Organizations are embracing digital transformation to enhance operations. Artificial intelligence (AI) in particular is revolutionizing the ways companies collaborate and conduct business. However, as these technologies spread across industries, these systems give rise to new attack points and vulnerabilities; especially for criminal activity. A study published in the journal Crime Science analyzed a vast spectrum of AI-enabled crimes in the years ahead ranging from military robots and autonomous attack drones to AI-assisted stalking. To assess the risks associated with these various potential criminal scenarios, the review featured a two-day workshop of individuals from the private and public sector, academics, police agencies, and more.

"Like all new technology, artificial intelligence…can also be misused and cause harm", warmed Tedros Adhanom Ghebreyesus, Director-General of the World health Organization (WHO). To regulate and govern AI, WHO published new guidance that provides six principles to limit the risks and maximize the opportunities intrinsic to AI for health. Artificial Intelligence (#AI) holds enormous potential for improving the health of millions of people around, but only if ethics & human rights are put at the heart of its design, deployment, & use. WHO's Ethics and governance of artificial intelligence for health report points out that AI can be and, in some wealthy countries is already being, used to improve the speed and accuracy of diagnosis and screening for diseases; assist with clinical care; strengthen health research and drug development; and support diverse public health interventions, including outbreak response and health systems management. AI could also empower patients to take greater control of their own health care and enable resource-poor countries to bridge health service access gaps.

"Like all new technology, artificial intelligence…can also be misused and cause harm", warmed Tedros Adhanom Ghebreyesus, Director-General of the World health Organization (WHO). To regulate and govern AI, WHO published new guidance that provides six principles to limit the risks and maximize the opportunities intrinsic to AI for health. Artificial Intelligence (#AI) holds enormous potential for improving the health of millions of people around, but only if ethics & human rights are put at the heart of its design, deployment, & use. WHO's Ethics and governance of artificial intelligence for health report points out that AI can be and, in some wealthy countries is already being, used to improve the speed and accuracy of diagnosis and screening for diseases; assist with clinical care; strengthen health research and drug development; and support diverse public health interventions, including outbreak response and health systems management. AI could also empower patients to take greater control of their own health care and enable resource-poor countries to bridge health service access gaps.

The year 2019 may have been a bit of a disappointment for enterprises in terms of their efforts to deploy artificial intelligence at scale. While executives in the C-suite remain committed to the idea of AI, and many organizations have created successful pilots of some form of AI technology, getting from pilot to scale has proven a greater challenge. How do you get from here to there? A new report from Lux Research offers a view into the state of AI in the enterprise today, perspective on its history, and some practical advice on a programmatic framework for how to think about AI in the enterprise and tackle implementation challenges. "Given the massive amounts of hype and promise surrounding AI and related technologies like machine learning and deep learning, it's become increasingly difficult to make critical innovation and investment decisions in the space," writes Lux analyst and lead report author Cole McCollum.

Bayesian quadrature optimization (BQO) maximizes the expectation of an expensive black-box integrand taken over a known probability distribution. In this work, we study BQO under distributional uncertainty in which the underlying probability distribution is unknown except for a limited set of its i.i.d. samples. A standard BQO approach maximizes the Monte Carlo estimate of the true expected objective given the fixed sample set. Though Monte Carlo estimate is unbiased, it has high variance given a small set of samples; thus can result in a spurious objective function. We adopt the distributionally robust optimization perspective to this problem by maximizing the expected objective under the most adversarial distribution. In particular, we propose a novel posterior sampling based algorithm, namely distributionally robust BQO (DRBQO) for this purpose. We demonstrate the empirical effectiveness of our proposed framework in synthetic and real-world problems, and characterize its theoretical convergence via Bayesian regret.

Ever wonder why Alexa is not Alex, which could actually be a nickname for either gender? It's actually ironic that a company with a name derived from a fierce warrior race of women just fell into the standard practice of casting the helper who takes orders from the user as female. In fact, the AI agent's name is derived from Alexandria, a city whose claim to fame in the ancient world was its library, according to Daniel Rausch, the head of Amazon's "Smart Home" division. He told Business Insider that it is to capture the idea of the original collection of volumes that housed "all the collective knowledge of the world at that time." But they could have just as easily considered the fact that the city was named for Alexander the Great, and gone with the name Alex, a nickname adopted by men and women.

This story was originally published by Grist. It appears here as part of the Climate Desk collaboration. Our gas-guzzling car culture is about to change forever, but not necessarily for good. The shift from gasoline-power to electric, the rise of ridesharing, and the invention of self-driving vehicles will soon overhaul transportation. A new report, just published by the Greenlining Institute, a racial equity nonprofit, says these three revolutions will speed us into a gridlocked and polluted future unless we put the right policies in place.

Artificial intelligence is changing the finance industry, with some early big movers monetizing their investments in back-office AI applications. But as this trend widens, new systemic and security risks may be introduced in the financial system. These are some of the findings of a new World Economic Forum report, The New Physics of Financial Services – How artificial intelligence is transforming the financial ecosystem, prepared in collaboration with Deloitte. "Big financial institutions are taking a page from the AI book of big tech: They develop AI applications and make them available as a'service' through the cloud," said Jesse McWaters, AI in Financial Services Project Lead at the World Economic Forum. "It is turning what were historically cost centres into new source of profitability, and creating a virtuous cycle of self-learning that accelerates their lead." The report, which draws on interviews and workshops with hundreds of financial and technology experts, observes that the "size of the prize" driven through these as-a-service offerings and other applications of AI is much larger than that of the more narrow applications that drive efficiency through the automation of human effort.

AI appears to be the way of the future, yet not all businesses are set to get on board. MIT Sloan Management Review partnered with The Boston Consulting Group to produce the report, Reshaping Business with Artificial Intelligence (PDF available for purchase). It sets out a realistic outlook for AI in businesses and looks at effective strategies employed by those that have adopted the technology. The report is based on a global survey of over 3,000 executives, managers and analysts. That informs their assessment of the huge difference between companies characterized as AI leaders and the ones that have yet to get on board.

The UK has a shot at leading the world in artificial intelligence and robotics governance, if not for Brexit. Britain's impending exit from the EU has cast doubts over crucial legal provisions for AI and robots, according to the results of an inquiry by the British parliament published today (Oct. To date, companies that stand to benefit from AI developments have so far been the ones leading the development of ethical guidelines around AI and robotics. Governments have been left behind, although the White House has also released its own, long awaited report on AI's impact today. The Science and Technology Committee of the House of Commons, the British parliament's lower chamber, published its report after six months of gathering evidence from academics, companies like Google DeepMind and Microsoft, and experts on AI and robotics in general.