• Comment |

    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
    • , Alastair K. Denniston
    • , Chris C. Holmes
    •  & Sebastian J. Vollmer
  • Comment |

    There is a need to consider how AI developers can be practically assisted in identifying and addressing ethical issues. In this Comment, a group of AI engineers, ethicists and social scientists suggest embedding ethicists into the development team as one way of improving the consideration of ethical issues during AI development.

    • Stuart McLennan
    • , Amelia Fiske
    • , Leo Anthony Celi
    • , Ruth Müller
    • , Jan Harder
    • , Konstantin Ritt
    • , Sami Haddadin
    •  & Alena Buyx
  • Comment |

    As robot swarms move from the laboratory to real-world applications, a routine checklist of questions could help ensure their safe operation.

    • Edmund R. Hunt
    •  & Sabine Hauert
  • Comment |

    Artificial intelligence tools can help save lives in a pandemic. However, the need to implement technological solutions rapidly raises challenging ethical issues. We need new approaches for ethics with urgency, to ensure AI can be safely and beneficially used in the COVID-19 response and beyond.

    • Asaf Tzachor
    • , Jess Whittlestone
    • , Lalitha Sundaram
    •  & Seán Ó hÉigeartaigh
  • 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
  • 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 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
  • 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 |

    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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • Comment |

    To develop scientific methods for evaluation in robotics, the field requires a more stringent definition of the subject of study, says Signe Redfield, focusing on capabilities instead of physical systems.

    • Signe Redfield
  • Comment |

    The European Commission’s report ‘Ethics guidelines for trustworthy AI’ provides a clear benchmark to evaluate the responsible development of AI systems, and facilitates international support for AI solutions that are good for humanity and the environment, says Luciano Floridi.

    • Luciano Floridi
  • Comment |

    There is much to be gained from interdisciplinary efforts to tackle complex psychological notions such as ‘theory of mind’. However, careful and consistent communication is essential when comparing artificial and biological intelligence, say Henry Shevlin and Marta Halina.

    • Henry Shevlin
    •  & Marta Halina
  • Comment |

    If we are to realize the potential of self-driving cars, we need to recognize the limits of machine learning. We should not pretend self-driving cars are around the corner: it will still take substantial time and effort to integrate the technology safely and fairly into our societies.

    • Jack Stilgoe
  • Comment |

    Technology companies have quickly become powerful with their access to large amounts of data and machine learning technologies, but consumers could be empowered too with automated tools to protect their rights.

    • Marco Lippi
    • , Giuseppe Contissa
    • , Francesca Lagioia
    • , Hans-Wolfgang Micklitz
    • , Przemysław Pałka
    • , Giovanni Sartor
    •  & Paolo Torroni
  • Comment |

    After a difficult start, medicinal chemists are now ready to embrace AI-based methods and concepts in drug discovery, explains Gisbert Schneider.

    • Gisbert Schneider
  • Comment |

    Artificial intelligence (AI) promises to be an invaluable tool for nature conservation, but its misuse could have severe real-world consequences for people and wildlife. Conservation scientists discuss how improved metrics and ethical oversight can mitigate these risks.

    • Oliver R. Wearn
    • , Robin Freeman
    •  & David M. P. Jacoby
  • Comment |

    Debate about the impacts of AI is often split into two camps, one associated with the near term and the other with the long term. This divide is a mistake — the connections between the two perspectives deserve more attention, say Stephen Cave and Seán S. ÓhÉigeartaigh.

    • Stephen Cave
    •  & Seán S. ÓhÉigeartaigh
  • Comment |

    Ken Goldberg reflects on how four exciting sub-fields of robotics — co-robotics, human–robot interaction, deep learning and cloud robotics — accelerate a renewed trend toward robots working safely and constructively with humans.

    • Ken Goldberg