News & Comment

  • Comment |

    The COVID-19 pandemic poses a historical challenge to society. The profusion of data requires machine learning to improve and accelerate COVID-19 diagnosis, prognosis and treatment. However, a global and open approach is necessary to avoid pitfalls in these applications.

    • Nathan Peiffer-Smadja
    • , Redwan Maatoug
    • , François-Xavier Lescure
    • , Eric D’Ortenzio
    • , Joëlle Pineau
    •  & Jean-Rémi King
  • Comment |

    In an unprecedented effort of scientific collaboration, researchers across fields are racing to support the response to COVID-19. Making a global impact with AI tools will require scalable approaches for data, model and code sharing; adapting applications to local contexts; and cooperation across borders.

    • Miguel Luengo-Oroz
    • , Katherine Hoffmann Pham
    • , Joseph Bullock
    • , Robert Kirkpatrick
    • , Alexandra Luccioni
    • , Sasha Rubel
    • , Cedric Wachholz
    • , Moez Chakchouk
    • , Phillippa Biggs
    • , Tim Nguyen
    • , Tina Purnat
    •  & Bernardo Mariano
  • Comment |

    The attention and resources of AI researchers have been captured by COVID-19. However, successful adoption of AI models in the fight against the pandemic is facing various challenges, including moving clinical needs as the epidemic progresses and the necessity to translate models to local healthcare situations.

    • Yipeng Hu
    • , Joseph Jacob
    • , Geoffrey J. M. Parker
    • , David J. Hawkes
    • , John R. Hurst
    •  & Danail Stoyanov
  • Editorial |

    Scientists have been getting concerned about the carbon footprint of international meetings and have been asking whether travelling to conferences is the best use of their time and funds. 2020 is turning out to be the year that many organizers decide to go virtual — and this was before COVID-19.

  • News & Views |

    To deploy robot swarms in our daily lives, they need to be resilient to malfunctioning errors and protected against malicious attacks. Blockchain technology could provide an essential level of protection.

    • Andreagiovanni Reina
  • Comment |

    The Catholic Church is challenged by scientific and technological innovation but can help to integrate multiple voices in the ongoing dialogue regarding AI and machine ethics. In this context, a multidisciplinary working group brought together by the Church reflected on roboethics, explored the themes of embodiment, agency and intelligence.

    • Edoardo Sinibaldi
    • , Chris Gastmans
    • , Miguel Yáñez
    • , Richard M. Lerner
    • , László Kovács
    • , Carlo Casalone
    • , Renzo Pegoraro
    •  & Vincenzo Paglia
  • Comment |

    As artificial intelligence becomes prevalent in society, a framework is needed to connect interpretability and trust in algorithm-assisted decisions, for a range of stakeholders.

    • Julia Stoyanovich
    • , Jay J. Van Bavel
    •  & Tessa V. West
  • Comment |

    As robotic systems become more autonomous, it gets less straightforward to determine liability when humans are harmed. This is an emerging challenge, with legal implications, in the field of surgical robotic systems. The iRobotSurgeon Survey explores public opinions about responsibility and liability in the area of surgical robotics.

    • Aimun A. B. Jamjoom
    • , Ammer M. A. Jamjoom
    •  & Hani J. Marcus
  • Editorial |

    The worldwide outbreak of COVID-19 has led to great tragedy and poses unprecedented challenges for countries’ healthcare systems. Data has become an important instrument in the global fight against the unprecedented spread of the virus. But how will we ensure a return to previous forms of data privacy once the pandemic subsides?

  • Editorial |

    Generative deep learning can produce artificial, natural-looking images and other data, which has many promising applications in research — and in art. But the wide availability of generative models poses a challenge for society, which needs tools and best practices to distinguish between real and synthetic data.

  • News & Views |

    Recurrent networks can be trained using a generalization of backpropagation, called backpropagation through time, but a gap exists between the mathematics of this learning algorithm and biological plausibility. E-prop is a biologically inspired alternative that opens up possibilities for a new generation of online training algorithms for recurrent networks.

    • Luca Manneschi
    •  & Eleni Vasilaki
  • Q&A |

    Martial Hebert is the director of the Robotics Institute and dean of the School of Computer Science at Carnegie Mellon University. We spoke with him at the O’Reilly AI Conference in New York in April 2019, where he delivered a keynote talk, ‘AI and the robotics revolution’, and in a follow-up conversation.

    • Trenton Jerde
  • Editorial |

    In a recent workshop at the Conference on Neural Information Processing Systems (NeurIPS), future directions at the intersection of neuroscience and AI were considered. A panel discussion at the end of the day started with a provocative question: do we need AI to understand the brain?

  • Correspondence |

    • Adam Poulsen
    • , Eduard Fosch-Villaronga
    •  & Roger Andre Søraa
  • Comment |

    Machine learning models have great potential in biomedical applications. A new platform called GradioHub offers an interactive and intuitive way for clinicians and biomedical researchers to try out models and test their reliability on real-world, out-of-training data.

    • Abubakar Abid
    • , Ali Abdalla
    • , Ali Abid
    • , Dawood Khan
    • , Abdulrahman Alfozan
    •  & James Zou
  • News & Views |

    Our understanding of concepts can differ depending on the modality — such as vision, text or speech — through which we learn this concept. A recent study uses computational modelling to demonstrate how conceptual understanding aligns across modalities.

    • Jessica S. Horst
    •  & Chris M. Bird
  • Editorial |

    Welcome to the new year, new decade and second volume of Nature Machine Intelligence.

  • News & Views |

    Tree-based models are among the most popular and successful machine learning algorithms in practice. New tools allow us to explain the predictions and gain insight into the global behaviour of these models.

    • Wojciech Samek
  • Comment |

    Many high-level ethics guidelines for AI have been produced in the past few years. It is time to work towards concrete policies within the context of existing moral, legal and cultural values, say Andreas Theodorou and Virginia Dignum.

    • Andreas Theodorou
    •  & Virginia Dignum
  • Feature |

    There is no shortage of opinions on the impact of artificial intelligence and deep learning. We invited authors of Comment and Perspective articles that we published in roughly the first half of 2019 to look back at the year and give their thoughts on how the issue they wrote about developed.

    • Alexander S. Rich
    • , Cynthia Rudin
    • , David M. P. Jacoby
    • , Robin Freeman
    • , Oliver R. Wearn
    • , Henry Shevlin
    • , Kanta Dihal
    • , Seán S. ÓhÉigeartaigh
    • , James Butcher
    • , Marco Lippi
    • , Przemyslaw Palka
    • , Paolo Torroni
    • , Shannon Wongvibulsin
    • , Edmon Begoli
    • , Gisbert Schneider
    • , Stephen Cave
    • , Mona Sloane
    • , Emmanuel Moss
    • , Iyad Rahwan
    • , Ken Goldberg
    • , David Howard
    • , Luciano Floridi
    •  & Jack Stilgoe
  • News & Views |

    Photonic computing devices are a compelling alternative to conventional computing setups for machine learning applications, as they are nonlinear, fast and easy to parallelize. Recent work demonstrates the potential of these optical systems to process and classify human motion from video.

    • Kathy Lüdge
    •  & André Röhm
  • News & Views |

    Origami engineering has long held the promise of complex and futuristic machines. A new foldable haptics system shows that this paradigm can be functional as well.

    • Samuel Felton
  • Editorial |

    The reach of artificial intelligence technologies across all parts of society is steadily growing, but so is the awareness of how they can negatively impact human rights. As 2019 draws to a close, the trajectory of technological progress defined by big technology companies is meeting resistance.

  • Challenge Accepted |

    A new open challenge tests whether algorithmic models can explain human brain activity in cognitive tasks and encourages interaction between researchers studying natural and artificial intelligence.

    • Radoslaw Martin Cichy
    • , Gemma Roig
    •  & Aude Oliva
  • News & Views |

    Loss-of-function mutations in metal-binding proteins are heavily implicated with numerous diseases, and identifying such ‘cracks’ will be valuable to biologists and medical doctors in the study and treatment of disease. A deep learning approach has been developed to tackle this challenging task.

    • Yuan Liu
    •  & Chu Wang
  • Comment |

    Artificial intelligence and machine learning are increasingly seen as key technologies for building more decentralized and resilient energy grids. However, researchers must consider the ethical and social implications of these developments.

    • Valentin Robu
    • , David Flynn
    • , Merlinda Andoni
    •  & Maizura Mokhtar
  • Editorial |

    Robots are making a transition into human environments, where they can directly interact with us, in shops, hospitals, schools and more. Transparency about robots’ capabilities and level of autonomy should be integrated into the design from the start.

  • News & Views |

    In cooperative games, humans are biased against AI systems even when such systems behave better than our human counterparts. This raises a question: should AI systems ever be allowed to conceal their true nature and lie to us for our own benefit?

    • Michael Rovatsos
  • Challenge Accepted |

    The first Smart Cities Robotics Challenge, organized by the European Robotics League, took place from 18–21 September at the Centre:MK shopping centre in Milton Keynes. The competition tested the ability of robots to interact with humans in everyday tasks as well as with the digital infrastructure of a smart city.

    • Jacob Huth
  • News & Views |

    Adversarial attacks make imperceptible changes to a neural network’s inputs so that it recognizes it as something entirely different. This flaw can give us insight into how these networks work and how to make them more robust.

    • Gean T. Pereira
    •  & André C. P. L. F. de Carvalho
  • Comment |

    Artificial intelligence systems copy and amplify existing societal biases, a problem that by now is widely acknowledged and studied. But is current research of gender bias in natural language processing actually moving towards a resolution, asks Marta R. Costa-jussà.

    • Marta R. Costa-jussà
  • Challenge Accepted |

    Tired of training neural networks? Try optimizing virtual creatures instead.

    • Sam Kriegman
  • Editorial |

    The organizers of Cognitive Computational Neuroscience, a relatively new AI-themed meeting held recently in Berlin, are dedicated to encouraging informal interactions and conversations to tackle the challenge of bridging scientific cultures.

  • Editorial |

    Brain–machine interfaces were envisioned already in the 1940s by Norbert Wiener, the father of cybernetics. The opportunities for enhancing human capabilities and restoring functions are now quickly expanding with a combination of advances in machine learning, smart materials and robotics.

  • Challenge Accepted |

    To safely operate in the real world, robots need to evaluate how confident they are about what they see. A new competition challenges computer vision algorithms to not just detect and localize objects, but also report how certain they are.

    • Niko Sünderhauf
    • , Feras Dayoub
    • , David Hall
    • , John Skinner
    • , Haoyang Zhang
    • , Gustavo Carneiro
    •  & Peter Corke
  • Comment |

    In order for the neuromorphic research field to advance into the mainstream of computing, it needs to start quantifying gains, standardize on benchmarks and focus on feasible application challenges.

    • Mike Davies
  • Challenge Accepted |

    As nations come together in Tokyo next summer to celebrate the spirit of human potential in the 2020 Olympic Games, they will have a chance to take part in another international competition hosted by Japan soon after, this time with challenges designed for robot contenders.

    • Liesbeth Venema
  • Comment |

    To create less harmful technologies and ignite positive social change, AI engineers need to enlist ideas and expertise from a broad range of social science disciplines, including those embracing qualitative methods, say Mona Sloane and Emanuel Moss.

    • Mona Sloane
    •  & Emanuel Moss
  • Editorial |

    As machine learning methods are adopted across the scientific community, strong code sharing and reviewing practices are required. Our policy mandates that code essential to the main results is made available to reviewers, and to readers on publication. Our partnership with Code Ocean helps authors and reviewers navigate this process.

  • News & Views |

    DeepMind’s AlphaFold recently demonstrated the potential of deep learning for protein structure prediction. DeepFragLib, a new protein-specific fragment library built using deep neural networks, may have advanced the field to the next stage.

    • Guo-Wei Wei
  • Comment |

    Deepfakes are a new dimension of the fake news problem. The criminal misuse of this technology poses far-reaching challenges and can threaten national security. Technological and governance solutions are needed to address this.

    • Irakli Beridze
    •  & James Butcher
  • News & Views |

    To prepare robots for working autonomously under real-world conditions, their resilience and capability to recover from damage needs to improve radically. A fresh take on robot design suggests that instead of adapting the robotic control strategy, we could enable robots to change their physical bodies to recover more effectively from damage.

    • Helmut Hauser
  • Challenge Accepted |

    Could this be the year that AI is going to surpass human performance in playing the popular video game Angry Birds? The organizers of the annual AIBIRDS competition discuss the challenges involved.

    • Jochen Renz
    • , XiaoYu Ge
    • , Matthew Stephenson
    •  & Peng Zhang
  • Editorial |

    Civil liberty groups are raising the alarm over the ubiquitous use of automated facial recognition. As a society, we need to decide on the acceptable use of this technology and how to build in safeguards to protect human rights.