You may perhaps have become aware of the General Data Protection Regulation (GDPR). The office of the Irish Data Protection Commissioner, via business briefings and media advertising, is increasingly highlighting this new European Union regulation, which comes into effect on May 25th. The GDPR preamble asserts: "The protection of natural persons in relation to the processing of personal data is a fundamental right." The key theme is that each of us owns our own data. Any company must therefore explicitly request permission to use any of our personal data, explaining why it would like to do so, and for how long.

I love it when I get feedback from a blog that I've written. I appreciate the different perspectives and insights that others bring to a topic of interest. And no blog that I've written has drawn more comments than my blog, "Isaac Asimov: The 4th Law of Robotics." The section of the blog that fueled the most comments stem from a scene in the movie I, Robot where Detective Spooner (played by Will Smith) is explaining to Doctor Calvin (who is responsible for giving robots human-like behaviors) why he distrusts and hates robots. He is describing an incident where his police car crashed into another car and both cars were thrown into a cold and deep river – certain death for all occupants.

The scam works like this: There you are, using your computer just like any other day, when suddenly a pop-up appears, warning you that your computer has been infected by a virus and you need to call tech support immediately. If you try to get rid of the pop-up, it just keeps coming back. If you do call the alleged tech support number, you're connected to telemarketers who claim to be affiliated with major technology companies – but are really scammers trying to bilk customers for costly and unnecessary computer repairs or services. When the Federal Trade Commission announced a major crackdown on these scammers last month, it was relying in part on the work of a group of Microsoft researchers and Digital Crimes Unit investigators who used artificial intelligence to help unravel the complex web of technical tricks the scammers were using to swindle users and avoid law enforcement. The scammers weren't easy to track down.

MPs from the House of Commons inquiry into fake news were warned last week of a new AI technology that is about to change the world, and not for the better. "We're rapidly moving into an era where the Russians, or any other adversary, can create our public figures saying or doing things that are disgraceful or highly corrosive to public trust," Edward Lucas, the senior vice president of the Centre for European Policy Analysis told MPs. "And we're not remotely ready for this." Lucas was talking about so-called deepfakes, which he described as "audio and video that look and sound like the real person, saying something that that person never has". Less than three months ago, producing such videos was a laborious process requiring a video editor, vast amounts of reference footage and years of experience. But in the first few months of this year, the technology has exploded into public availability.

IoT (Internet of Things), the convergence of IT and OT, rapid application development, digital twin simulation models, cyber-physical systems, advanced robots and cobots, additive manufacturing, autonomous production, consistent engineering across the entire value chain, thorough data collection and provisioning, horizontal and vertical integration, the cloud, big data analytics, virtual/augmented reality and edge computing amidst a shift of intelligence towards the edge (artificial intelligence indeed): these are some of the essential technological components of the fourth industrial revolution. Those are quite a lot of terms and components indeed. Yet, Industry 4.0 is a rather vast vision and, increasingly, vast reality that also stretches beyond merely these technological aspects. It is an end-to-end industrial transformation. What makes it all the more fascinating (and at first sight complex) is that convergence of two worlds which have been disconnected thus far: Information ...

Minutes later, and the easy listening instrumental track being piped through the theater died down. A whoop from somewhere in the venue sparked some excited chatter. A journalist sitting in front of me asked her neighbor "Is that him at the side there?" Someone started chanting "Elon, Elon, Elon," and it briefly caught on before dissolving into an insecure giggle as the next jam faded in. By the time SXSW director Hugh Forrest took the stage around half an hour behind schedule, excitement was at fever pitch.

Drones are a perfect example of how our technology has evolved and will continue to grow in the future. So, what exactly does it offer? For casual users, it is just a fun toy. However, drones have use cases in multiple fields, including safety, health, and industry. Until now, drones have gone on a wild ride.

Long lines and lengthy waits for round after round of security checks are di rigueur at major events in China such as the annual meetings of its legislature. That may change in the near future with the use of facial recognition to red-flag people for further screening while allowing others to proceed, speeding up the process of letting thousands of delegates, journalists and staff into the Great Hall of the People, according to Baidu CEO Robin Li Yanhong, whose company is testing such a system at airports. "The measures to verify identification, such as the tight security checks during the Two Sessions, have brought inconvenience to people's lives," said Li, who is a delegate to the Chinese People's Political Consultative Conference. "Most of the time, people's identification is done manually, which I think will be completely unnecessary in the future," he told mainland Chinese media ahead of the event. Li's comments highlight the growing use of facial recognition in security applications in China, part of the nation's wider push to lead the world in artificial intelligence and a desire by the central government to improve public safety through surveillance of citizens.

Non-uniform random samples are commonly generated in multiple scientific fields ranging from economics to medicine. Complex sampling designs afford research with increased precision for estimating parameters of interest in less prevalent sub-populations. With a growing interest in using complex samples to generate prediction models for numerous outcomes it is necessary to account for the sampling design that gave rise to the data in order to assess the generalized predictive utility of a proposed prediction rule. Specifically, after learning a prediction rule based on a complex sample, it is of interest to estimate the rule's error rate when applied to unobserved members of the population. Efron proposed a general class of covariance-inflated prediction error estimators that assumed the available training data is representative of the target population for which the prediction rule is to be applied. We extend Efron's estimator to the complex sample context by incorporating Horvitz-Thompson sampling weights and show that it is consistent for the true generalization error rate when applied to the underlying superpopulation giving rise to the training sample. The resulting Horvitz-Thompson-Efron (HTE) estimator is equivalent to dAIC---a recent extension of AIC to survey sampling data---and is more widely applicable. The proposed methodology is assessed via empirical simulations and is applied to data predicting renal function that was obtained from the National Health and Nutrition Examination Survey (NHANES).

Google has partnered with the United States Department of Defence to help the agency develop artificial intelligence for analysing drone footage, a move that set off a firestorm among employees of the technology giant when they learned of Google's involvement. Google's pilot project with the Defence Department's Project Maven, an effort to identify objects in drone footage, has not been previously reported, but it was discussed widely within the company last week when information about the project was shared on an internal mailing list, according to sources who asked not to be named because they were not authorised to speak publicly about the project. Some Google employees were outraged that the company would offer resources to the military for surveillance technology involved in drone operations, sources said, while others argued that the project raised important ethical questions about the development and use of machine learning. Google's Eric Schmidt summed up the tech industry's concerns about collaborating with the Pentagon at a talk last spring. "There's a general concern in the tech community of somehow the military-industrial complex using their stuff to kill people incorrectly," he said.