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Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare to economics. However, its black box nature…
Driven by ongoing improvements in machine learning, chatbots have increasingly grown from experimental interface prototypes to reliable and robust tools for process automation. Building on these advances, companies have identified various…
This chapter explores the symbiotic relationship between Artificial Intelligence (AI) and trust in networked systems, focusing on how these two elements reinforce each other in strategic cybersecurity contexts. AI's capabilities in data…
Providing well-calibrated AI confidence can help promote users' appropriate trust in and reliance on AI, which are essential for AI-assisted decision-making. However, calibrating AI confidence -- providing confidence score that accurately…
As our information environments become ever more powered by artificial intelligence (AI), the phenomenon of trust in a human's interactions with this intelligence is becoming increasingly pertinent. For example, in the not too distant…
Trust in clinical artificial intelligence (AI) cannot be reduced to model accuracy, fluency of generation, or overall positive user impression. In medicine, trust must be engineered as a measurable system property grounded in evidence,…
There is general agreement that some form of regulation is necessary both for AI creators to be incentivised to develop trustworthy systems, and for users to actually trust those systems. But there is much debate about what form these…
Recent advances in artificial intelligence (AI) and robotics have drawn attention to the need for AI systems and robots to be understandable to human users. The explainable AI (XAI) and explainable robots literature aims to enhance human…
As AI technology develops, trust in AI agents is becoming more important for more AI applications in human society. Possible ways to improve the trust relationship include empathy, success-failure series, and capability (performance).…
Large Language Models (LLMs) can engage in human-looking conversational exchanges. Although conversations can elicit trust between users and LLMs, scarce empirical research has examined trust formation in human-LLM contexts, beyond LLMs'…
With robots becoming increasingly prevalent in various domains, it has become crucial to equip them with tools to achieve greater fluency in interactions with humans. One of the promising areas for further exploration lies in human trust. A…
Generative AI (GenAI) has brought opportunities and challenges for higher education as it integrates into teaching and learning environments. As instructors navigate this new landscape, understanding their engagement with and attitudes…
The rapid progress in Large Language Models (LLMs) could transform many fields, but their fast development creates significant challenges for oversight, ethical creation, and building user trust. This comprehensive review looks at key trust…
Explainability, interpretability and how much they affect human trust in AI systems are ultimately problems of human cognition as much as machine learning, yet the effectiveness of AI recommendations and the trust afforded by end-users are…
In the ever-expanding landscape of Artificial Intelligence (AI), where innovation thrives and new products and services are continuously being delivered, ensuring that AI systems are designed and developed responsibly throughout their…
A large survey of American adults explored the complex landscape of attitudes towards artificial intelligence (AI). It explored the degree of concern regarding specific potential outcomes of the new advances in AI technology and correlates…
AI and ML models have already found many applications in critical domains, such as healthcare and criminal justice. However, fully automating such high-stakes applications can raise ethical or fairness concerns. Instead, in such cases,…
Although recent developments in generative AI have greatly enhanced the capabilities of conversational agents such as Google's Gemini (formerly Bard) or OpenAI's ChatGPT, it's unclear whether the usage of these agents aids users across…
In human-AI interactions, explanation is widely seen as necessary for enabling trust in AI systems. We argue that trust, however, may be a pre-requisite because explanation is sometimes impossible. We derive this result from a formalization…
Trust is a critical issue in Human Robot Interactions as it is the core of human desire to accept and use a non human agent. Theory of Mind has been defined as the ability to understand the beliefs and intentions of others that may differ…