Argumentation theory is a powerful paradigm that formalizes a type of commonsense reasoning that aims to simulate the human ability to resolve a specific problem in an intelligent manner. A classical argumentation process takes into account only the properties related to the intrinsic logical soundness of an argument in order to determine its acceptability status. However, these properties are not always the only ones that matter to establish the argument's acceptability---there exist other qualities, such as strength, weight, social votes, trust degree, relevance level, and certainty degree, among others.

We study model-agnostic copies of machine learning classifiers. We develop the theory behind the problem of copying, highlighting its differences with that of learning, and propose a framework to copy the functionality of any classifier using no prior knowledge of its parameters or training data distribution. We identify the different sources of loss and provide guidelines on how best to generate synthetic sets for the copying process. We further introduce a set of metrics to evaluate copies in practice. We validate our framework through extensive experiments using data from a series of well-known problems. We demonstrate the value of copies in use cases where desiderata such as interpretability, fairness or productivization constrains need to be addressed. Results show that copies can be exploited to enhance existing solutions and improve them adding new features and characteristics.

I'm excited to be at the Smart City Expo World Congress in Barcelona this week with my full leadership team from Western Europe. The purpose of the event is to bring people together to share information about how to empower cities and collectivize urban innovation across the globe, and it's been amazing to interact with many of the 33 partners from 15 countries who have joined us in our booth. By promoting social innovation, establishing partnerships, and identifying business opportunities, Smart City Expo can help create a better future for cities and their citizens worldwide. And I have to say…what a difference a year makes! I attended this event last year and it's remarkable to see how much progress has been made, particularly around the Internet of Things (IoT).

What is the single most important step the tech community can take to instill trust in artificial intelligence? In 2013, when I was the D.O.D.'s No. 2 official, I issued a policy directive on autonomous weapons that is still in force. The U.S. takes its values to the battlefield, and the directive says that a human must be involved in and responsible for decisions aided by A.I. to employ lethal weapons. The same moral compass should govern commercial applications of A.I., such as credit ratings, prison sentencing and privacy. After a lifetime in technology development, I believe that transparency for the sake of accountability must be a technical design requirement for A.I. algorithms.

Ren Zhengfei, the reclusive founder and CEO of China's embattled tech giant, Huawei, is defiant about American efforts to impede his company with lawsuits and restrictions. "There is no way the US can crush us," Ren said in a rare recent interview with international media. "The world cannot leave us because we are more advanced." It might sound like bluff and bluster, but these words carry a measure of truth. Huawei's technology road map, especially in the field of artificial intelligence, points to a company that is progressing more rapidly--and on more technology fronts--than any other business in the world.

It will be much harder than we have realised to blow up an asteroid and save the planet, scientists have warned. Experts have repeatedly warned that it is a question of when not if the Earth will be hit by the arrival of a potentially disastrous asteroid. But films have suggested a simple if high-tech response: launching heroes into space to blow it up before it ever gets here. In real life, however, those asteroids could be far more difficult to destroy than we knew. That is according to a new study from scientists at Johns Hopkins, who simulated the ways that an asteroid collision might happen and how such a space rock would fracture.

The Defense Advanced Research Projects Agency is pursuing an unprecedented machine-learning'breakthrough' technology -- and pioneering a new cybersecurity method intended to thwart multiple attacks at one time. The Defense Advanced Research Projects Agency is pursuing an unprecedented machine-learning "breakthrough" technology -- and pioneering a new cybersecurity method intended to thwart multiple attacks at one time and stop newer attacks less recognizable to existing defenses. A DARPA-led "Lifelong Learning Machines" (L2M) program, intended to massively improve real-time AI and machine learning, rests upon the fundamental premise that certain machine-learning-capable systems might struggle to identify, integrate and organize some kinds of new or complicated yet-to-be-seen information. "If something new is different enough, the system may fail. This is why I wanted to have some kind of machine learning that learns during experiences. Systems do not know what to do in some situations," Hava Siegelmann, DARPA program manager at the Information Innovation Office and Professor of Computer Science at the University of Massachusetts.

Health providers and artificial-intelligence software companies are developing tools that could help pathologists better spot diseases, prioritize critical cases and improve patient outcomes, according to a new research report from Frost & Sullivan. The Food and Drug Administration has yet to approve machine-learning pathology tools for use in patient care, but many pathologists say the day isn't far off. The FDA could put its stamp of approval on the technology in the next few years, said Dr. Liron Pantanowitz, vice...

Despite Canada's rising reputation as a global leader in the artificial intelligence community, it appears Canadian companies are not making as much of an impact on the international AI scene. CB Insights has released its third annual list of promising AI startups to watch around the world, and only one Canadian company, Montreal-based Element AI, made the cut. In addition to Element AI, a German startup with Canadian roots, Twenty Billion Neurons (TwentyBN) was also named to CB Insights' AI 100. Canadian companies leveraging this technology may still only have a minor presence on the global stage. CB Insights selected the 100 startups from a pool of over 3,000 companies from startups to unicorns, based on: patent activity, investor profile, news sentiment analysis, proprietary Mosaic scores, market potential, partnerships, competitive landscape, team strength, and tech novelty.

Artificial intelligence-based forgery reached a watershed moment. Recent developments in artificial intelligence (AI) point to an age where forgery of documents, pictures, audio recordings, videos, and online identities will occur with unprecedented ease. AI is poised to make high-fidelity forgery inexpensive and automated, leading to potentially disastrous consequences for democracy, security, and society. As an AI researcher, I'm here to sound the alarm, and to suggest a partial solution. In February, AI-based forgery reached a watershed moment–the OpenAI research company announced GPT-2, an AI generator of text so seemingly authentic that they deemed it too dangerous to release publicly for fears of misuse.