Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Artists have always been at the forefront of experimenting with digital tools. The AI: More than Human exhibition at the Barbican Centre, London (until August 26th), features some intriguing AI-inspired installations. We spoke to four artists about their work and influences.
Rebuilding particle trajectories from high-energy proton collisions is an essential step in processing the petabytes of data generated by the Large Hadron Collider at CERN. In search of an order of magnitude speed-up, physicists reached out to the computer science community.
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.
