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The Perils of Machine Learning in Designing New Chemicals and Materials

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Illustration of a head filled with computer code and digital circuitry.

As machine-learning tools become more broadly available for communities to use when making new compounds and materials, the possibilities of misuse also increase.

Credit: Getty Images

Machine learning (ML) is poised to revolutionize practice in chemistry and materials science, but too little attention is being paid to the potential downsides.

Just as the machine-learning analysis of bodily fluids might be used to develop medicines targeted to an individual, it may also be used to engineer viruses or toxins that might infect only certain people depending on their genes. Similarly, while ML might help to invent improved materials, such as biodegradable plastics and longer-lasting batteries, it could also be used to design a tasteless compound that is used to poison a community's water supply.

From Nature Machine Intelligence
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