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Volume 2 Issue 10, October 2020

Auditable autonomy on the road

Neural networks will have limited utility in high-risk environments unless their outputs can be reliably explained. In the cover image, Hasani et al. show how a compact controller inspired by the neural architecture of a roundworm may provide more robust and explainable outputs in a lane-following task. Also in this issue, Jiménez-Luna et al. review how explainable artificial intelligence approaches could aid in drug discovery.

See Lechner et al.

Image: Alexander Amini, Massachusetts Institute of Technology. Cover design: Karen Moore.


  • Robots can relieve humans of dangerous tasks. With the pandemic making physical contact potentially dangerous due to the risk of contagion, a new focus for robotic applications in healthcare has come into view.



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Comment & Opinion

  • For machine learning developers, the use of prediction tools in real-world clinical settings can be a distant goal. Recently published guidelines for reporting clinical research that involves machine learning will help connect clinical and computer science communities, and realize the full potential of machine learning tools.

    • Bilal A. Mateen
    • James Liley
    • Sebastian J. Vollmer
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News & Views

  • Finding states of matter with properties that are just right is a main challenge from metallurgy to quantum computing. A data-driven optimization approach based on gaming strategies could help.

    • Eliska Greplova
    News & Views
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  • Evidence syntheses produced from the scientific literature are important tools for policymakers. Producing such evidence syntheses can be highly time- and labour-consuming but machine learning models can help as already demonstrated in the health and medical sciences. This Perspective describes a machine learning-based framework specifically designed to support evidence syntheses in the area of agricultural research, for tackling the UN Sustainable Development Goal 2: zero hunger by 2030.

    • Jaron Porciello
    • Maryia Ivanina
    • Haym Hirsh
  • Robots could play an important part in transforming healthcare to cope with the COVID-19 pandemic. This Perspective highlights how robotic technology integrated in a range of tasks in the surgical environment could help to ensure a continuation of medical services while reducing the risk of infection.

    • Ajmal Zemmar
    • Andres M. Lozano
    • Bradley J. Nelson
  • Drug discovery has recently profited greatly from the use of deep learning models. However, these models can be notoriously hard to interpret. In this Review, Jiménez-Luna and colleagues summarize recent approaches to use explainable artificial intelligence techniques in drug discovery.

    • José Jiménez-Luna
    • Francesca Grisoni
    • Gisbert Schneider
    Review Article
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