This paper presents a systematic defense of large language model (LLM) hallucinations
or'confabulations' as a potential resource instead of a categorically negative pitfall. The …

Issues of reliability are claiming center‐stage in the epistemology of machine learning. This
paper unifies different branches in the literature and points to promising research directions …

This paper defends the use of generative artificial intelligence (AI) in scholarship and argues
for its legitimacy as a valuable tool for contemporary research practice. It uses a emergent …

Unraveling the connections between microscopic structure, emergent physical properties,
and slow dynamics has long been a challenge when studying the glass transition. The …

Deep learning (DL) has become increasingly central to science, primarily due to its capacity
to quickly, efficiently, and accurately predict and classify phenomena of scientific interest …

Este trabajo exploró la intersección filosófica de la inteligencia artificial mediante una
revisión sistemática que abordó la epistemología y la autenticidad de la comprensión de las …

Explainable AI (xAI) methods are important for establishing trust in using black-box models.
However, recent criticism has mounted against current xAI methods that they disagree, are …

In the social epistemology of scientific knowledge, it is largely accepted that relationships of
trust, not just reliance, are necessary in contemporary collaborative science characterised by …

There has been a surge of interest in explainable artificial intelligence (XAI). It is commonly
claimed that explainability is necessary for trust in AI, and that this is why we need it. In this …

Unravelling the connections between microscopic structure, emergent physical properties
and slow dynamics has long been a challenge when studying the glass transition. The …