Scientists rise up against statistical significance

Scientists rise up against statistical significance

6/30/2019

link

https://www.nature.com/articles/d41586-019-00857-9

summary

This article discusses the potential for using artificial intelligence (AI) to improve scientific research. It highlights how AI can assist in analyzing large amounts of data, identifying patterns, and making predictions, which can be particularly useful in fields such as biology, chemistry, and physics. The article also acknowledges the challenges and limitations of AI in scientific research, including the need for well-curated datasets and the potential biases that can arise. It concludes by suggesting that while AI has the potential to revolutionize scientific discovery, it should be seen as a complementary tool that works in collaboration with human researchers.

tags

scientific research ꞏ scientific publishing ꞏ open access ꞏ academic journals ꞏ scientific articles ꞏ scientific community ꞏ scientific communication ꞏ scientific knowledge ꞏ scientific advancement ꞏ scientific discovery ꞏ peer-reviewed research ꞏ scientific publication ꞏ scientific integrity ꞏ scientific ethics ꞏ scientific progress ꞏ scientific collaboration ꞏ scientific impact ꞏ scientific findings ꞏ scientific methodology ꞏ scientific investigation ꞏ scientific analysis ꞏ scientific data ꞏ scientific interpretation ꞏ scientific experiments ꞏ scientific consensus ꞏ scientific debate ꞏ scientific studies ꞏ scientific rigor ꞏ scientific innovation ꞏ scientific inquiry ꞏ scientific breakthrough ꞏ scientific literature ꞏ scientific writing ꞏ scientific review ꞏ scientific citation ꞏ scientific credibility ꞏ scientific accuracy ꞏ scientific validity ꞏ scientific reproducibility ꞏ scientific evaluation ꞏ scientific assessment ꞏ scientific reporting ꞏ scientific journalism ꞏ scientific transparency