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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.
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.
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.
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.
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.
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.
Deep learning has revolutionized the technology industry, but beyond eye-catching applications such as virtual assistants, recommender systems and self-driving cars, deep learning is also transforming many scientific fields.
The online availability of large amounts of publicly posted images and other data is fuelling machine learning research and applications. However, it is time to take privacy concerns seriously.
Artificial intelligence (AI) has recently re-emerged from the intersection of many fields, directing its collective energy at the building and studying of intelligent machines.
Preprints provide an efficient way for scientific communities to share and discuss results. We encourage authors to post preprints on arXiv, bioRxiv or other recognized community preprint platforms.
As artificial intelligence, robotics and machine learning are high on the agenda everywhere, Nature Machine Intelligence launches to stimulate collaborations between different disciplines.
