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Modern general-purpose artificial intelligence (AI) systems present an urgent risk management challenge, as their rapidly evolving capabilities and potential for catastrophic harm outpace our ability to reliably assess their risks. Current…
In this pilot study, we investigate the use of GPT4 to assist in the peer-review process. Our key hypothesis was that GPT-generated reviews could achieve comparable helpfulness to human reviewers. By comparing reviews generated by both…
Generative AI systems across modalities, ranging from text (including code), image, audio, and video, have broad social impacts, but there is no official standard for means of evaluating those impacts or for which impacts should be…
In reaction to growing concerns about the potential harms of artificial intelligence (AI), societies have begun to demand more transparency about how AI models and systems are created and used. To address these concerns, several efforts…
While often assumed a gold standard, effective human evaluation of text generation remains an important, open area for research. We revisit this problem with a focus on producing consistent evaluations that are reproducible -- over time and…
Human-centered AI (HCAI) is a design philosophy that advocates prioritizing humans in designing, developing, and deploying intelligent systems, aiming to maximize the benefits of AI to humans and avoid potential adverse impacts. While HCAI…
Many guidelines for responsible AI have been suggested to help AI practitioners in the development of ethical and responsible AI systems. However, these guidelines are often neither grounded in regulation nor usable by different roles, from…
Responsible design of AI systems is a shared goal across HCI and AI communities. Responsible AI (RAI) tools have been developed to support practitioners to identify, assess, and mitigate ethical issues during AI development. These tools…
Trustworthy Artificial Intelligence (TAI) integrates ethics that align with human values, looking at their influence on AI behaviour and decision-making. Primarily dependent on self-assessment, TAI evaluation aims to ensure ethical…
As Artificial Intelligence (AI) continues to advance rapidly, Friendly AI (FAI) has been proposed to advocate for more equitable and fair development of AI. Despite its importance, there is a lack of comprehensive reviews examining FAI from…
Over the past year, artificial intelligence (AI) companies have been increasingly adopting AI safety frameworks. These frameworks outline how companies intend to keep the potential risks associated with developing and deploying frontier AI…
As artificial intelligence (AI) continues advancing, ensuring positive societal impacts becomes critical, especially as AI systems become increasingly ubiquitous in various aspects of life. However, developing "AI for good" poses…
Generative artificial intelligence (GenAI) has become a transformative approach in bioinformatics that often enables advancements in genomics, proteomics, transcriptomics, structural biology, and drug discovery. To systematically identify…
In the past few years, several large companies have published ethical principles of Artificial Intelligence (AI). National governments, the European Commission, and inter-governmental organizations have come up with requirements to ensure…
Generative AI tools are increasingly entering academic peer review workflows, raising questions about fairness, accountability, and the legitimacy of evaluative judgment. While these systems promise efficiency gains amid growing reviewer…
In this chapter, we reflect on the use of Artificial Intelligence (AI) and its acceptance in clinical environments. We develop a general view of hindrances for clinical acceptance in the form of a pipeline model combining AI and clinical…
The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI systems in higher education (HE) and, thus, it is still unclear…
This paper is an analysis of the different methods proposed to achieve AGI, including Human Brain Emulation, AIXI and Integrated Cognitive Architecture. First, the definition of AGI as used in this paper has been defined, and its…
While research on explainable AI (XAI) is booming and explanation techniques have proven promising in many application domains, standardised human-centred evaluation procedures are still missing. In addition, current evaluation procedures…
This study explores the use of artificial intelligence (AI) as a complementary tool for grading essay-type questions in higher education, focusing on its consistency with human grading and potential to reduce biases. Using 70 handwritten…