The responsive system: a new challenge for AI

Abstract

I'm developing a responsive system as an intelligent front-end for computer-based management application programs. I intend for the responsive system to observe and understand the user, and interpret and carry out the user's wishes. I use the Management System Model (MSM) to provide a conceptual background to the responsive system. I operationalize the concept of a responsive system from three approaches: observing the human world, comparing responsiveness to other terms, and representing it in the MSM. I built a prototype, called MSLTRAIN, to accomplish the operational objectives of a responsive system. I'm improving MSLTRAIN through experiments meant to extract the meaning of responsiveness and to include that meaning in the MSLTRAIN system. The philosophy of operational responsiveness is evolving through experiment based on iterative design and the critical incident tool idea. Implementing a responsive system requires lots of artificial intelligence (AI) concepts and features. The new challenge for AI is to reason out and learn responsiveness — a human trait not easily found, let alone learned.