As the popularity of self-driving cars increases, so do the concerns. Last month, China banned tests of autonomous vehicles on public roads. And investigations continue into the death of Joshua Brown, who was killed when his Tesla car on autopilot ploughed into the side of an articulated truck in Florida. His car used visible-light cameras to image the road and computers to evaluate the situation. But according to Tesla, the white truck merged with the bright Florida sky and was not recognized.

Many choices that people consider their own are already determined by algorithms. Fridges, coffee machines, toothbrushes, phones and smart devices are all now equipped with communicating sensors. In ten years, 150 billion'things' will connect with each other and with billions of people. The'Internet of Things' will generate data volumes that double every 12 hours rather than every 12 months, as is the case now.

The fully programmable Nao robot has been used to experiment with machine ethics. In his 1942 short story'Runaround', science-fiction writer Isaac Asimov introduced the Three Laws of Robotics -- engineering safeguards and built-in ethical principles that he would go on to use in dozens of stories and novels. They were: 1) A robot may not injure a human being or, through inaction, allow a human being to come to harm; 2) A robot must obey the orders given it by human beings, except where such orders would conflict with the First Law; and 3) A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws. Fittingly, 'Runaround' is set in 2015. Real-life roboticists are citing Asimov's laws a lot these days: their creations are becoming autonomous enough to need that kind of guidance.

There is a strong possibility that in the not-too-distant future, artificial intelligences (AIs), perhaps in the form of robots, will become capable of sentient thought. Whatever form it takes, this dawning of machine consciousness is likely to have a substantial impact on human society. Microsoft co-founder Bill Gates and physicist Stephen Hawking have in recent months warned of the dangers of intelligent robots becoming too powerful for humans to control. The ethical conundrum of intelligent machines and how they relate to humans has long been a theme of science fiction, and has been vividly portrayed in films such as 1982's Blade Runner and this year's Ex Machina. Academic and fictional analyses of AIs tend to focus on human–robot interactions, asking questions such as: would robots make our lives easier?

This year, several leading researchers have sounded warnings about the risks of using the CRISPR gene-editing technique to modify human1 and other species' genomes in ways that could have "unpredictable effects on future generations"2 and "profound implications for our relationship to nature" (see go.nature.com/jq5sik). Concerns are coming from the silicon sector as well. Last year, the physicist Stephen Hawking proclaimed that rapidly advancing artificial intelligence (AI) could destroy the human race. And in 2013, former Royal Society president Martin Rees co-founded the Centre for the Study of Existential Risk at the University of Cambridge, UK, in part to study threats from advanced AI. Leaders of the scientific community are ready to share the responsibility for these powerful technologies with the public. George Church, a geneticist at Harvard University in Cambridge, Massachusetts, and others wrote last year of CRISPR that "the decision of when and where to apply this technology, and for what purposes, will be in our collective hands".

'Twas the week before Christmas, and all through the United Kingdom, scientists were waiting nervously to see how many glittering prizes the government would stuff into their stockings. Those prizes -- the results of the Research Excellence Framework (REF) exercise, to be announced on 18 December -- will go some way towards determining which researchers in UK universities have a happy New Year. The scale and importance of this assessment of publicly funded research is unique to the United Kingdom. The winners enjoy high-quality ratings for their academic departments and the guarantee of a hefty chunk of cash to support their research. A poor rating can see a department starved of money or even closed down.

Three research papers about the potential power of computers to outsmart us -- while comforting us with cute pet videos -- caught the attention of the online science community this week. Researchers shared a PLoS ONE paper about a computational fact-checker that can sort truth from fiction; an arXiv preprint about a computer program that can read and comprehend news stories; and a study of the psychology of watching Internet cat videos. In the PLoS ONE paper1, researchers at Indiana University in Bloomington mined Wikipedia's information boxes, which summarize the key facts in most Wikipedia entries, to create a'knowledge graph' of 3 million people, places and things. The resulting algorithm could then use that knowledge to gauge the truth of simple statements that were presented to it, such as "Rome is the capital of Italy", with nearly the same accuracy as human fact-checkers. The researchers acknowledge that the source material is not 100% reliable, something that online commenters also noted.

Particle collisions at the Large Hadron Collider produce huge amounts of data, which algorithms are well placed to process. The next generation of particle-collider experiments will feature some of the world's most advanced thinking machines, if links now being forged between particle physicists and artificial intelligence (AI) researchers take off. Such machines could make discoveries with little human input -- a prospect that makes some physicists queasy. Driven by an eagerness to make discoveries and the knowledge that they will be hit with unmanageable volumes of data in ten years' time, physicists who work on the Large Hadron Collider (LHC), near Geneva, Switzerland, are enlisting the help of AI experts. On 9–13 November, leading lights from both communities attended a workshop -- the first of its kind -- at which they discussed how advanced AI techniques could speed discoveries at the LHC. Particle physicists have "realized that they cannot do it alone", says Cécile Germain, a computer scientist at the University of Paris South in Orsay, who spoke at the workshop at CERN, the particle-physics lab that hosts the LHC.

Robin Li, head of China's web giant Baidu, unveils the firm's intelligent digital assistant, Duer. When Andrew Ng joined Google from Stanford University in 2011, he was among a trickle of artificial-intelligence (AI) experts in academia taking up roles in industry. Five years later, demand for expertise in AI is booming -- and a torrent of researchers is following Ng's lead. The laboratories of tech titans Google, Microsoft, Facebook, IBM and Baidu (China's web-services giant) are stuffed with ex-university scientists, drawn to private firms' superior computing resources and salaries. "Some people in academia blame me for starting part of this," says Ng, who in 2014 moved again to become chief scientist at Baidu, working at the company's research lab in California's Silicon Valley.

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