Inspired by the increasing use of artificial intelligence (AI) to augment humans, researchers
have studied human–AI systems involving different tasks, systems and populations. Despite …

Generative AI (GenAI) systems offer unprecedented opportunities for transforming
professional and personal work, yet present challenges around prompting, evaluating and …

Widely deployed large language models (LLMs) can produce convincing yet incorrect
outputs, potentially misleading users who may rely on them as if they were correct. To …

Data storytelling is powerful for communicating data insights, but it requires diverse skills
and considerable effort from human creators. Recent research has widely explored the …

Human oversight is currently discussed as a potential safeguard to counter some of the
negative aspects of high-risk AI applications. This prompts a critical examination of the role …

One of the most concrete measures towards meaningful AI accountability is to
consequentially assess and report the systems' performance and impact. However, the …

While existing literature has explored and revealed several insights pertaining to the role of
human factors (eg, prior experience, domain knowledge) and attributes of AI systems (eg …

Recent work highlights the ability of verbal machine learning classifiers to distinguish
between accurate and inaccurate recognition memory decisions (Dobbins, 2022; Dobbins & …

This is the interim publication of the first International Scientific Report on the Safety of
Advanced AI. The report synthesises the scientific understanding of general-purpose AI--AI …

Trust between humans and AI in the context of decision-making has acquired an important
role in public policy, research and industry. In this context, Human-AI Trust has often been …