Links for 2020-04-28

  • Coronavirus and Brexit: the connections and their consequences

    Have to agree with this…

    What both Brexit and coronavirus reveal are some fundamental flaws in the way [the UK] are governed and the political discourse around it. The populist explosion of this decade, of which Brexit was a prime example, has bequeathed a way of governing which is impervious to reason, and incapable of engaging with complexity. It isn’t just chance that we have a woefully incompetent Prime Minister, a dud stand in, and a cabinet of mediocrities, propped up by a cadre of special advisors with few skills beyond contrarian posturing. They are the legacy of Brexit. They were brought into power by Brexit. But all the things which secured the vote for Brexit – the clever-but-dumb messaging, the leadership-by-slogan, the appeal to nostalgic sentiment, the disdain for facts and evidence, the valorisation of anger and divisiveness, the bluff ‘commonsense’ and the ‘bluffers’ book’ knowledge – are without exception precisely the opposite of what is needed for effective governance in general, and crisis management in particular.

    (tags: uk-politics uk politics brexit covid-19 government populism crisis-management)

  • Google’s medical AI was super accurate in a lab. Real life was a different story. | MIT Technology Review

    When it worked well, the AI did speed things up. But it sometimes failed to give a result at all. Like most image recognition systems, the deep-learning model had been trained on high-quality scans; to ensure accuracy, it was designed to reject images that fell below a certain threshold of quality. With nurses scanning dozens of patients an hour and often taking the photos in poor lighting conditions, more than a fifth of the images were rejected. Patients whose images were kicked out of the system were told they would have to visit a specialist at another clinic on another day. If they found it hard to take time off work or did not have a car, this was obviously inconvenient. Nurses felt frustrated, especially when they believed the rejected scans showed no signs of disease and the follow-up appointments were unnecessary. They sometimes wasted time trying to retake or edit an image that the AI had rejected. Because the system had to upload images to the cloud for processing, poor internet connections in several clinics also caused delays. “Patients like the instant results, but the internet is slow and patients then complain,” said one nurse. “They’ve been waiting here since 6 a.m., and for the first two hours we could only screen 10 patients.” The Google Health team is now working with local medical staff to design new workflows. For example, nurses could be trained to use their own judgment in borderline cases. The model itself could also be tweaked to handle imperfect images better. 

    (tags: google health medicine ai automation software internet developing-world real-world images scanning)

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