New Zealand scientists have invented a new volcano alert system that they say could have provided warning ahead of last year's White Island disaster. Twenty-one people died when the country's most active volcano, also called Whakaari, suddenly erupted last December with tourists on it. The new system uses machine learning algorithms to analyse real-time data to predict future eruptions. The research was publish in the journal Nature last week. One of the scientists involved in the project, Shane Cronin from the University of Auckland, told the BBC the current system had been "too slow to provide warnings for people [on] the island." "The current [alert system] collects data in real-time but what tends to happen is that this information gets assessed by a panel and they have an expert process... this all takes a while," he said.

The United Nations Educational, Scientific and Cultural Organisation (Unesco) has launched a global online consultation on the ethics of artificial intelligence (AI), which will be used by the organisation's international group of AI experts to help draft a framework governing how the technology is applied globally. The multidisciplinary unit of 24 AI specialists, known as the Ad Hoc Expert Group (AHEG), was formed in March 2020, and has been tasked with producing a draft Unesco recommendation that takes into account the wide-ranging impacts of AI, including on the environment, labour markets and culture. The first draft text of its recommendation was published on 15 May 2020, which Unesco is now inviting the public to comment on until 31 July 2020. It outlined 11 principles for the "research, design, development, deployment and use of AI systems", including fairness, responsibility and accountability, human oversight and determination, sustainability, mutli-stakeholder and adaptive governance, and privacy, among others. The text also outlined six values that would provide the foundation for these principles, which are human dignity, human rights and fundamental freedoms, leaving no one behind, living in harmony, trustworthiness, and protection of the environment. "It is crucial that as many people as possible take part in this consultation, so that voices from around the world can be heard during the drafting process for the first global normative instrument on the ethics of AI," said Audrey Azoulay, director-general of Unesco.

A cross-disciplinary team of machine learning, security, policy, and law experts say inconsistent court interpretations of an anti-hacking law have a chilling effect on adversarial machine learning security research and cybersecurity. At question is a portion of the Computer Fraud and Abuse Act (CFAA). A ruling to decide how part of the law is interpreted could shape the future of cybersecurity and adversarial machine learning. If the U.S. Supreme Court takes up an appeal case based on CFAA next year, researchers predict that the court will ultimately choose a narrow definition of the clause related to "exceed authorized access" instead of siding with circuit courts who have taken a broad definition of the law. One circuit court ruling on the subject concluded that a broad view would turn millions of people into unsuspecting criminals.

Yeshimabeit Milner was in high school the first time she saw kids she knew getting handcuffed and stuffed into police cars. It was February 29, 2008, and the principal of a nearby school in Miami, with a majority Haitian and African-American population, had put one of his students in a chokehold. The next day several dozen kids staged a peaceful demonstration. That night, Miami's NBC 6 News at Six kicked off with a segment called "Chaos on Campus." Cut to blurry phone footage of screaming teenagers: "The chaos you see is an all-out brawl inside the school's cafeteria." Students told reporters that police hit them with batons, threw them on the floor, and pushed them up against walls. The police claimed they were the ones getting attacked--"with water bottles, soda pops, milk, and so on"--and called for emergency backup. Around 25 students were arrested, and many were charged with multiple crimes, including resisting arrest with violence.

With great power, the saying goes, comes great responsibility. As artificial intelligence (AI) technology becomes more powerful, many groups are taking an interest in ensuring its responsible use. The questions that surround AI ethics can be difficult, and the operational aspects of addressing AI ethics are complex. Fortunately, these questions are already driving debate and action in the public and commercial sectors. Organizations using AI-based applications should take note.

Ancient Egyptians used hieroglyphs over four millennia ago to engrave and record their stories. Today, only a select group of people know how to read or interpret those inscriptions. To read and decipher the ancient hieroglyphic writing, researchers and scholars have been using the Rosetta Stone, an irregularly shaped black granite stone. In 2017, game developer Ubisoft launched an initiative to use AI and machine learning to understand the written language of the Pharoahs. The initiative brought researchers from Australia's Macquarie University and Google's Art and Culture division togther.

AI is proving its ability to find patterns hidden within troves of data, accelerate decisions and predictions based in fact, and save us time, energy, and money. Yet, even with recent advancements and investments, organizations with AI in production are still the exception rather than the rule. In a world hampered by the need for instant gratification, end users and stakeholders quickly become skeptics when an AI pilot fails or a high-profile AI implementation results in unintended consequences. The psychological implications caused by doubt and second guessing can quickly lead to discouragement and distrust of good solution ideas. If trust is the currency of business and life, how will a digital-first world and increased reliance on machine learning technologies affect your AI trust currency balance?

Citizen Science Salon is a partnership between Discover and SciStarter.org. In 2016, a team of Alzheimer's disease researchers at Cornell University hit a dead end. The scientists were studying mice, looking for links between Alzheimer's and blood flow changes in the brain. For years, scientists have known that reduced blood flow in the brain is a symptom of Alzheimer's disease. More recent research has also shown that this reduced blood flow can be caused by clogged blood vessels -- or "stalls." And by reversing these stalls in mice, scientists were able to restore their memory.

As the popularity of Amazon Alexa and other voice assistants grows, so too does the number of ways those assistants both do and can intrude on users' privacy. Examples include hacks that use lasers to surreptitiously unlock connected-doors and start cars, malicious assistant apps that eavesdrop and phish passwords, and discussions that are surreptitiously and routinely monitored by provider employees or are subpoenaed for use in criminal trials. Now, researchers have developed a device that may one day allow users to take back their privacy by warning when these devices are mistakenly or intentionally snooping on nearby people. This story originally appeared on Ars Technica, a trusted source for technology news, tech policy analysis, reviews, and more. Ars is owned by WIRED's parent company, Condé Nast.

The wait is over: artificial intelligence (AI) is here. And despite apocalyptic predictions about workers being replaced by intelligent machines, leading organizations are taking a new tack: actively searching for strategies to integrate AI into teams to produce transformative business results. These "superteams" hold the promise of enabling organizations to reinvent themselves to create new value and meaning, while giving workers the potential to reinvent their careers in ways that help increase their value to the organization and their own employability. For organizations that still view AI mainly as an automation tool to reduce costs, connecting their AI initiatives with their efforts to craft more effective teams is a first step toward enabling humans and machines to work together in new, more productive ways. The Readiness Gap: Fifty-nine percent of organizations say the redesign of jobs to integrate AI technology is important or very important for their success over the next 12 to 18 months, but only 7 percent say they are very ready to address this trend.