News: Internet researchers harnessed the power of algorithm to find hate speech – Aalto University

The aim was to identify hate speech targeted at minorities and people in a vulnerable position.

 

During the municipal elections in spring 2017, a group of researchers and practitioners specialising in computer science, media and communication implemented a hate speech identification campaign with the help of an algorithm based on machine learning.

At the beginning of the campaign, the algorithm was taught to identify hate speech as diversely as possible, for example, based on the big data obtained from open chat groups. The algorithm learned to compare computationally what distinguishes a text that includes hate speech from a text that is not hate speech and to develop a categorisation system for hate speech. The algorithm was then used daily to screen all openly available content the candidates standing in the municipal elections had produced on Facebook and Twitter. The candidates’ account information were gathered using the material in the election machine of the Finnish Broadcasting Company Yle.

Source: News: Internet researchers harnessed the power of algorithm to find hate speech – Aalto University

Digital services collect unnecessary personal information | Karlstad University

When one creates an account to get access to an online service, the service provider requires certain details to identify users who want to access their accounts. There are existing methods that can be built into such services to protect users and their privacy under certain circumstances. However, many service providers choose to use other methods to collect as much information about us as possible, and so frequently threaten online user privacy.

Source: Digital services collect unnecessary personal information | Karlstad University

No Incentive? Algorand Blockchain Sparks Debate at Cryptography Event – CoinDesk

Should incentives in blockchain systems be a last resort? The developer of the Algorand proof-of-stake system thinks so, but other experts disagree.

“Can you say anything about incentives in Algorand?”

That question was directed to Silvio Micali, an MIT professor who had just delivered a keynote on his theoretical proof-of-stake (PoS) system at the Financial Cryptography and Data Security conference in Malta, yesterday. And the Turing-award winner’s answer set a few back on their heels.

“Incentives are the hardest thing to do,” Micali said.

In 30 years as a cryptographer, he had spent the last 10 working on just that issue.

Source: No Incentive? Algorand Blockchain Sparks Debate at Cryptography Event – CoinDesk

PrivacyStreams Helps Developers Create Privacy Friendly Apps | Carnegie Mellon School of Computer Science

PrivacyStreams Helps Developers Create Privacy Friendly Apps

Decision To Share Personal Data Need Not Be All or Nothing

A smartphone app that uses the raw feed from a device’s microphone or accesses its contact list can raise red flags for a user concerned about privacy. In many cases, however, the app doesn’t need all the details that users find most sensitive.

Researchers at Carnegie Mellon and Peking universities have addressed this dilemma by creating a service, PrivacyStreams, that enables app developers to access the smartphone data they need for app functionality while assuring users that their private information isn’t being sold to an online marketer or otherwise revealed.

A sleep-monitoring app, for instance, might need to access the smartphone’s microphone, but only to register loudness, not to monitor conversations. An app developer could simply sample the microphone feed every minute or so, use software in the PrivacyStreams library to transform the raw data to loudness and then send just the loudness data back to the smartphone for use by the app.

Source: PrivacyStreams Helps Developers Create Privacy Friendly Apps | Carnegie Mellon School of Computer Science

European Commission : CORDIS : News and Events : How you handle your phone gives away more than you think

European Commission

The EU-funded AMBER (Enhanced Mobile Biometrics) project has done just this. The project has shown it can identify gender by breaking down gestures and analysing the way in which users swipe screens using multiple datasets. In a recently published paper the team detail the software and protocol used for data collection, the feature set extracted and subsequent machine learning analysis. The results of this exploratory analysis have confirmed the possibility of sex prediction from the swipe gesture data, obtaining an encouraging 78% accuracy rate using swipe gesture data from two different directions.

Source: European Commission : CORDIS : News and Events : How you handle your phone gives away more than you think

Sexism and Shopping: Female Players Get Most of the Odd Questions at the U.S. Open – The New York Times

A study casts a light not just on gender bias, but also on how algorithms work.

The tennis finals of the United States Open are Saturday for the women and Sunday for the men. On the court, except for the number of sets, they all face the same rules. When they walk off the court, though, the game changes.

Source: Sexism and Shopping: Female Players Get Most of the Odd Questions at the U.S. Open – The New York Times

New software can detect when people text and drive | Waterloo News | University of Waterloo

Computer algorithms developed by engineering researchers at the University of Waterloo can accurately determine when drivers are texting or engaged in other distracting activities. The system uses cameras and artificial intelligence (AI) to detect hand movements that deviate from normal driving behaviour and grades or classifies them in terms of possible safety threats.

Source: New software can detect when people text and drive | Waterloo News | University of Waterloo

The 2017 Top Programming Languages – IEEE Spectrum

Python jumps to No. 1, and Swift enters the Top Ten

It’s summertime here at IEEE Spectrum, and that means it’s time for our fourth interactive ranking of the top programming languages. As with all attempts to rank the usage of different languages, we have to rely on various proxies for popularity. In our case, this means having data journalist Nick Diakopoulos mine and combine 12 metrics from 10 carefully chosen online sources to rank 48 languages. But where we really differ from other rankings is that our interactive allows you choose how those metrics are weighted when they are combined, letting you personalize the rankings to your needs.

Source: The 2017 Top Programming Languages – IEEE Spectrum

Thousands sign up to clean sewage because they didn’t read the small print | Technology | The Guardian

Those who fell for the gag clause inserted into wifi terms and conditions committed to more than a month of community service

Do you read the terms and conditions? Probably not. No one does. And so, inevitably, 22,000 people have now found themselves legally bound to 1000 hours of community service, including, but not limited to, cleaning toilets at festivals, scraping chewing gum off the streets and “manually relieving sewer blockages”.

The (hopefully) joke clause was inserted in the terms and conditions of Manchester-based wifi company Purple for a period of two weeks, “to illustrate the lack of consumer awareness of what they are signing up to when they access free wifi”. The company operates wifi hotspots for a number of brands, including Legoland, Outback Steakhouse and Pizza Express.

Source: Thousands sign up to clean sewage because they didn’t read the small print | Technology | The Guardian

On computer science: a turbo in the algorithm (theconversation.com)

A new “Interview on Computer Science”. Serge Abiteboul and Christine Froidevaux interview Claude Berrou, computer engineer and electronics engineer, and a member of the French Academy of Sciences. Claude Berrou is a professor at IMT Atlantique. He is best known for his work on turbo codes, which has been used extensively in mobile telephony. His current research focus is on informational neuroscience. This article is published in collaboration with the blog Binaire.

Source: On computer science: a turbo in the algorithm