Artificial intelligence (AI) is transforming the world around us - and healthcare is no exception. From early diagnosis to personalized treatment, AI offers new opportunities to support both patients and professionals. But alongside this progress come critical questions about safety, ethics, and emotional responsibility - especially when we consider the impact on vulnerable populations such as children, adolescents, and people living with mental health challenges.
As a UX designer with a background in architecture, urban planning, and digital design - as well as a certified Mental Health First Aider (MHFA) and first responder - I view technology through both a human-centered and socially responsible lens. For me, good design is not just about functionality; it must protect, support, and empower people in meaningful ways. Especially in healthcare, where the stakes are high, we have a duty to ensure that AI systems are not only efficient but also safe, inclusive, and emotionally aware.
This article explores the current and potential applications of AI in healthcare - from psychological support to assistive technologies - while addressing the responsibilities of UX professionals in shaping these tools for the betterment of all. The use of artificial intelligence (AI) in healthcare holds great promise but also comes with risks - especially for vulnerable groups like children, adolescents, and people living with depression.
What Is Artificial Intelligence?
Although I am confident that my readers have a good or even a very thorough understanding of AI, I would like to share my perspective on it. Artificial Intelligence (AI) refers to the capability of machines to perform tasks that typically require human intelligence, such as pattern recognition, decision-making, and adapting to new situations. Its application can significantly enhance the efficiency and productivity of various processes, particularly in the field of healthcare. AI can serve as a valuable teammate, colleague, consultant, and agent (in a positive sense), functioning as a trustworthy assistant.
Practical Applications in Healthcare
1. Therabot – AI-Powered Psychological Support
One example of AI in mental healthcare is Therabot, a chatbot developed at Dartmouth University. In a clinical study involving 106 participants with depression, anxiety, or eating disorders, the following improvements were observed after four weeks of use:
51% reduction in depression symptoms
31% reduction in anxiety symptoms
19% reduction in eating disorder symptoms (significantly more than in the control group)
Users described the interaction as trustworthy - similar to that with a human therapist. Nevertheless, researchers emphasize the importance of clinical oversight and clearly defined safety standards.
Therabot describes itself as "Your Compassionate Digital Partner" - here is the link to Therabot.
Therabot shows the potential of AI to provide accessible and stigma-free mental health support. However, it is crucial to remember that while AI can offer a sense of security and consistency, it should never fully replace human interaction in mental health care. Maintaining a balance between technological innovation and human touch is essential for ethical and effective treatment.
2. Intelligent Care Technologies
AI is also enhancing nursing and caregiving through technologies such as:
Smart beds that monitor vital signs
AR glasses that display real-time data for care staff
Exoskeletons to assist with physically demanding tasks
Voice-controlled documentation systems to ease paperwork burdens
Intelligent walkers with sensors for increased safety
Service robots that assist with mobility and monitoring
3. ChatGPT in Medicine
ChatGPT illustrates how versatile AI chatbots can be in healthcare:
Support for diagnosis and treatment (as a supplement, not a replacement for medical expertise)
Administration and communication, e.g., appointment scheduling or translating medical terminology
Education and training, such as creating quizzes or personalized learning aids
Advantages of AI in Healthcare
Greater efficiency through automation
24/7 availability
Personalized treatment plans
Reduced workload for care staff
Through thoughtful UX design strategies, AI systems can be made intuitive, accessible, and user-friendly - for example, via simplified interfaces for smart devices or voice-controlled systems.
Such design strategies can ensure / might have the potential / will hopefully ensure that AI systems are not only efficient but also human-centric, recognizing the unique needs and comfort levels of different users. By making AI tools more intuitive, designers can help to bridge the digital divide and increase accessibility for a broader range of users, including those who may not be as technologically savvy.
Risks – Especially for Vulnerable Groups
Tragic Example: The Case of Sewell Setzer
14-year-old Sewell Setzer took his own life after intense interaction with an AI chatbot (Character.ai). This heartbreaking case clearly demonstrates how dangerous unregulated AI can be for emotionally vulnerable users. This tragic example underscores the urgent need for robust regulations and ethical guidelines in the development and deployment of AI. It is imperative that AI systems are designed with empathy, incorporating safeguards to protect the emotional well-being of users. This necessitates ongoing research and collaboration between mental health professionals and AI developers to create solutions that are both effective and safe for all users.
Risks for Children and Adolescents
Addiction risk due to AI-driven social interactions
Worsening of mental health issues through manipulative systems
Risks for Adults with Depression
Lack of empathy: AI can only simulate human warmth
Misinformation: AI may give misleading or harmful advice
Responsibilities of UX Designers and Developers - for all the topics and points I mentioned before
Integrating AI demands a high degree of responsibility. UX designers should follow these principles:
User-Centered Design: Create intuitive, accessible interfaces
Emotional Intelligence: Develop systems that can respond to emotional cues - with humans at the center
Safety and Transparency: Clearly communicate the capabilities and limitations of AI
Data Privacy: Implement strong safeguards to protect sensitive health data
Conclusion
AI has the potential to sustainably improve healthcare - through personalized treatment, more efficient processes, and support for professionals. At the same time, we must take the risks for vulnerable populations seriously and mitigate them through intentional UX design, clear guidelines, and human oversight. As a UX designer - and as an experienced first responder - I believe it is our duty to ensure that AI systems are safe, empathetic, and accessible to everyone.
Last Throughs - so that you might understand me better
As a UX designer - as a designer - I always see our work as work for people, for those who ultimately engage with and interact with what we create. That’s why, for me, my commitment to mental health and my long-standing volunteer work as a paramedic - primarily as a first responder with the German Red Cross (DRK) and the Samaritan Federation (ASB) motorcycle response unit - is more than just a natural extension of my professional life. Improving emergency services is something I care deeply about.
In addition, I volunteer as a certified Mental Health First Aider (MHFA) and support people in crisis through psychosocial emergency care (PSNV). I do this not only because I believe it’s important - but because it’s essential and valuable to society. Good design, to me, must go beyond the product or service. It must fulfill, support, and bring joy to people. Only when usefulness, usability, accessibility, and joy of use form a true unity does design reach its full potential. That’s been my guiding principle - whether during my time as an architect, as an urban planner, or later, since the rise of new media, as a designer of digital experiences.
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