Transparency in Human-Machine Mutual Action

Abstract

Recent advances in human-computer integration (HInt) have focused on the development of human-machine systems, where both human and machine autonomously act upon each other. However, a key challenge in designing such systems is augmenting the user’s physical abilities while maintaining their sense of self-attribution. This challenge is particularly prevalent when both human and machine are capable of acting upon each other, thereby creating a human-machine mutual action (HMMA) system. To address this challenge, we present a design framework that is based on the concept of transparency. We define transparency in HInt as the degree to which users can self-attribute an experience when machines intervene in the users’ action. Using this framework, we form a set of design guidelines and an approach for designing HMMA systems. By using transparency as our focus, we aim to provide a design approach for not only achieving human-machine fusion into a single agent, but also controlling the degrees of fusion at will. This study also highlights the effectiveness of our design approach through an analysis of existing studies that developed HMMA systems. Further development of our design approach is discussed, and future prospects for HInt and HMMA system designs are presented.

Optimal Motor Point Search Using Mm-Order Electrode Arrays

“…By creating circumstances where human intention and induced movement do not compete, an unaware intervention (i.e., transparency of the intervention [37]) can be realized. This approach is expected to contribute to the implementation of a transparent intervention.…”