After combing through hundreds of impressive, insightful and creative entries, we've decided on the winners of the World Data Visualization Prize 2019. Conducted in partnership with the World Government Summit, the prize focuses on how governments are improving citizens' lives. We asked entrants to use the power of data-visualization to illuminate data on the innovations and decisions – seen and unseen – that drive progress. Scroll through the interactive, static and hand-drawn "napkin" category winners to see who took the grand prize of $25,000. GOV DNA This beautiful interactive graphic shows the "DNA" of good government.

In science fiction and real life alike, there are plenty of horror stories where humans trust artificial intelligence too much. They range from letting the fictional SkyNet control our nuclear weapons to letting Patriots shoot down friendly planes or letting Tesla Autopilot crash into a truck. As conflict on earth, in space, and in cyberspace becomes increasingly fast-paced and complex, the Pentagon's Third Offset initiative is counting on artificial intelligence to help commanders, combatants, and analysts chart a course through chaos -- what we've dubbed the War Algorithm (click here for the full series). But if the software itself is too complex, too opaque, or too unpredictable for its users to understand, they'll just turn it off and do things manually. At least, they'll try: What worked for Luke Skywalker against the first Death Star probably won't work in real life.

The government on Tuesday approved a bill to revise the drone regulation law to prohibit the flying of drones over U.S. military bases and Self-Defense Forces' facilities as part of its measures to prevent terrorist attacks using drones. The government plans to submit the bill to the current Diet session, but news organizations are protesting the move on the grounds it could potentially disrupt newsgathering. Under the bill, the government would also ban drones from flying over venues for this year's Rugby World Cup and the 2020 Tokyo Olympics and Paralympics. During those sporting events, only drones controlled by the media providing coverage would be allowed to fly over the venues. Under the existing law, Japan already prohibits drone flights over key facilities such as the Prime Minister's Office and the Imperial Palace in Tokyo.

Everyone uses the term artificial intelligence (AI) generically, and they mix it up with ML, AR, VR, and MR. The definitions have changed over time, and everyone seems to inherently assume that they know what they're talking about when they say AI. From my perspective, it's essentially the ability of machines to perform those targeted functions that you normally associate with a human mind. These are things that humans do naturally, like reasoning, learning, and interacting with the environment. Anything that falls in that realm right now is AI. If you asked me that 20 years ago, AI would just be anything that is human-like that has to do with software.

Over the past few months, a fierce debate has erupted in Silicon Valley over whether large technology companies like Amazon, Google and Microsoft should join forces with the United States military, along with agencies like Immigration and Customs Enforcement. The debate has largely been conducted along ethical lines. On one side are tech executives and many government officials, who argue that at a time when advanced technologies like artificial intelligence and machine learning are poised to reshape top issues like drone warfare or border security, American tech giants have a patriotic duty to pitch in. Jeff Bezos, Amazon's chief executive, summed up this view last year: "If big tech companies are going to turn their back on the U.S. Department of Defense, this country is going to be in trouble." On the other side are groups of employees at those companies, including many anti-Trump progressives, who don't want their tools to be used for drone warfare, immigrant detention and other projects they consider immoral.

Can hype-scarred cybersecurity pros dare to be hopeful about artificial intelligence as a means to ease the acute information security labor shortage? The answer is a highly qualified "yes," say several industry players usually skeptical of trendy cyber solutions but who are on the lookout for any tech that promises greater efficiency for labor-intensive grunt work. "A lot of the cybersecurity tasks today are mundane and manual," says Chenxi Wang, founder and general partner at Rain Capital. "From that lens, AI can help eliminate those tasks. Human time can be better spent on the more sophisticated tasks such as threat hunting, versus things like fixing configurations or processing low-level data."

An autonomous rover named Zoë, designed and built by Carnegie Mellon University's Robotics Institute, drilled into the soil of Chile's Atacama Desert in 2013 and discovered unusual, highly specialized microbes. The NASA-funded mission demonstrated how robots might someday find life on Mars. The astrobiology mission was led by the Robotics Institute and the SETI Institute to test technologies for searching for life underground. The microbial analyses of the soil samples recovered by Zoë were published Feb. 28 in the journal Frontiers of Microbiology. Zoë was equipped with a one-meter drill that recovered samples several times each day.

High-tech chips implanted in the brain could soon give humans an intelligence boost. Researchers have been working to develop minimally invasive methods to hack the human brain and squeeze out more of its potential. Recent technological advancements could make this possible within the next five years, Northwestern University neuroscientist Dr. Moran Cerf told CBS – but, he warns the move could also create new forms of social inequality. High-tech chips implanted in the brain could soon give humans an intelligence boost. Researchers have been working to develop minimally invasive methods to hack the human brain and squeeze out more of its potential.

We present PROPS, a lightweight transfer learning mechanism for sequential data. PROPS learns probabilistic perturbations around the predictions of one or more arbitrarily complex, pre-trained black box models (such as recurrent neural networks). The technique pins the black-box prediction functions to "source nodes" of a hidden Markov model (HMM), and uses the remaining nodes as "perturbation nodes" for learning customized perturbations around those predictions. In this paper, we describe the PROPS model, provide an algorithm for online learning of its parameters, and demonstrate the consistency of this estimation. We also explore the utility of PROPS in the context of personalized language modeling. In particular, we construct a baseline language model by training a LSTM on the entire Wikipedia corpus of 2.5 million articles (around 6.6 billion words), and then use PROPS to provide lightweight customization into a personalized language model of President Donald J. Trump's tweeting. We achieved good customization after only 2,000 additional words, and find that the PROPS model, being fully probabilistic, provides insight into when President Trump's speech departs from generic patterns in the Wikipedia corpus. Python code (for both the PROPS training algorithm as well as experiment reproducibility) is available at https://github.com/cylance/perturbed-sequence-model.

The instrumentation of real systems is often designed for control purposes and control inputs are designed to achieve nominal control objectives. Hence, the available measurements may not be sufficient to isolate faults with certainty and diagnoses are ambiguous. Active diagnosis formulates a planning problem to generate a sequence of actions that, applied to the system, enforce diagnosability and allow to iteratively refine ambiguous diagnoses. This paper analyses the requirements for applying active diagnosis to space systems and proposes ActHyDiag as an effective framework to solve this problem. It presents the results of applying ActHyDiag to a real space case study and of implementing the generated plans in the form of On-Board Control Procedures. The case study is a redundant Spacewire Network where up to 6 instruments, monitored and controlled by the on-board software hosted in the Satellite Management Unit, are transferring science data to a mass memory unit through Spacewire routers. Experiments have been conducted on a real physical benchmark developed by Thales Alenia Space and demonstrate the effectiveness of the plans proposed by ActHyDiag.