Conference Paper/Proceeding/Abstract 15 views
Towards Co-Designing a Continuous-Learning Human-AI Interface: A Case Study in Online Grooming Detection
Peter Daish,
Nicholas Micallef 
,
Nuria Lorenzo-Dus ,
Adeline Paiement ,
Deepak Sahoo
,
Nuria Lorenzo-Dus ,
Adeline Paiement ,
Deepak Sahoo
CEUR Workshop Proceedings, Volume: 3701
Swansea University Authors:
Peter Daish, Nicholas Micallef , Nuria Lorenzo-Dus , Adeline Paiement , Deepak Sahoo
Full text not available from this repository: check for access using links below.
Abstract
Interest is growing in using Human-Centered design to enhance compatibility of AI within humanenvironments. These design techniques are valid for eliciting human-centered design requirements,however, they often paint the scenario that AI interaction design is a one-way process in which userbehaviour...
| Published in: | CEUR Workshop Proceedings |
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| ISSN: | 1613-0073 |
| Published: |
Genoa, Italy
2024
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa68369 |
| Abstract: |
Interest is growing in using Human-Centered design to enhance compatibility of AI within humanenvironments. These design techniques are valid for eliciting human-centered design requirements,however, they often paint the scenario that AI interaction design is a one-way process in which userbehaviour is captured to improve interactions and user experiences. Such an approach does not consider real-world settings in which Human-AI environments involve multiple stakeholders, with contrasting needs, which could impact the interactivity, usability and usefulness of Human-AI environments. In this paper, we present a framework for incorporating multiple-stakeholders perspectives into the design of Human-AI environments, designed to establish a common dialogue between end-users’ needs for HumanAI interaction and AI developers’ practical limitations. This is a work in progress project and in our future work we plan to follow this iterative prototyping approach to develop a real-world continuous-learning Human-AI detection system for online grooming. |
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| Keywords: |
Human-AI, Continuous-learning, Human-centered design, Online grooming |
| College: |
Faculty of Science and Engineering |