Research on artificial intelligence has highlighted the importance of quality data: a machine learning device is “only as smart as the data it’s allowed to cull through,” after all. So, how do you mitigate the risks posed to AI development by bad data? Forbes offers a couple of strategies. First,

“Another day, another data breach?” Breach fatigue is setting in as the next new breach hits headlines on an overwhelmingly regular basis. Rather than “tuning out” or ignoring the breaches, however, they must become alarm bells that drive companies, individuals, and governments around the world to implement proactive security practices

Amazon sent 1,700 voice recordings captured by their Alexa in-home device to a random person. An individual in Germany requested copies of all of his data on Amazon’s files as part of the EU General Data Protection Regulation. As part of their compliance, however, Amazon included 1,700 voice recordings from

“A misconfigured server exposed the taxpayer identification numbers, or Cadastro de Pessoas Físicas (CPFs), for 120 million Brazilian nationals for an unknown period of time Before a Brazilian national can perform many tasks such as opening a bank account, creating a business, paying taxes, or getting a loan, they must first apply for a Cadastro

News of new data breaches splash across the headlines on a seemingly weekly, if not daily, basis. Marriott’s loss of personal information from around 500 million guests is the most recent and one of the most largest. But how does it stack up against others by sheer numbers? This Nextgov

Google has secured patents for technology that would allow devices to scan its surroundings and then create ads based off what it detects. For example, a shirt on the floor with a print of Will Smith’s head could be read by a device with the technology and then used to

Critics of the forthcoming Federal Data Strategy have faulted it for being unwieldy and overly difficult for end users to understand. According to one policy analyst, “the current draft has 47 practices organized around five objectives, 10 principles and six lifecycle steps. The result is an unwieldy three-dimensional framework that

With all the talk about Artificial Intelligence, little has been said about developments or quality protocols in data management. And with a technology that is only as good as the data that enables it, this is a problem. “If we don’t make the right investments on the data side, it’s