Digital dystopia: how algorithms punish the poor

The Guardian

All around the world, from small-town Illinois in the US to Rochdale in England, from the Pacific shore of Perth, Australia, to Dumka in northern India, a revolution is under way in how governments treat the poor. You can't see it happening, and may have heard nothing about it. It's being planned by engineers and coders behind closed doors, in secure government locations far from public view. Only mathematicians and computer scientists fully understand the sea change, powered as it is by artificial intelligence (AI), predictive algorithms, risk modeling and biometrics. But if you are one of the millions of vulnerable people at the receiving end of the radical reshaping of welfare benefits, you know it is real and that its consequences can be serious – even deadly.


Benefits system automation could plunge claimants deeper into poverty

The Guardian

The UK government is accelerating the development of robots in the benefits system in a digitisation drive that vulnerable claimants fear could plunge them further into hunger and debt, the Guardian has learned. The Department for Work and Pensions has hired nearly 1,000 new IT staff in the past 18 months, and has increased spending to about £8m a year on a specialist "intelligent automation garage" where computer scientists are developing over 100 welfare robots, deep learning and intelligent automation for use in the welfare system. As well as contracts with the outsourcing multinationals IBM, Tata Consultancy and CapGemini, it is also working with UiPath, a New York-based firm co-founded by Daniel Dines, the world's first "bot billionaire" who last month said: "I want a robot for every person." His software, used by Walmart and Toyota, is now being deployed in a bid to introduce machine learning into checking benefit claims. The DWP is also testing artificial intelligence to judge the likelihood that citizens' claims about their childcare and housing costs are true when they apply for benefits.


Excavating AI

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There's an urban legend about the early days of machine vision, the subfield of artificial intelligence (AI) concerned with teaching machines to detect and interpret images. In 1966, Marvin Minsky was a young professor at MIT, making a name for himself in the emerging field of artificial intelligence.[1] Deciding that the ability to interpret images was a core feature of intelligence, Minsky turned to an undergraduate student, Gerald Sussman, and asked him to "spend the summer linking a camera to a computer and getting the computer to describe what it saw."[2] This became the Summer Vision Project.[3] Needless to say, the project of getting computers to "see" was much harder than anyone expected, and would take a lot longer than a single summer.


Adopting AI for Superior Reconciliations – A Team

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Firms' reconciliation and exceptions management processes are manually intensive, expensive and prone to error. With rising compliance costs and greater competition narrowing margins in financial services, firms are looking to streamline their reconciliations processes through automation, giving them the opportunity to reduce the number of exceptions they manage and the time it takes to deal with them. Financial institutions are adopting emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) in an attempt to automate processes and activities that previously required human intervention. Through automation of their reconciliations, firms are seeing an opportunity to reduce operational risk and boost their overall financial position, both in terms of reduced losses and regulatory capital. How can firms embrace AI to modernize their reconciliation processes for a better operational and financial outcome?


Google avoids serving repeat ads with machine learning

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Serving repeat ads can adversely affect everyone in the advertising pipeline, says Google. Advertisers typically pay on a "cost per click" basis, but "cost per mille" (where the advertiser pays for every 1,000 times an ad is displayed) isn't unheard of, so showing the same ad to the same user can be a waste of money. And if users see the same ad repeatedly, they're probably going to get annoyed. Google will roll out its machine learning solution in the next month or so. It will first come to the Display & Video 360 advertising platform, and will later be a feature for display ads in Google Ads (formerly called Google Adwords).


Continual Learning in Neural Networks

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Artificial neural networks have exceeded human-level performance in accomplishing several individual tasks (e.g. However, such success remains modest compared to human intelligence that can learn and perform an unlimited number of tasks. Humans' ability of learning and accumulating knowledge over their lifetime is an essential aspect of their intelligence. Continual machine learning aims at a higher level of machine intelligence through providing the artificial agents with the ability to learn online from a non-stationary and never-ending stream of data. A key component of such a never-ending learning process is to overcome the catastrophic forgetting of previously seen data, a problem that neural networks are well known to suffer from.


An Algorithm that identifies Bullies on Twitter with 90% accuracy. - Analytics Jobs

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New York: Machine learning algorithms have been developed by scientists which can predict bullying and aggressors on Twitter with 90% accuracy. The study analyzed the behavioral patterns showed by abusive Twitter users as well as the differences of theirs from various other Twitter users. "Tweets of twitter users have been gathered along with their profiles, and social network-related things like who they follow, who follows them," said Jeremy Blackburn, Binghamton University. The scientists created algorithms to automatically classify 2 specific kinds of offensive online behavior, i.e. cyberbullying and cyberaggression. The algorithms could determine abusive users on Twitter with accuracy up to 90%, scientists said.


No more exams for students in future classrooms: KHDA chief

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In the classrooms of the future, students will no longer have to sit down for exams. Instead, they will be busy working together to solve the problems of the world. This is how Dr Abdulla Al Karam, director-general of the Knowledge and Human Development Authority (KHDA), sees the future of learning in Dubai, as he explained during a session at Gitex Technology Week on Wednesday, October 9. "In the future, classrooms will be replaced by open, collaborative spaces that bring students of different ages and abilities together. This will encourage students to work together on solving real-world problems from a very young age, allowing schools to completely move away from tests and exams," said Dr Al Karam. He explained that there will also be more'teachers' powered by artificial intelligence (AI).


High powered tools using AI are transforming Indian Healthcare Industry. - Analytics Jobs

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In India whenever a person is detected facing medical conditions, most of them are likely to dodge the treatment process either due to the inability of fulfilling the demanded expenses or due to lack of time to complete the treatment. However, this practice is about to change with the help of artificial intelligence. The concept is becoming a fundamental component of the healthcare business globally. Multiple healthcare startups are started in the past several years and even some have come out with AI equipment to filter the condition through non-invasive methods with great accuracy in a couple of minutes. By combining medical sciences and computer engineering, self-dependent tools are developed which are capable of catching anomalies that even a human eye can miss.


Real Time face detection systems to be installed in public : Kerala Government. - Analytics Jobs

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Kerala government has requested Artificial Intelligence companies from developing a facial identification and a real-time mass surveillance system to be deployed across the state. Permanent cameras will be deployed at railway stations, bus stands, T-points, road junctions, and other public places if required mobile units can be deployed at a special place to record the venue such as a protest or any trouble spots. These surveillance cameras will be connected to powerful computers, and any person whose data has been entered into the system will be detected in minutes if the person steps in front of any camera installed across the state. The government of Kerala constituted "a strategic think-tank and advisory body" in the name of Kerala Development & Innovation Strategic Council (K-DISC). At present this approach is implemented in China where every citizen should have a file opened in his/her name in a mass surveillance called "social credit system".