From remediating blight to optimizing restaurant inspections and pest control, cities across the country are using analytics to help improve municipal policy and performance. The continued adoption of analytics in city governments shows no sign of slowing, and as even more sophisticated tools such as machine learning and artificial intelligence are deployed, there is a critical need for research on how these practices are reshaping urban policy. By examining and capturing lessons learned from city-level analytics projects, practitioners and theorists alike can better understand how data- and tech-enabled innovations are affecting municipal governance. This report seeks to contribute to that developing field. Members of the Civic Analytics Network, a peer group of leading urban chief data officers convened by the Harvard Ash Center, are using data-smart policymaking practices to develop, iterate, and replicate municipal analytics projects. The Civic Analytics Network was established as a community of practice in 2016 to support the growth and replication of analytics capacities in cities across the United States. Civic Analytics Network members represent many early leaders in urban analytics, and their cities' analytics projects, policies, and approaches are at the forefront of this space. To help other cities learn how to use analytics to better serve their communities, this report profiles a selection of Civic Analytics Network city initiatives in areas ranging from municipal public safety and public health to housing and transportation. A key component in creating, launching, and implementing an analytics project is adopting a systemic approach to project development. Whether a city has an established chief data officer position, an analytics team, or is a newcomer to public-sector data analytics altogether, there are various approaches and processes that can help initiate, scope, and implement a successful analytics project. While many urban analytics projects have been largely successful in fulfilling their initial objectives and supporting better governance, most underwent multiple iterations.

Last September, the world welcomed Juggalos (or Juggalettes, depending on which you prefer) to The Resistance when they marched on Washington en masse to protest the policies of the Trump administration. As if they weren't already doing the absolute most, the die-hard fans of the rap group Insane Clown Posse have become accidental heroes for people concerned about facial recognition tech: According to Twitter user @tahkion, a computer science blogger for WonderHowTo, Juggalo makeup outmatches the machine learning algorithms that govern facial recognition technology. In a series of follow-up tweets, @tahkion explained that facial recognition works by pinpointing the areas of contrast on a human face--for instance, where a nose is located, or where the chin becomes the neck. As it happens, juggalo makeup often involves applying black paint below the mouth, but above the chin. That makes facial recognition vulnerable to misidentifying the placement of the jaw.

In a future where AI and automation are likely to lead to millions of displaced workers, it's essential that we don't leave coding to the robots, according to former Googler Megan Smith. As companies look to AI to cut costs and automate the most manual and time-consuming tasks, it's widely accepted that millions of jobs will be lost to the machines. Gartner believes that while AI will create 2.3 million jobs by 2020, it will make 1.8 million workers redundant as companies find the improved efficiency and cost-savings too tempting to ignore. And the Bank of England identified 15 million UK jobs at risk from automation over the next two decades, with chessmaster Garry Kasparov - who famously lost a match to an AI in 1997 - calling the job losses the cost of progress. Some believe such an impact on the economy should lead to governments giving people a universal basic income, which others have suggested amounts to putting people on welfare.

Over the past few weeks, news about various state governments here in the US using facial recognition technology has caused concerns. Not only is it an invasion of privacy but also something that people feel will result in more racially biased profiling. Imagine what it enables government bodies to do when citizens are tracked, in real-time, following their private choices, actions, and behaviors. Some in the New York Police Department want access to the Department of Motor Vehicles database of driver's license photos as it expands facial recognition technology to such matters as identifying missing persons. But privacy advocates are crying foul.

Dubai – The Saudi Ministry of Haj and Umrah has published on its Youtube channel a video giving an insight on how Haj as we know it today will change in 2030. Saudi vision 2030 doesn't only tackle economic and public sector development but also Haj and Umrah services will be improved. Artificial intelligence and technology as announced by Minister of Haj and Umrah, Mohammad Saleh bin Taher Benten, will give pilgrims to Makkah a high quality experience. According to the video, Muslims from around the world who intend to undertake Haj would have to apply through a mobile application, and within a few days, they will receive a box that contains an electronic card, a bracelet, and an earphone. The pilgrims should keep these three items with themselves at all times during the Haj.

A professor of ethics and technology has told scientists and policymakers that digital technology like artificial intelligence'desperately' need to be regulated using an institutional framework and system of values. "People are becoming aware that this digital age is not neutral," he said. "It is presented to us mainly by big corporations who want to make some profit." Van den Hoven, a member of the European Group on Ethics in Science and New Technologies (EGE), said: "We need to think about governance, inspection, monitoring, testing, certification, classification, standardisation, education, all of these things. We need to desperately, and very quickly, help ourselves to it."

What do machine learning practitioners actually do? Written: 12 Jul 2018 by Rachel Thomas This post is part 1 of a series. Part 2 will explain AutoML and neural architecture search, and Part 3 will look at Google's AutoML in particular. There are frequent media headlines about both the scarcity of machine learning talent (see here, here, and here) and about the promises of companies claiming their products automate machine learning and eliminate the need for ML expertise altogether (see here, here, and here). In his keynote at the TensorFlow DevSummit, Google's head of AI Jeff Dean estimated that there are tens of millions of organizations that have electronic data that could be used for machine learning but lack the necessary expertise and skills.

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The biggest coming danger is so-called "deepfakes," or AI-doctored videos falsely showing people saying or doing something, according to a co-author of the report, published today by the Center for a New American Security and shared first with Axios The details: The report is an abridged encyclopedia of the good and ill that AI could bring to national security. Some scenarios show the potential upside of AI tools, but others would result in chaos if not challenged by smart AI countermeasures. The impact: If this wave is left unchecked, the report warns, the world could face "the end of truth" -- a grisly fate the public has already had a taste of, thanks to misinformation released on social media sites and by the White House. The report's examples vary from the current to the far-off, like mind-reading AI. But they're not prophecies that humanity is doomed to suffer.

A terror network established in south Wales is now suspected to have been a much more elaborate and sophisticated operation. BBC Wales Investigates reveals the complex web which began with the arrival in Pontypridd of a "vulnerable looking" computer engineering student. In late December 2015 a uniformed Pentagon spokesman, Colonel Steve Warren, made a video announcement about "Operation Inherent Resolve", the US military's campaign against so-called the Islamic State group in Iraq and Syria. The spokesman gave details about 10 senior IS figures who had been targeted and killed, many in drone strikes, over the course of the month. "We are striking at the head of this snake by hunting down and killing ISIS leaders," declared the US army spokesman. Among those killed was Siful Sujan, a Bangladeshi national who was targeted near Raqqa in Syria on 10 December.