Trustworthy AI: From principles to practices
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …
of various systems based on it. However, many current AI systems are found vulnerable to …
A systematic review of human–computer interaction and explainable artificial intelligence in healthcare with artificial intelligence techniques
Artificial intelligence (AI) is one of the emerging technologies. In recent decades, artificial
intelligence (AI) has gained widespread acceptance in a variety of fields, including virtual …
intelligence (AI) has gained widespread acceptance in a variety of fields, including virtual …
Formalizing trust in artificial intelligence: Prerequisites, causes and goals of human trust in AI
Trust is a central component of the interaction between people and AI, in that'incorrect'levels
of trust may cause misuse, abuse or disuse of the technology. But what, precisely, is the …
of trust may cause misuse, abuse or disuse of the technology. But what, precisely, is the …
Toward trustworthy AI development: mechanisms for supporting verifiable claims
With the recent wave of progress in artificial intelligence (AI) has come a growing awareness
of the large-scale impacts of AI systems, and recognition that existing regulations and norms …
of the large-scale impacts of AI systems, and recognition that existing regulations and norms …
[PDF][PDF] Four principles of explainable artificial intelligence
We introduce four principles for explainable artificial intelligence (AI) that comprise
fundamental properties for explainable AI systems. We propose that explainable AI systems …
fundamental properties for explainable AI systems. We propose that explainable AI systems …
Designing for responsible trust in AI systems: A communication perspective
Current literature and public discourse on “trust in AI” are often focused on the principles
underlying trustworthy AI, with insufficient attention paid to how people develop trust. Given …
underlying trustworthy AI, with insufficient attention paid to how people develop trust. Given …
Interpretable machine learning for discovery: Statistical challenges and opportunities
New technologies have led to vast troves of large and complex data sets across many
scientific domains and industries. People routinely use machine learning techniques not …
scientific domains and industries. People routinely use machine learning techniques not …
A survey on trustworthy recommender systems
Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …
deployed in almost every corner of the web and facilitate the human decision-making …
When confidence meets accuracy: Exploring the effects of multiple performance indicators on trust in machine learning models
Previous research shows that laypeople's trust in a machine learning model can be affected
by both performance measurements of the model on the aggregate level and performance …
by both performance measurements of the model on the aggregate level and performance …
Instruction backdoor attacks against customized {LLMs}
The increasing demand for customized Large Language Models (LLMs) has led to the
development of solutions like GPTs. These solutions facilitate tailored LLM creation via …
development of solutions like GPTs. These solutions facilitate tailored LLM creation via …