Inside the Algorithm That Tries to Predict Gun Violence in Chicago - The New York Times
statisticians reverse engineering the "strategic subject list" algorithm used in Chicago. CPD has declined to release details citing proprietary technology. Journalists filed FOIA suits to get full information.
algorithms  ee  chicago  guns  violence  police  predictive_policing 
12 days ago
ConceptNet Numberbatch 17.04: better, less-stereotyped word vectors
"I had tried building an algorithm for sentiment analysis based on word embeddings — evaluating how much people like certain things based on what they say about them. When I applied it to restaurant reviews, I found it was ranking Mexican restaurants lower. The reason was not reflected in the star ratings or actual text of the reviews. It’s not that people don’t like Mexican food. The reason was that the system had learned the word “Mexican” from reading the Web.

If a restaurant were described as doing something “illegal”, that would be a pretty negative statement about the restaurant, right? But the Web contains lots of text where people use the word “Mexican” disproportionately along with the word “illegal”, particularly to associate “Mexican immigrants” with “illegal immigrants”. The system ends up learning that “Mexican” means something similar to “illegal”, and so it must mean something bad."
algorithms  bias  nlp  km 
13 days ago
Corporate Surveillance in Everyday Life
Report by Susan's grantee: 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?
surveillance  km 
17 days ago
DHS Public Database Includes Personal Information of Abuse Victims
The Trump administration’s effort to highlight crimes committed by undocumented immigrants has become a nightmare for immigrant victims of abuse, with the personal information of undocumented victims appearing in a publicly searchable database launched last month by the Department of Homeland Security.
trump  database  km  privacy 
19 days ago
How to Call B.S. on Big Data: A Practical Guide - The New Yorker
At the University of Washington, students are learning to navigate the hazards of our information-addled age.
big_data 
23 days ago
How Twitter Is Being Gamed to Feed Misinformation
“Bots allow groups to speak much more loudly than they would be able to on any other social media platforms — it lets them use Twitter as a megaphone,” said Samuel Woolley, the director for research at Oxford University’s Computational Propaganda Project. “It’s doing something that I call ‘manufacturing consensus,’ or building the illusion of popularity for a candidate or a particular idea.”
twitter  misinformation  botnets  km  nytimes 
24 days ago
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning | Mental Floss
At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data.
ai  machine_learning  ee 
24 days ago
Uber Starts Charging What It Thinks You’re Willing to Pay
On Friday, Uber acknowledged to drivers the discrepancy between their compensation and what riders pay. The new fare system is called “route-based pricing,” and it charges customers based on what it predicts they’re willing to pay. It’s a break from the past, when Uber calculated fares using a combination of mileage, time and multipliers based on geographic demand. Daniel Graf, Uber’s head of product, said the company applies machine-learning techniques to estimate how much groups of customers are willing to shell out for a ride. Uber calculates riders’ propensity for paying a higher price for a particular route at a certain time of day. For instance, someone traveling from a wealthy neighborhood to another tony spot might be asked to pay more than another person heading to a poorer part of town, even if demand, traffic and distance are the same.
uber  price_discrimination  km 
4 weeks ago
Twitter user numbers overtaken by China's Sina Weibo - BBC News
There are now more people using Sina Weibo, the Chinese micro-blogging platform, than there are using Twitter. According to the Chinese company's first quarter results, it has 340 million active monthly users, 30% up on the previous year. About 154 million people use the site daily, 91% of whom access it via mobile. By comparison, Twitter, which is blocked in China, has around 328 million active monthly users.
5 weeks ago
A Taxpayer-Supported Version of Facebook - The Atlantic
So, haven’t we just replaced one tech-centric explanation with another? Not quite. If the combination of online news, social media, and echo chambers led to political polarization and ideological capture, we’d expect to see the same phenomenon on the left as on the right. We don’t. In our study, people who read far-left sources like Daily Kos or Mother Jones are generally also engaged with center and center-left sources like the New York Times, The Washington Post, and CNN. The new right’s echo chamber is hermetically sealed, while the left’s is not. (Of course, if you’re within that hermetically sealed chamber, you’re likely to see CNN as just as left-leaning at The Nation.)
facebook  fakenews  elections  hjd 
5 weeks ago
“Google Is as Close to a Natural Monopoly as the Bell System Was in 1956"
Media scholar Jonathan Taplin, author of the new book Move Fast and Break Things, on the rent-seeking and regulatory capture of digital platforms.
antitrust  Google  Facebook 
6 weeks ago
Regulating the internet giants: The world’s most valuable resource is no longer oil, but data | The Economist
Regulating the internet giants: The world’s most valuable resource is no longer oil, but data

The data economy demands a new approach to antitrust rules
data 
6 weeks ago
NAACP | Open Educational Resources: Equity & Opportunities
Civil rights org NAACP adopts OER resolution in fight for education access and equity
oer 
7 weeks ago
Jeff Wise - When machines go rogue | The Outline
What’s happening inside our algorithms? What happens when those algorithms control our cars and planes? Pretty soon, we may have no idea.
algorithms  automation 
12 weeks ago
Artificial intelligence runs wild while humans dither
A study published last month in the research journal Plos One, analysing the use of bots on Wikipedia over a decade, found that even those designed for wholly benign purposes could spend years duelling with each other.

In one such battle, Xqbot and Darknessbot disputed 3,629 entries, undoing and correcting the other’s edits on subjects ranging from Alexander the Great to Aston Villa football club.

The authors, from the Oxford Internet Institute and the Alan Turing Institute, were surprised by the findings, concluding that we need to pay far more attention to these bot-on-bot interactions. “We know very little about the life and evolution of our digital minions.”
AI  algorithms  public_sphere 
march 2017
How the UK government can hack your personal data
In short, it forces internet companies to keep bulk records of all the websites you visit for up to a year and allows the UK government to coerce tech companies to hand over your web history with a retention notice and remove encryption, upon request.
uk  surveillance  hjd 
february 2017
The Data That Turned the World Upside Down - Motherboard
a then little-known British company based in London sent out a press release: "We are thrilled that our revolutionary approach to data-driven communication has played such an integral part in President-elect Trump's extraordinary win," Alexander James Ashburner Nix was quoted as saying. Nix is British, 41 years old, and CEO of Cambridge Analytica. He is always immaculately turned out in tailor-made suits and designer glasses, with his wavy blonde hair combed back from his forehead. His company wasn't just integral to Trump's online campaign, but to the UK's Brexit campaign as well.
fakenews  trump  brexit  hjd  CambridgeAnalytica 
february 2017
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