A new Lancet framework argues that cancer screening should match each person's risk. I agree, as long as precision also means doing less for people at low risk.

In June 2026, bioRxiv's parent openRxiv began testing an interactive way to read preprints. It is an experiment, and I think it asks the right question.

An AI system wrote a paper that cleared reviewers at an ICLR workshop. It is a real milestone, and an honest stress test of peer review itself.

A 2023 survey put numbers on the extra hours, rejections and skipped conferences that come with doing science in a second language. Journals and conferences can shrink that cost.

A January 2026 Nature study links AI use to bigger scientific careers and a narrower spread of research topics. Both can be true at once, and that is the problem.

A Swedish screening trial randomized more than 100,000 women to test AI in real mammography. That, not another benchmark score, is what earns trust.

In a 2025 experiment, Turkish high school students did far better on math practice with GPT-4. Those given a plain chatbot then did worse on their own. Tutor design made the difference.

A small MIT study found that people who let ChatGPT write their essays remembered little of them. That is a real cost for learning, and it is not brain damage.

A 2025 consensus guideline asks for medical AI to be monitored for its whole working life. Radiation therapy machines have lived by that rule for decades.

AlphaFold 3 predicts how proteins, DNA, RNA and drug-like molecules fit together. That is a real advance. A predicted shape is still a starting point, not a finding.

A 2024 study found that AI-written lay summaries made scientists look more trustworthy in one experiment and helped readers follow the science in another. Clear writing still has to be checked for accuracy.

A large 2024 study found expert reviewers rated AI research ideas as more novel than human ones. Novel is a good start, but it is not the same as worth testing.

A 2024 checklist for medical imaging AI quietly asks the questions a headline AUC skips: who was tested, where, how trustworthy the numbers are, and who benefits.

Seventy-three teams tested one hypothesis on the same data and reached opposite answers. The lesson is about method, not misconduct, and about making hidden choices visible.

A 68-country survey published in January 2025 found trust in scientists moderately high on average. Where scientists scored lowest was listening, and that part is fixable.

Registered Reports let journals judge a study's question and methods before any data exist. For many studies that test a clear idea, I think that is a better deal.

A 2024 Nature Perspective argues that AI can make scientists feel they understand more than they do. The fix starts with knowing the assumptions behind a fluent answer.

When one patient's scans end up in both training and test data, a medical imaging model can look far better than it is, and nobody has to cheat.

In March 2025, bioRxiv and medRxiv moved to a new independent nonprofit. Science leans on these servers now, so how they are run and paid for matters.

A December 2024 consensus asks health AI teams to say who is in their data, who is missing, and how a model works for each group.

A December 2022 Liver-Chip study reported strong results on one defined job. The useful question is what a model is validated for, not whether it replaces animals.

In a 2023 study, radiologists followed a fake AI's wrong calls on mammograms. The lesson is less about AI than about when and how its answer is shown.

Nature's 2023 postdoc survey found more optimism than in 2020, alongside familiar pressures. I think the healthiest reading is that a science career has many homes.

A 2024 study reran thousands of notebooks from biomedical papers, and few gave the same answer. Sharing code is the first step. Making it run again is the real work.

A 2023 Nature study found that science is breaking with the past less often. Critics call the yardstick flawed. Either way, it is worth asking what we reward.

In 2022, eLife announced it would stop saying yes or no to papers after review. Public reviews and a short verdict on the evidence now travel with the paper instead.

In October 2024 a scholarly society told members that, according to its publisher, its journal content was being made available for AI training. The deal may be lawful. Authors still deserved to hear first.

Each year, a list of the world's top 2% of scientists makes the rounds. Its own authors call it a measure of citation impact and warn against leaning on it.

A 2023 experiment showed ChatGPT makes professional writing faster. Science should be careful about treating that speed as progress.

A 2024 Nature study showed AI models degrade when trained on their own output. Science is not collapsing, but it should start keeping track of what humans wrote.

In January 2023, two leading science journals ruled that ChatGPT cannot be an author. The real reason is what happens after a paper is published.

In 2023, seven popular AI detectors labeled more than half of a set of TOEFL essays by non-native English writers as machine-made. A detector score can start a conversation. It should never end one.

A 2024 dataset of publisher price lists shows what open access can cost authors at list price. Free reading is a real gain, but the fee should not decide who gets published.

In 2023 the whole editorial board of NeuroImage quit over fees and started a rival journal. Elsevier kept NeuroImage running with an interim board. The reputation was harder to keep.

A 2024 study estimated how much AI conference review text was reshaped by ChatGPT. The real question is where tidying words ends and handing off judgment begins.

A 2023 study found ChatGPT inventing many of the references it listed. A tidy citation is not proof that a paper exists, and checking it is still our job.

An April 2024 update to a reporting guideline asks prediction model papers to show their work. A strong result means little when readers cannot see how it was made.

A journal openly invited clinical trials that missed their main goal. That is welcome, but only a well designed "no" tells anyone something useful.

A 2022 experiment sent one finance paper to hundreds of reviewers under a Nobel laureate's name, a junior researcher's name, or no name. The name changed the verdict.

The 2023 Hindawi retractions showed how paper mills exploit special issues. Better detection helps, but mills keep finding customers because publication counts are what get rewarded.

In 2023 Crossref opened up the Retraction Watch database, creating what it called the largest open database of retractions. A retraction only works if the warning follows the paper to where people read and cite it.

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