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Christine Gateau, Michelle Kisloff and Adam Cooke Posted in Cybersecurity, Data Protection & Privacy Going global: Data class actions make their way to the EU Class actions have become an increasingly common means to seek redress in data privacy cases. With data breaches and data privacy claims on the rise, we asked our lawyers in France and the U.S. what you should bear in mind. electricity distribution losses How real is the risk of class actions in data privacy?

Christine Gateau, France: Data privacy breaches usually affect lots of people. One person’s claim may be too small to launch an action on its own, generally. This makes class action — the opportunity to bring joint claims — a stronger option. Plus, French lawmakers are in favor of allowing consumers to seek redress for data loss and privacy breaches.

Adam Cooke, U.S.: The risk is real. gas under 2 dollars But in the U.S. plaintiffs have hurdles to overcome in prosecuting a class action. A threshold hurdle is that plaintiffs must show they have the ability, or “standing,” to bring a claim. One component of standing is injury, and plaintiffs must show they have suffered or will suffer losses, which must be real or imminent, not hypothetical. The mere possibility of future harm alone is not enough. Continue Reading Tags: data class actions, European Privacy, GDPR

On December 4, 2018, the New York Attorney General (NYAG) announced that Oath Inc., which was known until June 2017 as AOL Inc. (AOL), has agreed to pay a $4.95 million civil penalty to settle allegations that AOL’s ad exchange practices violated the Children’s Online Privacy Protection Act (COPPA). la gas prices map The $4.95 million penalty is the largest ever assessed by any regulator in a COPPA enforcement matter.

The NYAG alleged that AOL used its display ad exchange to help advertisers track and serve targeted display ads to children on hundreds of websites that the company knew were directed to children under the age of 13. Ad exchanges enable websites to sell, and advertisers to buy, advertising space through an auction process that takes place in real time after a user visits a webpage that contains ad space. To facilitate its online auctions, AOL allegedly collected, used, and disclosed to advertisers the personal information from child-directed websites’ users without first obtaining verifiable parental consent as required by COPPA. Continue Reading Tags: advertisement, Children’s Online Privacy Protection Act, compliance, COPPA, New York

At its Open Meeting on November 15, the FCC approved a draft Order that grants in part the European Commission’s (EC) long-pending request for waivers of certain FCC licensing requirements to permit non-Federal U.S. receive-only earth stations to operate with specific signals of the Galileo satellite system (Galileo) without having to obtain an FCC license or grant of US market access. Galileo was developed by the European Union and consists of a number of satellites operating in the radionavigation-satellite service (RNSS), similar to the U.S. gas constant for helium Global Positioning System (GPS). The U.S. gas works park address Department of Commerce’s National Telecommunications and Information Administration (NTIA) recommended grant of the requested waivers, and the FCC’s International Bureau issued a Public Notice seeking comment on the potential benefits and technical issues associated with the waiver request. The FCC granted the EC waiver request for operations with the Galileo E1 signal (1559-1591 MHz) and E5 signal (1164-1219 MHz), but denied the request for operations with the E6 signal (1260-1300 MHz). Continue Reading Tags: European Commission, FCC, Galileo, GPS, NTIA, RNSS

An ever increasing variety of companies are incorporating machine learning into their products and services. Machine learning provides the ability to quickly and accurately perform, in parellel, a large number of well-defined tasks. The accuracy will improveover time as additional data is obtaied and the machine learning model continues to “learn”. Many companies, however, are struggling with the best way to protect machine learning and artificial intelligence innovation.

In amchine learning, statistical models (ie, neural networks) are trained using a set of classified data. Once trained, the model can analyse unclassified data, such as images representing unidentified objects, and classify or generate observations for the data. A significant issue slowing widespread adopetion of machine learning is the inability to acess or determine the internal relationships or mechanisms y which machine learning generates these observations. igas energy shares Information about the initla configuration and training might be known, but trained models cannot “explain” in easily understandable terms how specific decisions were made. Continue Reading Tags: AI, artificial intelligence, bias, Data Protection, machine learning