Gaze-based Opportunistic Privacy-preserving Human-Agent Collaboration

In

Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24)

Conference

Date

May 11, 2024

Authors

Jan Grau, Simon Mayer, Jannis Strecker, Kimberly Garcia, and Kenan Bektaş

Abstract

This paper introduces a novel system to enhance the spatiotemporal alignment of human abilities in agent-based workflows. This optimization is realized through the application of Linked Data and Semantic Web technologies and the system makes use of gaze data and contextual information. The showcased prototype demonstrates the feasibility of implementing such a system, where we specifically emphasize the system’s ability to constrain the dissemination of privacy-relevant information.

Text Reference

Jan Grau, Simon Mayer, Jannis Strecker, Kimberly Garcia, and Kenan Bektaş. 2024. Gaze-based Opportunistic Privacy-preserving Human-Agent Collaboration. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3613905.3651066

BibTex Reference
@inproceedings{10.1145/3613905.3651066,
author = {Grau, Jan and Mayer, Simon and Strecker, Jannis and Garcia, Kimberly and Bektas, Kenan},
title = {Gaze-based Opportunistic Privacy-preserving Human-Agent Collaboration},
year = {2024},
isbn = {9798400703317},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3613905.3651066},
doi = {10.1145/3613905.3651066},
abstract = {This paper introduces a novel system to enhance the spatiotemporal alignment of human abilities in agent-based workflows. This optimization is realized through the application of Linked Data and Semantic Web technologies and the system makes use of gaze data and contextual information. The showcased prototype demonstrates the feasibility of implementing such a system, where we specifically emphasize the system’s ability to constrain the dissemination of privacy-relevant information.},
booktitle = {Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems},
articleno = {176},
numpages = {6},
keywords = {Human-Agent-Collaboration, Koreografeye, Privacy-Preserving, Solid},
location = {Honolulu, HI, USA},
series = {CHI EA '24}
}
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