Design of AI to prevent and counteract work-related mental illness

Abstract: Artificial intelligence (AI) is an emerging technology with the potential to revolutionize the field of mental health. As the prevalence of mental health issues continues to rise, there is a growing need for effective and accessible interventions. This master’s thesis is done in collaboration with Prevas South in Malmö at the UX department. The scope of the project was to investigate how AI can be used to prevent and counteract work-related mental illness and assess the barriers to AI. Several different data gathering techniques including literature review, questionnaire, interviews, and focus groups were used for analyzing the user’s needs and requirements. The data was analyzed in detail and resulted in an extensive affinity diagram and the user needs were identified as key findings. Three main themes of the key findings were “Comparison AI and human”, “Organizational” and “Design”. This was followed by brainstorming, developing conceptual models, and generating a final concept: an AI-based system tailored to accommodate key findings with the Demand-Control-Support model as the foundation. The concept was prototyped and iteratively tested and evaluated through both user tests and with regard to the key findings and different design principles. When evaluated, the concept received positive results and was reportedly comfortable and easy to use while not compromising user privacy. To summarize, when developing AI systems for preventing and counteracting mental illness at work, it is of importance recognizing the differences between AI and humans. Further, it is also important to consider the impact of organizational culture on user trust and attitude towards AI, and design for personalized and short interactions.