AI systems have been widely adopted across various domains in the real world.
However, in high-value, sensitive, or safety-critical applications such as
self-management for personalized health or food recommendation with a specific
purpose (e.g., allergy-aware recipe recommendations), their adoption is
unlikely. Firstly, the AI system needs to follow guidelines or well-defined
processes set by experts; the data alone will not be adequate. For example, to
diagnose the severity of depression, mental healthcare providers use Patient
Health Questionnaire (PHQ-9). So if an AI system were to be used for diagnosis,
the medical guideline implied by the PHQ-9 needs to be used. Likewise, a
nutritionist's knowledge and steps would need to be used for an AI system that
guides a diabetic patient in developing a food plan. Second, the BlackBox
nature typical of many current AI systems will not work; the user of an AI
system will need to be able to give user-understandable explanations,
explanations constructed using concepts that humans can understand and are
familiar with. This is the key to eliciting confidence and trust in the AI
system. For such applications, in addition to data and domain knowledge, the AI
systems need to have access to and use the Process Knowledge, an ordered set of
steps that the AI system needs to use or adhere to.

AI 系统需要遵循专家制定的指导方针和流程，使用过程知识和领域知识，并提供用户可理解的解释，以在高价值、敏感或安全关键的应用程序中获得信任和信心.