Designers
Chenrui Ma, Shiyun Wang, Shuyang Zhang, Ke Ma, Yujia Dai, Qinzhi Yuan
Year
2026
Category
New Talent
Country
United Kingdom
School
Goldsmiths University of London
Teacher
Dr. Rabail Tahir
Three questions to the project team
What was the particular challenge of the project from a UX point of view?
The biggest UX challenge was designing trust in a highly emotional and high-risk context. Families were not only choosing a caregiver, they were making decisions about the safety and dignity of someone they love. Most existing platforms focus on resumes, ratings, and availability. But during research, we found that families actually cared more about emotional fit: Is this person patient? Can they handle stress? Will they fit into our home environment? The challenge was turning AI matching from a black box into something people could understand and trust. We had to redesign the experience around transparency, personality compatibility, and emotional reassurance instead of just efficiency.
What was your personal highlight in the development process? Was there an aha!-moment, was there a low point?
Our biggest turning point came after the third external usability test. At first, we thought our project was about helping families find caregivers more easily. But testers kept asking the same question: why should users trust this match? That was a difficult moment for us because we realized our interface looked polished, but the logic behind the AI still felt unclear. This completely changed our direction. We stopped thinking about faster matching and started thinking about trustworthy matching. We added caregiver personality assessments, situational judgement tests, and explainable match cards to show not only who was recommended, but why. That was the moment the project became much stronger.
Where do you see yourself and the project in the next five years?
In the next five years, we hope CareMatch will grow into a trusted support system for home care services, starting in the UK. Our first step is to work with local care agencies and adapt the platform to different real-world care situations. Future versions may include adaptive care planning, multilingual support, and deeper collaboration with healthcare providers. We believe more transparent and emotionally aware AI systems can better support elderly care, disability care, and long-term family care. Through this project, we also began to see UX as more than interface design. In the age of AI, UX is about designing relationships between people, systems, trust, and responsibility.
