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Title: The Bible of AI™ – International scientific and technical publication on Artificial Intelligence | ISSN 2695-6411 | Officially founded in September, 2019

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A number with no recorded reason may end up deciding for a patient
Transparency in artificial intelligence has become a question of provenance. Provenance tells you where a piece of content came from; it does not tell you why what it asserts was decided.

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Contemporary AI lacks the imagination to diverge or negate in science
Bold projections that artificial intelligence will accelerate scientific discovery have raced ahead of evidence from working scientists, and the field still lacks large-scale, scientist-in-the-loop tests of these claims. Here we mount the largest such evaluation to date and map what AI cannot yet do for science. We invited authors of 121,640 recent preprints across biology, medi...

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An Embarrassingly Simple Graph Heuristic Reveals Shortcut-Solvable Benchmarks for Sequential Recommendation
Sequential recommendation is a central task in recommender systems, and recent research has increasingly shifted toward generative recommenders that leverage both sequential patterns and semantic item information. However, these methods are often evaluated on a small set of widely used benchmarks. This raises a natural question: do these benchmarks actually require the advanced ...

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When silence is safer: a review and decision-theoretic framework for LLM abstention in healthcare
Large language models (LLMs) are designed to generate answers to user prompts, which often drives them to respond even when uncertainty is high, information is incomplete, or a refusal would be more appropriate. In healthcare, this tendency can be dangerous: confidently stated but inaccurate medical advice can cause significant harm, making the ability to abstain especially impo...

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Not yet: the third answer in machine intelligence
The most difficult thing to build into an artificial intelligence is not accuracy. It is restraint. Contemporary systems are rewarded, structurally, for producing an answer — a label, a score, a confident sentence — because a fluent reply reads as competence and a hesitation reads as failure. Yet in the places where these systems will […]

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