Usability, User Comprehension, and Perceptions of Explanations for Complex Decision Support Systems in Finance: A Robo-Advisory Use Case
Sahil Deo, Neha Sontakke
Abstract
Robo-financial advisors are complex algorithmic decision-making systems with a high potential for mass adoption due to their low operating costs and multitasking abilities. The quantitative aspects of our study measure the efficacy and usability of explanations and qualitative aspects determine the effect of explanations on users and system usability.
Topics & Concepts
UsabilityComputer scienceHuman multitaskingUsability goalsDecision support systemComprehensionHuman–computer interactionPerceptionUsability engineeringKnowledge managementArtificial intelligencePsychologyCognitive psychologyNeuroscienceProgramming languageExplainable Artificial Intelligence (XAI)Big Data and Business IntelligenceStock Market Forecasting Methods