The European Commission has announced the launch of a pilot project intended to test draft ethical rules for developing and applying artificial intelligence technologies to ensure they can be implemented in practice. It's also aiming to garner feedback and encourage international consensus building for what it dubs "human-centric AI" -- targeting among other talking shops the forthcoming G7 and G20 meetings for increasing discussion on the topic. The Commission's High Level Group on AI -- a body comprised of 52 experts from across industry, academia and civic society announced last summer -- published their draft ethics guidelines for trustworthy AI in December. A revised version of the document was submitted to the Commission in March. It's boiled the expert consultancy down to a set of seven "key requirements" for trustworthy AI, i.e. in addition to machine learning technologies needing to respect existing laws and regulations -- namely: The next stage of the Commission's strategy to foster ethical AI is to see how the draft guidelines operate in a large-scale pilot with a wide range of stakeholders, including international organizations and companies from outside the bloc itself.

BRUSSELS (Reuters) - Companies working with artificial intelligence need to install accountability mechanisms to prevent it being misused, the European Commission said on Monday, under new ethical guidelines for a technology open to abuse by authoritarian regimes.

In its most basic form, decision-making can be viewed as a computational process that progressively eliminates alternatives, thereby reducing uncertainty. Such processes are generally costly, meaning that the amount of uncertainty that can be reduced is limited by the amount of available computational resources. Here, we introduce the notion of elementary computation based on a fundamental principle for probability transfers that reduce uncertainty. Elementary computations can be considered as the inverse of Pigou-Dalton transfers applied to probability distributions, closely related to the concepts of majorization, T-transforms, and generalized entropies that induce a preorder on the space of probability distributions. As a consequence we can define resource cost functions that are order-preserving and therefore monotonic with respect to the uncertainty reduction. This leads to a comprehensive notion of decision-making processes with limited resources. Along the way, we prove several new results on majorization theory, as well as on entropy and divergence measures.

With conventional anti-jamming solutions like frequency hopping or spread spectrum, legitimate transceivers often tend to "escape" or "hide" themselves from jammers. These reactive anti-jamming approaches are constrained by the lack of timely knowledge of jamming attacks. Bringing together the latest advances in neural network architectures and ambient backscattering communications, this work allows wireless nodes to effectively "face" the jammer by first learning its jamming strategy, then adapting the rate or transmitting information right on the jamming signal. Specifically, to deal with unknown jamming attacks, existing work often relies on reinforcement learning algorithms, e.g., Q-learning. However, the Q-learning algorithm is notorious for its slow convergence to the optimal policy, especially when the system state and action spaces are large. This makes the Q-learning algorithm pragmatically inapplicable. To overcome this problem, we design a novel deep reinforcement learning algorithm using the recent dueling neural network architecture. Our proposed algorithm allows the transmitter to effectively learn about the jammer and attain the optimal countermeasures thousand times faster than that of the conventional Q-learning algorithm. Through extensive simulation results, we show that our design (using ambient backscattering and the deep dueling neural network architecture) can improve the average throughput by up to 426% and reduce the packet loss by 24%. By augmenting the ambient backscattering capability on devices and using our algorithm, it is interesting to observe that the (successful) transmission rate increases with the jamming power. Our proposed solution can find its applications in both civil (e.g., ultra-reliable and low-latency communications or URLLC) and military scenarios (to combat both inadvertent and deliberate jamming).

This work tackles the problem of learning a set of language specific acoustic units from unlabeled speech recordings given a set of labeled recordings from other languages. Our approach may be described by the following two steps procedure: first the model learns the notion of acoustic units from the labelled data and then the model uses its knowledge to find new acoustic units on the target language. We implement this process with the Bayesian Subspace Hidden Markov Model (SHMM), a model akin to the Subspace Gaussian Mixture Model (SGMM) where each low dimensional embedding represents an acoustic unit rather than just a HMM's state. The subspace is trained on 3 languages from the GlobalPhone corpus (German, Polish and Spanish) and the AUs are discovered on the TIMIT corpus. Results, measured in equivalent Phone Error Rate, show that this approach significantly outperforms previous HMM based acoustic units discovery systems and compares favorably with the Variational Auto Encoder-HMM.

DINARD, FRANCE - Foreign ministers of Group of Seven nations on Saturday pushed North Korea to continue denuclearization negotiations with the United States while vowing to maintain pressure on Pyongyang to encourage it to give up its nuclear weapons and ballistic missile programs. In a communique issued after a two-day meeting in Dinard, western France, the ministers also expressed serious concern about the situation in the East and South China seas -- a veiled criticism of China's militarization of outposts in disputed areas of the South China Sea and its attempts to undermine Japan's control of the Senkaku Islands in the East China Sea. The Senkakus are administered by Japan, but claimed by China and Taiwa, which call them the Diaoyu and Tiaoyutai, respectively. During the meeting, some G7 members touched on China's expanding global ambitions through its signature Belt and Road Initiative infrastructure project, a Japanese official said. But the communique makes no reference to the initiative in an apparent effort to demonstrate unity among the group.

After little more than a week, Google backtracked on creating its Advanced Technology External Advisory Council, or ATEAC--a committee meant to give the company guidance on how to ethically develop new technologies such as AI. The inclusion of the Heritage Foundation's president, Kay Coles James, on the council caused an outcry over her anti-environmentalist, anti-LGBTQ, and anti-immigrant views, and led nearly 2,500 Google employees to sign a petition for her removal. Instead, the internet giant simply decided to shut down the whole thing. How did things go so wrong? And can Google put them right?

Step aside, Mr Aldrin, because there's a new buzz in town - and it's coming from robot bees that NASA is sending to work on the International Space Station. Dubbed'Astrobees', the cube-shaped robots will fly about the orbiting laboratory, running experiments and helping out the crew by using their attachable manipulator arms. The design of the little bots was inspired by the flying combat remote from Star Wars, which teaches the film's hero Luke Skywalker to fight with a lightsaber. Dubbed'Astrobees', the cube-shaped robots will fly about the orbiting laboratory, running experiments and helping out the crew by using their attachable manipulator arms The design of the little bots was inspired by the flying combat remote from Star Wars, which teaches the film's hero Luke Skywalker to fight with a lightsaber (pictured) The robots were built and developed at NASA's Ames Research Center in California, where engineers created a mock-up of the interior of the International Space Station where they tested the Astrobees' capabilities. 'There are some things only humans can do in space.

Algorithms are biased--and Facebook's is no exception. Just last week, the tech giant was sued by the US Department of Housing and Urban Development over the way it let advertisers purposely target their ads by race, gender, and religion--all protected classes under US law. The company announced that it would stop allowing this. But new evidence shows that Facebook's algorithm, which automatically decides who is shown an ad, carries out the same discrimination anyway, serving up ads to over two billion users on the basis of their demographic information. A team led by Muhammad Ali and Piotr Sapiezynski at Northeastern University ran a series of otherwise identical ads with slight variations in available budget, headline, text, or image.

In the 1970s, faced with the USSR's overwhelming superiority in numbers, the Department of Defense decided to compensate by focusing on high technology platforms. This led to the highly successful F-15, F-16, F-18, Abrams tanks, and Bradley fighting vehicles. Since then, the United States has continued to pursue cutting edge technology that has resulted in the highly capable F-22 and, when the testing and software development is complete, perhaps a highly capable F-35. Unfortunately, cost has accelerated faster than capabilities. And thus numbers have declined precipitously. The U.S. Air Force initially planned to buy 750 F-22s, but the high cost led Secretary of Defense Robert Gates to cap the program at 187. Nor has the Air Force been alone in pursuing top end systems. The Navy attempted an entirely new concept with "Streetfighter." Meant to be a low-cost, highly capable ship to replace the Navy's frigates and minesweepers for operations in brown water, it evolved into the Littoral Combat Ship.