AI4AUI

Abstract

This workshop aims at exploring how adaptive user interfaces, i.e., user interface that can modify, change, or adapt themselves based on the user, or their context of use, can benefit from Artificial Intelligence (AI) in general, and Machine Learning (ML) techniques in particular, towards objectively improving some software quality properties, such as usability, aesthetics, reliability, or security. For this purpose, participants will present a case study, and classify their proposed technique in terms of several criteria, such as (but not limited to): input, technique, output, adaptation steps covered, adaptation time, level of automation, software quality properties addressed, measurement method, potential benefits, and drawbacks. These will be then clustered for group discussions according to the aforementioned criteria, such as by technique family or property addressed. From these discussions, an AI4AUI framework will emerge that will be used for positioning, comparing presented techniques, and for generating future avenues.