Privacy

  • UK police arrest man via automatic face-recognition tech (via RISKS 30.32).

    Back in April, it emerged that South Wales Police planned to scan the faces "of people at strategic locations in and around the city centre" ahead of the UEFA Champions League final, which was played at the Millennium Stadium in Cardiff on June 3.

    On May 31, though, a man was arrested via AFR. "It was a local man and unconnected to the Champions League," a South Wales Police spokesperson told Ars. It's not clear whether this was due to the technology being tested ahead of the match.

    [...] the man's face was probably included in the force's "Niche Record Management system," which contains "500,000 custody images."

  • Cracked Labs report: Corporate Surveillance in Everyday Life.

    How thousands of companies monitor, analyze, and influence the lives of billions. Who are the main players in today's digital tracking? What can they infer from our purchases, phone calls, web searches, and Facebook likes? How do online platforms, tech companies, and data brokers collect, trade, and make use of personal data?

  • How a crippling shortage of analysts let the London Bridge attackers through. There are two things here: at the same time, governments don't have enough analysts to extract valuable information from the data they collect, and at the same time they're pushing for more data collection, with the net result that it will be noise the one increasing.

    So why did they all slip through the net? Some security experts warn of an analytical deficit in the heart of the government's intelligence infrastructure, claiming a lack of human resources to decode and contextualise the myriad snippets of information, terabytes of chatter, tipoffs, sightings and wiretaps that cumulatively help to form the modern intelligence picture.

Tech

  • What is your favorite data analysis cartoon?.

  • Artificial intelligence can now predict suicide with remarkable accuracy.

    Walsh and his colleagues have created machine-learning algorithms that predict, with unnerving accuracy, the likelihood that a patient will attempt suicide. In trials, results have been 80-90% accurate when predicting whether someone will attempt suicide within the next two years, and 92% accurate in predicting whether someone will attempt suicide within the next week.

    The prediction is based on data that's widely available from all hospital admissions, including age, gender, zip codes, medications, and prior diagnoses. Walsh and his team gathered data on 5,167 patients from Vanderbilt University Medical Center that had been admitted with signs of self-harm or suicidal ideation. They read each of these cases to identify the 3,250 instances of suicide attempts.

Visualizations


Data Links is a periodic blog post published on Sundays (specific time may vary) which contains interesting links about data science, machine learning and related topics. You can subscribe to it using the general blog RSS feed or this one, which only contains these articles, if you are not interested in other things I might publish.

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