artificial intelligence

Two research teams, with some authors in common, have shown in two separate studies that interaction with chatbots using artificial intelligence (AI) can significantly change a voter's opinion about a presidential candidate or a policy proposal. One of the studies, published in Nature, was conducted in three countries (the US, Canada, and Poland), while the other, developed in the UK, is published in Science. Both studies reach the same conclusion: the persuasive power of these tools stems less from psychological manipulation than from the accumulation of fact-based claims that support their position. However, this information is not always accurate, and the greater the persuasive power, the greater the inaccuracy and fabrication.

An artificial intelligence (AI) model trained on over 400,000 mammograms and analyzed in a separate sample of over 240,000 improved cancer risk prediction in cases of dense breasts, which are more common in young women or those with a low body mass index. This is an important factor in screening, especially because it can hinder tumor detection. The results are presented as an abstract, not yet peer-reviewed, at the annual meeting of the Radiological Society of North America.

A team from the Center for Genomic Regulation in Barcelona and Harvard Medical School (United States) has created an artificial intelligence (AI) model to support the diagnosis of rare diseases in patients with unique genetic mutations. Called popEVE, the tool performs better than AlphaMissense—another model developed by Google DeepMind—according to an article published in Nature Genetics.

A team at Google DeepMind has developed AlphaProof, an artificial intelligence system that learns to find formal proofs by training on millions of self-formulated problems. According to the authors, the system “substantially improves upon previous-generation results on historical problems from mathematical competitions.” Specifically, in the 2024 International Mathematical Olympiad (IMO) for secondary school students, “this performance, achieved after several days of computation, resulted in a score equivalent to that of a silver medalist, marking the first time an AI system has achieved medal-level performance.” The results are published in the journal Nature.

Large language models (LLMs) do not reliably identify people's false beliefs, according to research published in Nature Machine Intelligence. The study asked 24 such models – including DeepSeek and GPT-4o, which uses ChatGPT – to respond to a series of facts and personal beliefs through 13,000 questions. The most recent LLMs were more than 90% reliable when comparing whether data was true or false, but they found it difficult to distinguish between true and false beliefs when responding to a sentence beginning with ‘I believe that’.

A research group at Stanford University (United States) has organised the first academic conference in which artificial intelligence (AI) tools serve as both authors and reviewers of scientific articles. Called Agents4Science 2025, the conference will take place on 22 October.

On the internet, professional women are represented as younger—and therefore less experienced—than their male counterparts, even though this age difference does not correspond to actual data in the US, according to an article published in Nature. This study of gender and age stereotypes is based on an analysis of 1.4 million images on five platforms (Google, Wikipedia, IMDb, Flickr and YouTube), as well as nine large language models, such as ChatGPT, trained with texts from Reddit, Google News, Wikipedia and Twitter. 

The temporary employment rate for teaching staff in Spain is 31%, above the OECD average of 19% and the EU average of 17%. This is one of the results of the latest edition of TALIS, the Teaching and Learning International Study, promoted by the OECD and involving more than 50 participating countries. In its previous edition, in 2018, 33% of Spanish teachers had temporary contracts. The study also shows that teacher job satisfaction is among the highest, at 95%—compared to 89% in the OECD and 90% in the EU. As a new feature, TALIS analyzes four new areas: the impact of artificial intelligence on learning and teaching, managing diversity in the classroom, socio-emotional learning, and education for sustainability.

Artificial intelligence (AI)-assisted protein engineering is enabling advances in the design of new molecules, but it also poses biosafety challenges related to the potential production of harmful or dangerous proteins. Some of these threats, whether deliberate or accidental, may not be detected by current control tools. An international team has analyzed the situation and developed software patches to improve their identification, although they acknowledge that it remains incomplete. The authors of the study, published in the journal Science, warn that some of the data and code should not be published in a public repository due to its potential misuse.

An artificial intelligence (AI) tool can predict the probability of more than 1,000 diseases based on a person's medical history, with greater accuracy than existing technologies, which focus on fewer pathologies, according to the authors in Nature. This model, called Delphi-2M, is also capable of simulating health trajectories for up to 20 years. The tool was trained with health data from 400,000 people in the United Kingdom and tested using data from nearly two million people in Denmark.