Key points

The quality of science is only as good as the data that supports it.

Science faces two major threats to data integrity.

AI can fabricate virtually undetectable fraudulent data, and trusted public domain datasets are disappearing.

About a decade ago, I (Frank W. Putnam) read an editorial by the president of the Chinese Academy of Sciences lamenting the high rates of fraudulent research published in Chinese journals. Could Chinese science meaningfully advance over the long run given that an estimated one-third of papers were thought to include fabricated or falsified data?

Smugly, I thought that this was a uniquely Chinese problem related to a politicized academic system that excessively emphasized number and prestige of publications, even paying scientists and their institut

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