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  • OUTLOOK

Why artificial intelligence needs to understand consequences

A machine with a grasp of cause and effect could learn more like a human, through imagination and regret.
  1. Neil Savage

    1. Neil Savage is a freelance writer in Lowell, Massachusetts.

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Animated gif of a Newton's cradle in which the typical balls have been replaced by zeroes and ones on strings

Credit: Neil Webb

When Rohit Bhattacharya began his PhD in computer science, his aim was to build a tool that could help physicians to identify people with cancer who would respond well to immunotherapy. This form of treatment helps the body’s immune system to fight tumours, and works best against malignant growths that produce proteins that immune cells can bind to. Bhattacharya’s idea was to create neural networks that could profile the genetics of both the tumour and a person’s immune system, and then predict which people would be likely to benefit from treatment.

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doi: https://doi.org/10.1038/d41586-023-00577-1

This article is part of Nature Outlook: Robotics and artificial intelligence, an editorially independent supplement produced with the financial support of third parties. About this content.

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