AI-based Technologies for Everyone: How and Why to Adapt Voice Assistants’ Complexity to Older Adults

Rzepka Christine, Berger Benedikt, Tams Stefan

Abstract

Technological advancements in the area of artificial intelligence have rapidly improved the performance of speech recognition and natural language processing. These improvements have facilitated the proliferation of voice assistants (VAs), which can understand human speech and provide spoken answers to assist in various tasks. More and more individuals and organizations adopt VAs because they value the naturalness of speech interaction. However, speech interaction is of ephemeral nature and processed in sequential order, which puts cognitive load on the user. Therefore, we investigate the relationship between the complexity of speech interaction and the interaction outcomes enjoyment, satisfaction, and intention to explore. Our results show that this relationship has an inverted U-shape for people with above-median information processing speed (i.e., younger adults) but is negatively linear otherwise. The results contribute to the literature on interface complexity and on the use of IT systems by the elder.