Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems 2019
DOI: 10.1145/3290605.3300647
|View full text |Cite
|
Sign up to set email alerts
|

Explicating "Implicit Interaction"

Abstract: The term implicit interaction is often used to denote interactions that differ from traditional purposeful and attention demanding ways of interacting with computers. However, there is a lack of agreement about the term's precise meaning. This paper develops implicit interaction further as an analytic concept and identifies the methodological challenges related to HCI's particular design orientation. We first review meanings of implicit as unintentional, attentional background, unawareness, unconsciousness and… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
6
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
5
2
2

Relationship

0
9

Authors

Journals

citations
Cited by 37 publications
(6 citation statements)
references
References 90 publications
(133 reference statements)
0
6
0
Order By: Relevance
“…Similarly, we lack a strong understanding of how classification rates derived from machine learning algorithms regarding the internal state of the user correspond with those subjective types of self-assessment that informs perceived accuracy of the system (Fairclough et al, 2015 ; McCrea et al, 2016 ). Due to the high speed of data exchange between brain and machine, interactions with neurotechnology can occur implicitly and autonomously, i.e., functions can be activated without seeking confirmation from the user (Solovey et al, 2015 ; Serim and Jacucci, 2019 ). While this is a potentially exciting development from a HCI perspective, we know relatively little about how users will respond to this type of interaction mechanic, will they welcome an opportunity to communicate unconsciously with a machine or experience the triggering of autonomous functions by real-time changes in neurophysiological activity as a loss of personal control?…”
Section: Grand Challenge: Designing User Experience With Neurotechnol...mentioning
confidence: 99%
“…Similarly, we lack a strong understanding of how classification rates derived from machine learning algorithms regarding the internal state of the user correspond with those subjective types of self-assessment that informs perceived accuracy of the system (Fairclough et al, 2015 ; McCrea et al, 2016 ). Due to the high speed of data exchange between brain and machine, interactions with neurotechnology can occur implicitly and autonomously, i.e., functions can be activated without seeking confirmation from the user (Solovey et al, 2015 ; Serim and Jacucci, 2019 ). While this is a potentially exciting development from a HCI perspective, we know relatively little about how users will respond to this type of interaction mechanic, will they welcome an opportunity to communicate unconsciously with a machine or experience the triggering of autonomous functions by real-time changes in neurophysiological activity as a loss of personal control?…”
Section: Grand Challenge: Designing User Experience With Neurotechnol...mentioning
confidence: 99%
“…Ju and Leifer [75] argued that traditional HCI was limited to command-based and graphical interface-based explicit interactions, whereas implicit interactions, defined as "those that occur without the explicit behest or awareness of the user," are common in day-to-day interactions. Developing on this, Serim and Jacucci [76] described implicit interaction as "...a system response to the user input does not rely on the user having conducted the input to intentionally achieve it." With the development of ubiquitous computing, big data, and AI, implicit interactions increasingly influenced users to interact with the intelligent system because these emerging technologies have the ability to sense the environment that does not rely on intentional input from users.…”
Section: Implicitness Versus Explicitnessmentioning
confidence: 99%
“…With the development of ubiquitous computing, big data, and AI, implicit interactions increasingly influenced users to interact with the intelligent system because these emerging technologies have the ability to sense the environment that does not rely on intentional input from users. Hence, in this context, implicitness refers to unintentionally taking action, reducing attention during input or output, action without awareness, and executing results without conscious processing [76]. The implicit-explicit interaction dimension refers to whether the design of BCTs requires intentional goals, users' attention, awareness of input, and conscious processing.…”
Section: Implicitness Versus Explicitnessmentioning
confidence: 99%
“…A shift in attention can be triggered by, among other things, evoking positive or negative emotions, but these also require personalization [7]. Thus, designing for implicit interaction means enabling secondary activities to run in the background of attention, often in parallel to explicit tasks [37,68]. Interactive wearables are also often considered unobtrusive [13,19,52,64,89] as long as they are adapted to the user's skin and temperature sensitivity and stay non-disruptive to movement [20], and prior work has explored novel affective wearable displays, such as chronometry [79].…”
Section: Unobtrusive Designmentioning
confidence: 99%