An industry-backed researcher who has forged a career sowing doubt about the dangers of pollutants is attempting to use artificial intelligence (AI) to amplify his perspective. Louis Anthony "Tony" Cox Jr, a Denver-based risk analyst and former Trump adviser who once reportedly claimed there is no proof that cleaning air saves lives, is developing an AI application to scan academic research for what he sees as the false conflation of correlation with causation. Cox has described the project as an attempt to weed "propaganda" out of epidemiological research and perform "critical thinking at scale" in emails to industry researchers, which were obtained via Freedom of Information Act requests by the Energy and Policy Institute, a non-profit advocacy group, and exclusively reviewed by the Guardian. He has long leveled accusations of flimsiness at research linking exposure to chemical compounds with health dangers, including on behalf of polluting interests such as cigarette manufacturer Philip Morris and the American Petroleum Institute – a fossil fuel lobbying group he has even allowed to "copy edit" his findings. Both the tobacco and oil industries have a history of weaponizing scientific uncertainty, experts say, with some arguing that similar tactics drive the Trump administration's current deregulatory efforts. The president's May "gold standard" science order, for instance, empowered his appointees to "correct scientific information" and "discipline" those who breach the administration's views, prompting outrage from some scientists. Cox has obtained funding to develop the new AI reviewer from the American Chemistry Council (ACC), the nation's largest chemical industry advocacy group, which counts oil and chemical giants such as Exxon and DuPont as members.

Google's plan to monitor home activities "crosses a moral boundary" that "needlessly encourages a conflict between science and ethics," says Australia's chief science adviser Alan Finkel. Earlier this month Google obtained a patent on the use of an array of sensors and cameras to monitor home life, and claims the technology has the capability to see the title of the book you're reading in bed. The system could also electronically lock doors and turn off running taps. Speaking at an artificial intelligence (AI) summit at Monash University, Melbourne on Thursday, Finkel likened this to a complete stranger offering you unlimited furniture and non-stick frying pans, in exchange for sitting in your bedroom for the next fortnight to observe your behaviour. "We are repulsed by this prospect not because of its unfamiliarity, but because we innately feel that it violates fundamental principles we rightfully hold dear," Finkel said.

Alan Finkel, speaking at an artificial intelligence summit at Monash University in Melbourne on Thursday, said there was a "golden opportunity" for Australia to be a world leader in scientific discovery while also holding to the ideals of a virtuous society. He said there was enormous potential for artificial intelligence to deliver substantial benefits to Australians in areas as varied as manufacturing and financial services. Chief Scientist Alan Finkel says the advent of artificial intelligence will need both technological as well as ethical considerations. But Dr Finkel pointed to how Google this month obtained a patent to use sensors and cameras to monitor home activity. It claims to be able to work out the title of a book someone is reading in their bed.

With new technology available to us, we're inching closer to the end of the days when deciphering ancient languages is a painstaking task filled with frustration and confusion. Nifty machines following complex algorithms are helping researchers around the globe as they take on the often monumental task of understanding ancient texts and lost languages. Big Think reports that linguistic experts estimate there have been approximately 31,000 languages spoken throughout human history. Many of them are now dead and forgotten, but a new AI project may be part of the answer in how to decipher the writing of ancient languages. "While languages change, many of the symbols and how the words and characters are distributed stay relatively constant over time. Because of that, you could attempt to decode a long-lost language if you understood its relationship to a known progenitor language."

Artificial intelligence (AI) might be technology's Holy Grail, but Australia's Human Rights Commissioner Edward Santow has warned about the need for responsible innovation and an understanding of the challenges new technology poses for basic human rights. "AI is enabling breakthroughs right now: Healthcare, robotics, and manufacturing; pretty soon we're told AI will bring us everything from the perfect dating algorithm to interstellar travel -- it's easy in other words to get carried away, yet we should remember AI is still in its infancy," Santow told the Human Rights & Technology conference in Sydney in July. Santow was launching the Human Rights and Technology Issues Paper, which was described as the beginning of a major project by the Human Rights Commission to protect the rights of Australians in a new era of technological change. The paper [PDF] poses questions centred on what protections are needed when AI is used in decisions that affect the basic rights of people. It asks also what is required from lawmakers, governments, researchers, developers, and tech companies big and small. Pointing to Microsoft's AI Twitter bot Tay, which in March 2016 showed the ugly side of humanity -- at least as present on social media -- Santow said it is a key example of how AI must be right before it's unleashed onto humans.

Driverless cars could make our roads safer and reduce congestion. But the algorithms driving them will also have to make life-or-death decisions. At some stage in the future, a fully autonomous car may determine who lives and who dies on our roads. These machines are being tested right now and Australian politicians are looking overseas for leadership, emboldened by the promise of fewer fatalities and less congestion. At the moment, there must be a human behind the wheel of these cars at all times, but government agencies are already working on a legal framework for when machines are totally in control.

Here's a question: do you consider yourself to be a trusting person? Or let me put it another way: would you put your life in the hands of a total stranger? This morning I woke up. I switched on the light – trusting that I wouldn't be electrocuted by a faulty lamp, or cord, or socket. I prepared my breakfast – trusting that I wouldn't be poisoned by salmonella in my factory-processed muesli.

Let's get the basics over with," W said to M when they met on a 4-minute speed date. I am fresh from the shower, wrapped in just a towel and smelling of mild herbal soaps (both shower and soaps are required), standing at the door to the tank. It resembles a shower door--knee-high, sliding--and opens to reveal a...READ MORE They talked about where they were from (she hailed from Iowa, he from New Jersey), life in a small town, and the transition to college. An eavesdropper would have been hard-pressed to detect a romantic spark in this banal back-and-forth. Yet when researchers, who had recorded the exchange, ran it through a language-analysis program, it revealed what W and M confirmed to be true: They were hitting it off. The researchers weren't interested in what the daters discussed, or even whether they seemed to share personality traits, backgrounds, or interests.

Twitter, used in 200 countries with over 250 milliontweets a day, is a rich source of local news from aroundthe world. Many events of local importance are first reportedon Twitter, including many that never reach newschannels. Further, there are often only a few tweetsreporting each such event, in contrast with the largervolumes that follow events of wider significance. Eventhough such events may be primarily of local importance,they can also be of critical interest to some specificbut possibly far flung entities: For example, a firein a supplier’s factory half-way around the world maybe of interest even from afar. In this paper we describehow this ‘long tail’ of events can be detected in spite oftheir sparsity.We then extract and correlate informationfrom multiple tweets describing the same event. Ourgeneric architecture for converting a tweet-stream intoevent-objects uses locality sensitive hashing, classification,boosting, information extraction and clustering.Our results, based on millions of tweets monitored overmany months, appear to validate our approach and architecture:We achieved success-rates in the 80% rangefor event detection and 76% on event-correlation; we also reduced tweet-comparisons by 80% using LSH.