In 1970, Lyudmila Terentyevna Aleksandrova lost her right hand. It happened at work, where she was employed by the Russian state. With her hand gone, she fought for a disability allowance that never materialized, batted about by district and regional courts. Eventually, after decades of frustration, she brought the case to the European Court of Human Rights, which ruled in 2007 that there had been a violation in Aleksandrova's right to a fair trial. Pay the money, it told Russia.

Artificial intelligence is advancing rapidly. It is powering autonomous vehicles and being applied in areas from health care and finance to retail sales and national defense. As noted in a 2018 Brookings Institution report, "AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking." Yet most of the current AI impetus in the United States comes from the private sector.

Having now worked in the mobile apps industry for several years, I'm troubled that the most popular technology trends at CES will harm the developmental health of our children. Even worse, I feel that technology companies, government, and society are likely to make the same mistakes made with mobile screen time -- though at a much greater cost. With an urgency similar to what has moved nations to ward off the worst of global warming, we too must act now to prepare our children and better understand and regulate organizations developing artificial intelligence (AI), virtual reality (VR), and 5G (5th generation mobile connectivity). This is why I'm asking the United States federal government to appoint a task force consisting of consumer advocates and technology experts to recommend policy to the relevant Congressional committees and the Federal Trade Commission. Even though the emerging technologies at CES are rolling out very quickly, there were plenty of headlines in 2018 suggesting that the crises with mobile screen time is far from fully understand, let alone resolved.

In this paper, we present a novel approach for the task of eXplainable Question Answering (XQA), i.e., generating natural language (NL) explanations for the Visual Question Answering (VQA) problem. We generate NL explanations comprising of the evidence to support the answer to a question asked to an image using two sources of information: (a) annotations of entities in an image (e.g., object labels, region descriptions, relation phrases) generated from the scene graph of the image, and (b) the attention map generated by a VQA model when answering the question. We show how combining the visual attention map with the NL representation of relevant scene graph entities, carefully selected using a language model, can give reasonable textual explanations without the need of any additional collected data (explanation captions, etc). We run our algorithms on the Visual Genome (VG) dataset and conduct internal user-studies to demonstrate the efficacy of our approach over a strong baseline. We have also released a live web demo showcasing our VQA and textual explanation generation using scene graphs and visual attention.

3D object classification and segmentation using deep neural networks has been extremely successful. As the problem of identifying 3D objects has many safety-critical applications, the neural networks have to be robust against adversarial changes to the input data set. There is a growing body of research on generating human-imperceptible adversarial attacks and defenses against them in the 2D image classification domain. However, 3D objects have various differences with 2D images, and this specific domain has not been rigorously studied so far. We present a preliminary evaluation of adversarial attacks on deep 3D point cloud classifiers, namely PointNet and PointNet++, by evaluating both white-box and black-box adversarial attacks that were proposed for 2D images and extending those attacks to reduce the perceptibility of the perturbations in 3D space. We also show the high effectiveness of simple defenses against those attacks by proposing new defenses that exploit the unique structure of 3D point clouds. Finally, we attempt to explain the effectiveness of the defenses through the intrinsic structures of both the point clouds and the neural network architectures. Overall, we find that networks that process 3D point cloud data are weak to adversarial attacks, but they are also more easily defensible compared to 2D image classifiers. Our investigation will provide the groundwork for future studies on improving the robustness of deep neural networks that handle 3D data.

Many companies expect in the near future to derive substantial benefits from adopting artificial intelligence-powered technologies. However, they must first overcome some significant obstacles. In a global survey of 300 C-level executives and their direct reports by consulting firm Protiviti, 16% of the respondents say their companies are getting "high" or "very high" value from their investments in AI. But more than three times that many (52%) say they anticipate they will be doing so in two years. Protiviti identified five major barriers to AI adoption. First, although improved cybersecurity is a major advantage of AI, it also brings its own cybersecurity risks due to the greater access to sensitive and personal data.

Killer robots are a'grave threat to humanity' and should be banned, the world's largest gathering of scientists was told. As yet, robot soldiers and security guards armed with lethal weapons are largely science fiction concepts. But advances in artificial intelligence mean it is only a matter of time before robots with the power to select and attack targets without human input become widespread. Killer robots, similar to the Terminator played by Arnold Schwarzenegger (pictured), are a'grave threat to humanity' and should be banned, the world's largest gathering of scientists was told (stock image) Scientists and human rights campaigners told the American Association for the Advancement of Science annual meeting in Washington DC lethal droids able to select targets without human help represent the'third revolution' in warfare after gun powder and nuclear weapons. Just as international agreements greatly restricted the use of landmines, similar international agreements should be used to prevent robotic killers becoming established.

There is widespread public support for a ban on so-called "killer robots", which campaigners say would "cross a moral line" after which it would be difficult to return. Polling across 26 countries found over 60 per cent of the thousands asked opposed lethal autonomous weapons that can kill with no human input, and only around a fifth backed them. The figures showed public support was growing for a treaty to regulate these controversial new technologies - a treaty which is already being pushed by campaigners, scientists and many world leaders. However, a meeting in Geneva at the close of last year ended in a stalemate after nations including the US and Russia indicated they would not support the creation of such a global agreement. Mary Wareham of Human Rights Watch, who coordinates the Campaign to Stop Killer Robots, compared the movement to successful efforts to eradicate landmines from battlefields.

Russia has declared war on the United States after Donald Trump accidentally fired a missile in the air. Russia said it had "identified the missile's trajectory and will take necessary measures to ensure the security of the Russian population and the country's strategic nuclear forces." The White House said it was "extremely concerned by the Russian violation" of a treaty banning intermediate-range ballistic missiles. The US and Russia have had an uneasy relationship since 2014, when Moscow annexed Ukraine's Crimea region and backed separatists in eastern Ukraine. That story is, in fact, not only fake, but a troubling example of just how good AI is getting at fooling us.