Friday, June 21, 2019

AI Has Made Video Surveillance Automated and Terrifying

In a word, the world itself is a maze, a labyrinth of errors, a desert, a wilderness, a den of thieves, cheaters, &c., full of filthy puddles, horrid rocks, precipitiums, an ocean of adversity, an heavy yoke, wherein infirmities and calamities overtake, and follow one another, as the sea waves; and if we scape Scylla, we fall foul on Charybdis, and so in perpetual fear, labour, anguish, we run from one plague, one mischief, one burden to another . . .”
~ on twitter

Keneally can sometimes seem the nearest that we have to a Balzac of our literature; he is in his own rich and idiosyncratic ways the author of an Australian ‘human comedy’.

There must be a better way to share out federal cash to the states


Dobbers hit dodgers: Tax office gets record 60,000 tip offs - Sydney Morning Herald


Sydney barrister Charles Waterstreet suspended from practice

MARK SWIVEL. ‘To be without a home. Like a complete unknown. Just like a rolling stone’. – Bob Dylan.


Having a home one of the most basic human needs. We talk about housing or shelter as a human right – as we should. But that is not what we want. Not just the bricks and mortar but the sense of place and belonging. It’s why homeless people gather. Sure there’s safety in numbers when sleeping rough but we need each other and want to be together with others. Continue reading 



“It used to be that surveillance cameras were passive. Maybe they just recorded, and no one looked at the video unless they needed to. Maybe a bored guard watched a dozen different screens, scanning for something interesting. In either case, the video was only stored for a few days because storage was expensive. Increasingly,none of that is true. Recent developments in video analytics—fueled by artificial intelligence techniques like machine learning—enable computers to watch and understand surveillance videos with human-like discernment. Identification technologies make it easier to automatically figure out who is in the videos. And finally, the cameras themselves have become cheaper, more ubiquitous, and much better; cameras mounted on drones can effectively watch an entire city. Computers can watch all the video without human issues like distraction, fatigue, training, or needing to be paid. The result is a level of surveillance that was impossible just a few years ago…”
NiemanLab: “Should journalists learn to code?” is an old question that has always had only unsatisfying answers. (That was true even back before it became a useful heuristic for identifying Twitter jackasses.) Some should! Some shouldn’t! Helpful, right? One way the question gets derailed involves what, exactly, the question-asker means by “code.” It’s unlikely a city hall reporter will ever have occasion to build an iPhone app in Swift, or construct a machine learning model on deadline. But there is definitely a more basic and straightforward set of technical skills — around data analysis — that can be of use to nearly anyone in a newsroom. It ain’t coding, but it’s also not a skillset every reporter has. The New York Times wants more of its journalists to have those basic data skills, and now it’s releasing the curriculum they’ve built in-house out into the world, where it can be of use to reporters, newsrooms, and lots of other people too…”


At-risk youth exchanging sex for ice and ending up in 'captive-like' situations, inquiry told