Human-centered trust framework: An HCI perspective
원문 초록
The rationale of this work is based on the current user trust discourse of Artificial Intelligence (AI). We aim to produce novel HCI approaches that use trust as a facilitator for the uptake (or appropriation) of current technologies. We propose a framework (HCTFrame) to guide non-experts to unlock the full potential of user trust in AI design. Results derived from a data triangulation of findings from three literature reviews demystify some misconceptions of user trust in computer science and AI discourse, and three case studies are conducted to assess the effectiveness of a psychometric scale in mapping potential users' trust breakdowns and concerns. This work primarily contributes to the fight against the tendency to design technical-centered vulnerable interactions, which can eventually lead to additional real and perceived breaches of trust. The proposed framework can be used to guide system designers on how to map and define user trust and the socioethical and organisational needs and characteristics of AI system design. It can also guide AI system designers on how to develop a prototype and operationalise a solution that meets user trust requirements. The article ends by providing some user research tools that can be employed to measure users' trust intentions and behaviours towards a proposed solution.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Structured Unplugged Approach for Foundational AI Literacy in Primary Education
Harnessing Structured Knowledge: A Concept Map-Based Approach for High-Quality Multiple Choice Question Generation with Effective Distractors
Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative Filtering
How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation
Paths and Ambient Spaces in Neural Loss Landscapes
Learning to Correction: Explainable Feedback Generation for Visual Commonsense Reasoning Distractor
토론
이 논문과 연결된 포럼 글이 아직 없습니다.