dChan - Q Origins Project Archive

https://www.businessinsider.com.au/china-facial-recognition-technology-works-in-one-second-2018-3

Across China, facial-recognition technology that can scan the country’s entire population is being put to use. In some cases, the technology can perform the task in just one second.

Sixteen cities, municipalities, and provinces are using a frighteningly fast surveillance system that has an accuracy rate of 99.8%, Global Times reported over the weekend.

“The system is fast enough to scan China’s population in just one second, and it takes two seconds to scan the world’s population,” the Times reported, citing local Chinese newspaper Worker’s Daily.

The system is part of Skynet, a nationwide monitoring program launched in 2005 to increase the use and capabilities of surveillance cameras.

According to developers, this particular system works regardless of angle or lighting condition and over the last two years has led to the arrest of more than 2,000 people.

The use of facial-recognition technology is soaring in China where it is being used to increase efficiencies and improve policing. Cameras are used to catch jaywalkers, find fugitives, track people’s regular hangouts, and even predict crime before it happens.

Currently, there are 170 million surveillance cameras in China and, by 2020, the country hopes to have 570 million – that’s nearly one camera for every two citizens.

Facial recognition technology is just a small part of the artificial intelligence industry that China wants to pioneer.

According to a report by CB Insights, five times as many AI patents were applied for in China than the US in 2017.

And, for the first time, China’s AI scene gained more investment than that of the US last year. Of every available dollar going to AI startups around the world, nearly half went to companies in China.

Big data meets Big Brother as China moves to rate its citizens

The Chinese government plans to launch its Social Credit System in 2020. The aim? To judge the trustworthiness – or otherwise – of its 1.3 billion residents

On June 14, 2014, the State Council of China published an ominous-sounding document called "Planning Outline for the Construction of a Social Credit System". In the way of Chinese policy documents, it was a lengthy and rather dry affair, but it contained a radical idea. What if there was a national trust score that rated the kind of citizen you were?

Imagine a world where many of your daily activities were constantly monitored and evaluated: what you buy at the shops and online; where you are at any given time; who your friends are and how you interact with them; how many hours you spend watching content or playing video games; and what bills and taxes you pay (or not). It's not hard to picture, because most of that already happens, thanks to all those data-collecting behemoths like Google, Facebook and Instagram or health-tracking apps such as Fitbit. But now imagine a system where all these behaviours are rated as either positive or negative and distilled into a single number, according to rules set by the government. That would create your Citizen Score and it would tell everyone whether or not you were trustworthy. Plus, your rating would be publicly ranked against that of the entire population and used to determine your eligibility for a mortgage or a job, where your children can go to school - or even just your chances of getting a date.

A futuristic vision of Big Brother out of control? No, it's already getting underway in China, where the government is developing the Social Credit System (SCS) to rate the trustworthiness of its 1.3 billion citizens. The Chinese government is pitching the system as a desirable way to measure and enhance "trust" nationwide and to build a culture of "sincerity". As the policy states, "It will forge a public opinion environment where keeping trust is glorious. It will strengthen sincerity in government affairs, commercial sincerity, social sincerity and the construction of judicial credibility."

MORE:

https://www.wired.co.uk/article/chinese-government-social-credit-score-privacy-invasion

The merging of humans and machines is happening now

Her organisation invented the internet. It gave us the self-driving car. And now DARPA’s former boss sees us crossing a new technological boundary

The merging of machine capability and human consciousness is already happening. Writing exclusively for WIRED, DARPA director Arati Prabhkar outlines the potential rewards we face in the future - and the risks we face

Peter Sorger and Ben Gyori are brainstorming with a computer in a laboratory at Harvard Medical School. Their goal is to figure out why a powerful melanoma drug stops helping patients after a few months. But if their approach to human-computer collaboration is successful, it could generate a new approach to fundamentally understanding complexities that may change not only how cancer patients are treated, but also how innovation and discovery are pursued in countless other domains.

At the heart of their challenge is the crazily complicated hairball of activity going on inside a cancer cell - or in any cell. Untold thousands of interacting biochemical processes, constantly morphing, depending on which genes are most active and what's going on around them. Sorger and Gyori know from studies of cells taken from treated patients that the melanoma drug's loss of efficacy over time correlates with increased activity of two genes. But with so many factors directly or indirectly affecting those genes, and only a relatively crude model of those global interactions available, it's impossible to determine which actors in the cell they might want to target with additional drugs.

That's where the team's novel computer system comes in. All Sorger and Gyori have to do is type in a new idea they have about the interactions among three proteins, based on a mix of clinical evidence, their deep scientific expertise, and good old human intuition. The system instantly considers the team's thinking and generates hundreds of new differential equations, enriching and improving its previous analytical model of the myriad activities inside drug-treated cells. And then it spits out new results.

These don't predict all the relevant observations from tumour cells, but it gives the researchers another idea involving two more proteins - which they shoot back on their keyboard. The computer churns and responds with a new round of analysis, producing a model that, it turns out, predicts exactly what happens in patients and offers new clues about how to prevent some cases of melanoma recurrence.

In a sense, Sorger and Gyori do what scientists have done for centuries with one another: engage in ideation and a series of what-ifs. But in this case, their intellectual partner is a machine that builds, stores, computes and iterates on all those hundreds of equations and connections.