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Summary

ML Tools' Potential in Biology

This is a news story, published by MSN, that relates primarily to ML news.

biology news

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AI tools
ZME Science

ZME Science

•

For better or worse, machine learning is shaping biology research

ZME Science
Summary
Nutrition label

86% Informative

Machine learning ( ML ) tools are a subset of artificial intelligence ( AI ) that use mathematical models to recognize patterns between input and output.

ML tools have made a significant impact in fields like finance, logistics, and marketing, their potential in scientific research is especially exciting.

When it comes to biology, better ML technology is already producing noticeable impacts.

Scientists relying too heavily on AI ’s predictive capabilities can give scientists a false sense of understanding the “why” and “how” of a phenomenon.

When biologists use ML tools without a thorough understanding of how they work, they might overlook the limitations of these tools, leading to misinterpretations.

Biases in the training data present another significant risk: bias in the data reflects historical biases.

VR Score

88

Informative language

90

Neutral language

15

Article tone

semi-formal

Language

English

Language complexity

66

Offensive language

not offensive

Hate speech

not hateful

Attention-grabbing headline

not detected

Known propaganda techniques

not detected

Time-value

long-living

External references

28

https://www.nature.com/articles/d41586-024-01555-xhttps://www.nature.com/articles/s41592-023-02087-4https://www.nature.com/articles/s41586-024-07487-whttps://www.nature.com/articles/d41586-024-03708-4https://www.zmescience.com/feature-post/pieces/the-nobel-prizes-this-year-are-an-ai-bonanza/https://hdsr.mitpress.mit.edu/pub/f9kuryi8/release/8https://www.pbs.org/newshour/science/genetic-research-has-a-white-bias-and-it-may-be-hurting-everyones-healthhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021588/https://sites.google.com/view/stockholm-declarationhttps://bit.ly/3O7EwAchttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352112/https://responsiblebiodesign.ai/https://www.science.org/doi/10.1126/science.adk4858https://www.zmescience.com/science/news-science/for-better-or-worse-machine-learning-is-shaping-biology-research/https://www.nature.com/articles/s41580-021-00407-0https://www.nature.com/articles/s41586-024-07146-0https://www.springernature.com/gp/researchers/campaigns/dei-insightshttps://crsreports.congress.gov/product/pdf/R/R47849https://www.un.org/sites/un2.un.org/files/governing_ai_for_humanity_final_report_en.pdfhttps://www.science.org/doi/10.1126/science.ade2574https://cshperspectives.cshlp.org/content/15/12/a041473.longhttps://pmc.ncbi.nlm.nih.gov/articles/PMC7614889/https://www.nobelturingchallenge.org/https://www.pnas.org/doi/10.1073/pnas.2205058119https://iapp.org/resources/article/global-ai-legislation-tracker/https://www.fda.gov/vaccines-blood-biologics/artificial-intelligence-and-machine-learning-aiml-biological-and-other-products-regulated-cberhttps://www.science.org/content/article/limits-access-deepmind-s-new-protein-program-trigger-backlashhttps://deepmind.google/technologies/alphafold/

Source diversity

19

www.nature.comwww.zmescience.comhdsr.mitpress.mit.eduwww.pbs.orgwww.ncbi.nlm.nih.govsites.google.combit.lyresponsiblebiodesign.aiwww.science.orgwww.springernature.comcrsreports.congress.govwww.un.orgcshperspectives.cshlp.orgpmc.ncbi.nlm.nih.govwww.nobelturingchallenge.orgwww.pnas.orgiapp.orgwww.fda.govdeepmind.google

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