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  • A research paper makes the most impact when its methods, data and code are available for others to use and build on. We highlight the benefits of good sharing practices with a new type of article, reusability reports.

  • Artificial intelligence can be defined as intelligence demonstrated by machines. But what counts as intelligence, and how intelligence is implemented in different kinds of machines, robots and software varies across disciplines and over time.

  • Synthesizing robots via physical artificial intelligence is a multidisciplinary challenge for future robotics research. An education methodology is needed for researchers to develop a combination of skills in physical artificial intelligence.

    • Aslan Miriyev
    • Mirko Kovač
  • Addressing the problems caused by AI applications in society with ethics frameworks is futile until we confront the political structure of such applications.

    • Jathan Sadowski
    • Mark Andrejevic
  • 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.

  • 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
  • The challenge of practically integrating an ethical and social approach in the development and implementation of AI needs to be urgently addressed, to help restore public trust in technology.

  • The part that artificial intelligence plays in climate change has come under scrutiny, including from tech workers themselves who joined the global climate strike last year. Much can be done by developing tools to quantify the carbon cost of machine learning models and by switching to a sustainable artificial intelligence infrastructure.

    • Payal Dhar
    News Feature
  • OpenAI released a beta version of its language model, GPT-3. As artificial writing permeates our lives, the challenge is how to think clearly about what it is and what impact it could have on society.

  • 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
    • Alena Buyx
  • 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
  • AI tools used in society often enhance inequality, affecting Black lives disproportionally. Addressing this issue will require more than technological solutions. Researchers and experts in the field are overwhelmingly white and need to engage and listen to those experiencing the harm.

  • 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
    • Seán Ó hÉigeartaigh
  • Expectations are high for AI to help fight COVID-19. But before AI tools can make an impact, global collaboration and high-quality data and model sharing are needed.

  • Contact-tracing apps could help keep countries open before a vaccine is available. But do we have a sufficient understanding of their efficacy, and can we balance protecting public health with safeguarding civil rights? We interviewed five experts, with backgrounds in digital health ethics, internet law and social sciences.

    • Yann Sweeney
  • 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
    • Jean-Rémi King