Fuzzy cognitive maps (FCMs) model feedback causal relations in interwoven webs of causality and policy variables. FCMs are fuzzy signed directed graphs that allow degrees of causal influence and event occurrence. Such causal models can simulate a wide range of policy scenarios and decision processes. Their directed loops or cycles directly model causal feedback. Their nonlinear dynamics permit forward-chaining inference from input causes and policy options to output effects. Users can add detailed dynamics and feedback links directly to the causal model or infer them with statistical learning laws. Users can fuse or combine FCMs from multiple experts by weighting and adding the underlying fuzzy edge matrices and do so recursively if needed. The combined FCM tends to better represent domain knowledge as the expert sample size increases if the expert sample approximates a random sample. Many causal models use more restrictive directed acyclic graphs (DAGs) and Bayesian probabilities. DAGs do not model causal feedback because they do not contain closed loops. Combining DAGs also tends to produce cycles and thus tends not to produce a new DAG. Combining DAGs tends to produce a FCM. FCM causal influence is also transitive whereas probabilistic causal influence is not transitive in general. Overall: FCMs trade the numerical precision of probabilistic DAGs for pattern prediction, faster and scalable computation, ease of combination, and richer feedback representation. We show how FCMs can apply to problems of public support for insurgency and terrorism and to US-China conflict relations in Graham Allison's Thucydides-trap framework. The appendix gives the textual justification of the Thucydides-trap FCM. It also extends our earlier theorem [Osoba-Kosko2017] to a more general result that shows the transitive and total causal influence that upstream concept nodes exert on downstream nodes.

Importance weighting is a general way to adjust Monte Carlo integration to account for draws from the wrong distribution, but the resulting estimate can be noisy when the importance ratios have a heavy right tail. This routinely occurs when there are aspects of the target distribution that are not well captured by the approximating distribution, in which case more stable estimates can be obtained by modifying extreme importance ratios. We present a new method for stabilizing importance weights using a generalized Pareto distribution fit to the upper tail of the distribution of the simulated importance ratios. The method, which empirically performs better than existing methods for stabilizing importance sampling estimates, includes stabilized effective sample size estimates, Monte Carlo error estimates and convergence diagnostics.

A novel approach is provided for evaluating the benefits and burdens from vehicle modularity in fleets/units through the analysis of a game theoretical model of the competition between autonomous vehicle fleets in an attacker-defender game. We present an approach to obtain the heuristic operational strategies through fitting a decision tree on high-fidelity simulation results of an intelligent agent-based model. A multi-stage game theoretical model is also created for decision making considering military resources and impacts of past decisions. Nash equilibria of the operational strategy are revealed, and their characteristics are explored. The benefits of fleet modularity are also analyzed by comparing the results of the decision making process under diverse operational situations.

An independent expert group tasked with advising the European Commission to inform its regulatory response to artificial intelligence -- to underpin EU lawmakers' stated aim of ensuring AI developments are "human centric" -- has published its policy and investment recommendations. This follows earlier ethics guidelines for "trustworthy AI", put out by the High Level Expert Group (HLEG) for AI back in April, when the Commission also called for participants to test the draft rules. The AI HLEG's full policy recommendations comprise a highly detailed 50-page document -- which can be downloaded from this web page. The group, which was set up in June 2018, is made up of a mix of industry AI experts, civic society representatives, political advisers and policy wonks, academics and legal experts. The document includes warnings on the use of AI for mass surveillance and scoring of EU citizens, such as China's social credit system, with the group calling for an outright ban on "AI-enabled mass scale scoring of individuals".

An organization that won the Nobel Prize in 2017 for its work to eliminate nuclear weapons is sounding the alarm about the possibility of artificial intelligence leading to unintended wars. Beatrice Fihn, executive director of the International Campaign to Abolish Nuclear Weapons, is worried that hackers could breach A.I. technologies that are used in nuclear programs or that they could use A.I. to dupe countries into launching attacks. For example, deepfakes, or realistic-looking computer-altered videos, may be used to "create a perceived threat that might not be there," she warns, prompting governments to overreact. Fihn told Fortune that she wants to convene a meeting in the fall with nuclear weapons experts and some of the leading companies in A.I. and cybersecurity. Participants in the off-the-record event, she said, would produce a document that her group would use to inform governments and others about the danger.

The Allen Institute for Artificial Intelligence has an interesting new tactic in the war on fake news: make more of it. A team of researchers at the institute recently developed Grover, a neural network capable of generating fake news articles in the style of actual human journalists. In essence, the group is fighting fire with fire because the better Grover gets at generating fakes, the better it'll be at detecting them. Our study presents a surprising result: the best way to detect neural fake news is to use a model that is also a generator. The generator is most familiar with its own habits, quirks, and traits, as well as those from similar AI models, especially those trained on similar data, i.e. publicly available news.

Military doctrine identifies five domains of warfare--land, sea, air, space and information. While borders and barriers define the four natural domains, the fifth dimension, with the advancements of artificial intelligence, is rapidly expanding with the potential to destabilize free and open international order. Nations like China and Russia are making significant investments in AI for military purposes, potentially threatening world norms and human rights. This year the Defense Department, in support of the National Defense Strategy, launched its Artificial Intelligence Strategy in concert with the White House executive order creating the American Artificial Intelligence Strategy. The DoD AI strategy states the U.S., together with its allies and partners, must adopt AI to maintain its strategic position, prevail on future battlefields and safeguard order.

Technology providers are investing huge sums to infuse AI into their products and services. The industry press touts the gains companies stand to make by infusing AI in IT infrastructure -- from bolstering cybersecurity and streamlining compliance to automating data capture and optimizing storage capacity. AI, we are told, will make every corner of the enterprise smarter, and businesses that fail to understand AI's transformational power will be left behind. The reality, as with most emerging tech, is less straightforward. "Despite AI's potential to transform products and business processes, executives must not get caught up in the hype," cautioned Ashok Pai, vice president and global head of cognitive business operations at Tata Consultancy Services. "Starting out with AI means developing a sharp focus." Before IT and business leaders fund AI projects, they need to carefully consider where AI might have the greatest impact in their organizations. They must align AI investment to strategic business priorities such as growing sales, increasing productivity and getting products to market faster.

The saying "a picture is worth a thousand words" does something of an injustice to the medium of language. It suggests that words are an inefficient form of communication when in fact the opposite is true. When humans use language to communicate, so much is left out because the speaker and listener share experience of the same world, which makes explicit statements about that shared world unnecessary in everyday speech. For example, if I say to you "the vase is on its side, rolling along the table," I don't need to also tell you that the vase is made of fragile stuff (it's a reasonable assumption that it is), or that the table doesn't have edges that will stop the vase's rolling, or that as a result the vase will likely roll off the table, or that gravity will make the vase to fall to the floor, which is hard and will therefore cause the fragile vase to shatter. It's enough for me to say "the vase is on its side, rolling along the table" for you to know the vase will likely smash to pieces unless someone intervenes.

Products/Services Visa agreed to acquire the token and electronic ticketing business of Rambus for $75 million in cash. The business involved is part of the Smart Card Software subsidiary of Rambus. It includes the former Bell ID mobile-payment businesses and the Ecebs smart-ticketing systems for transit providers. Meanwhile, Rambus expanded its CryptoManager Root of Trust product line. "Security is a mission-critical imperative for SoC designs serving virtually every application space," Neeraj Paliwal, vice president of products, cryptography at Rambus, said in a statement.