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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.

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.

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

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.

To attract and retain talent from all backgrounds, new educational models and mentorship programmes are needed in machine intelligence, says Shannon Wongvibulsin.

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.

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.