where UX isn’t just a function but a core driver of the company’s success.
Are we designing for users or ourselves?
People often don’t know what they truly want, even if they believe they do. As UX psychologist Joe Leech puts it, “People want more choices, but can’t handle them.”
This raises a critical question: how can we design effectively for users when their expressed preferences don’t always align with their actual needs? The answer lies in thorough UX research.
In the early 2000s, psychologists Sheena Iyengar and Mark Lepper conducted a fascinating study on consumer choice. At a supermarket, they tested two scenarios: one week, only 6 varieties of jam were offered, while the following week featured 30 varieties. Surprisingly, more jam was sold during the week with fewer options. Yet when consumers were asked which scenario they preferred, they favored the week with 30 choices.
This example underscores Joe’s argument: “A designer who doesn’t understand psychology is like an architect who doesn’t understand physics.”
To truly meet users’ needs rather than just their wants, teams must rely on comprehensive user research. Analyzing responses on a larger scale requires effort, but it provides invaluable insights, forming a solid foundation for meaningful and effective UX design.