Personalized Artificial intelligence explainability based on the Technology Acceptance Model and the user’s literacy Level

Abstract The developed approach in this research, centers around personalisation derived from targeted clustering techniques based on the principles of the Technology Acceptance Model – TAM. By employing targeted clustering, we create tailored explanations for users based on their unique characteristics and requirements. To validate the effectiveness of our methodology, we conducted a case study…

Dialogue Rule augmentation

Parameters main(q, d, m): The primary function that takes in the Question (q), Domain (d), and Medical (m) parameters and returns the Answer (a) and Grade (grade). • Decision Logic: Implements the conditional logic as per the pseudocode to determine the appropriate answer a. • answer_content(): A placeholder function to generate the answer content c.…