While it might not always be easy to pull the plug on your electronics, doing so is rarely a case of moral dilemma. But, powering down might be a lot more difficult if your devices were begging you not to do it. A new study explores the ways in which social robots can manipulate their owners by pulling on our heartstrings. When robots protested, shouting things such as'No! Please do not switch me off' and implying they were afraid of the dark, participants hesitated and sometimes even refused to turn them off.

A decade ago, a group of Internet companies, civil society organizations, academics, and investors launched the Global Network Initiative (GNI), a collaborative effort to promote free expression and protect user privacy on the Internet. Google helped lead this effort and a parallel project devoted to developing a human rights framework for the Internet. In 2010, Google further demonstrated its leadership by making a principled decision to withdraw its search-engine services from China. In a very public way, the company acknowledged the inherent contradiction between Chinese Internet censorship and Google's commitments to its users and the GNI to promote free expression. It was thus disturbing to read recent reports suggesting that Google now is seriously considering re-entering the Chinese market and succumbing to Chinese censorship in exchange for commercial opportunity.

Hollywood producer Harvey Weinstein is seeking to get the criminal case against him thrown out of court. On Friday, his lawyers filed a defence motion citing dozens of "warm" emails they say Mr Weinstein received from one of his accusers after an alleged rape. His team argue prosecutors should have shared the evidence with the Grand Jury that indicted him. Mr Weinstein has pleaded not guilty to six charges involving three different women. The accuser in question has retained her anonymity.

The researchers collected photos of people of different races and Nao, a humanoid robot, and changed the color of the robot's shell to a variety of human skin tones. Their experimental setup relied on the "shooter bias" procedure, which has participants playing the role of a police officer who has to decide if they should or shouldn't shoot their gun when shown different images. Those photos had a person or Nao in it, either holding a weapon in their hand or some other, benign object. The study subjects saw the picture for only a split second and were asked to act on instinct. The study found that the participants were faster to shoot an armed black human and robot than they were to shoot their white counterparts.

Sarah Jeong, a technology journalist hired by the New York Times and vilified online for tweets comparing "dumbass f****** white people" to dogs and saying they would "all go extinct soon", has been targeted for harassment by dishonest trolls, her former employer has claimed. Editors at The Verge, an online tech magazine, denounced what they called "disingenuous" criticism of Ms Jeong by "people acting in bad faith". The senior writer had been the victim of a Gamergate-style campaign designed to "divide and conquer by forcing newsrooms to disavow their colleagues", they suggested. Ms Jeong, 30, posted a string of offensive and apparently racist messages including "#CancelWhitePeople" and "white men are bulls***" up to five years ago. After being uncovered they quickly spread and were picked up by conservative media including the Daily Caller and Gateway Pundit websites.

Most of the focus has been on economic growth (like China's ambition for a $150bn industry). But there has also been a flurry of interest in AI for good; a proliferation of events, organisations being set up (like AINow, OpenAI and AI4ALL in the US and the Ada Lovelace Institute or ElementAI's new London office focusing on AI for good, here in the UK). Some are real and some may turn out to be little more than hot air, or algorithmic greenwash. So what can we hope for? Through the half century history of AI, the direction of research and funding has been dominated by the military and intelligence.

One of our biggest learnings is that AI is best trained by diverse teams that help identify the right questions for AI algorithms to solve. For example, several teams used multi-terabytes of operational data in wealth management to train algorithms to drive higher trading income. The obvious approach was to focus on day traders, who are mostly single, 30-35 year old white males. One of the teams – with a set of diverse members beyond the usual data engineers and neural net experts – addressed that objective and also identified an even larger opportunity targeting single 50-55 year old women, which uncovered a high investible assets segment that previously had gone untapped. Diverse teams think of questions others may not even know to ask.

Amazon has applied for a patent for an audio system that detects the accent of a speaker and changes it to the accent of the listener, perhaps helping eliminate communication barriers in many situations and industries. The patent doesn't mean the company has made it (or necessarily that it will be granted), but there's also no technical reason why it can't do so. The application, spotted by Patent Yogi, describes "techniques for accent translation." Although couched in the requisite patent-ese, the method is quite clear. After a little translation of my own, here's what it says: In a two-party conversation, received audio is analyzed to see if it matches with one of a variety of stored accents.

The system is called Reinforcement Learning for Structural Evolution, known as ReLeaSE, and is an algorithm and computer program that comprises two neural networks which can be thought of as a teacher and a student. The teacher knows the syntax and linguistic rules behind the vocabulary of chemical structures for about 1.7 million known biologically active molecules. By working with the teacher, the student learns over time and becomes better at proposing molecules that are likely to be useful as new medicines. The University has applied for a patent for the technology, and the team published a proof-of-concept study in the journal Science Advances last week. "If we compare this process to learning a language, then after the student learns the molecular alphabet and the rules of the language, they can create new'words,' or molecules," said Tropsha.

"Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence--the human biological machine intelligence of our civilization--a billion-fold." When futurists warned that artificial intelligence would soon be doing jobs that humans once did, what did you envision? You may have seen jobs in construction and manufacturing as likely targets for a robotic labor revolution, for example--or perhaps accountants could be replaced with complex mathematical programs. To many, the law seemed to be more or less untouchable.