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Content Type: Examples
Caucuses, which are used in some US states as a method of voting in presidential primaries, rely on voters indicating their support for a particulate candidate by travelling to the caucus location. In a 2016 Marketplace radio interview, Tom Phillips, the CEO of Dstillery, a big data intelligence company, said that his company had collected mobile device IDs at the location for each of the political party causes during the Iowa primaries. Dstillery paired caucus-goers with their online…
Content Type: Examples
In a presentation given at the Knowledge Discovery and Data Mining conference in 2016, researchers discussed a method of using the data generated by smart card public transport tickets to catch pickpockets. In a study of 6 million passenger movements in Beijing, the researchers used a classifier to pick out anomalous journeys - sudden variations in the patterns of ordinary travellers or routes that made no sense. A second classifier primed with information derived from police reports and social…
Content Type: Examples
As part of its Smart Nation programme, in 2016 Singapore launched the most extensive collection of data on everyday living ever attempted in a city. The programme involved deploying myriad sensors and cameras across the city-state to comprehensively monitor people, places, and things, including all locally registered vehicles. The platform into which all this data will be fed, Virtual Singapore, will give the government the ability to watch the country's functioning in real time. The government…
Content Type: Examples
In 2015, the Royal Parks conducted a covert study of visitors to London's Hyde Park using anonymised mobile phone signals provided by the network operator EE to analyse footfall. During the study, which was conducted via government-funded Future Cities Catapult, the Royal Parks also had access to aggregated age and gender data, creating a detailed picture of how different people used the park over the period of about a year. The study also showed the percentage of EE subscribers who visited…
Content Type: Examples
A new generation of technology has given local law enforcement officers in some parts of the US unprecedented power to peer into the lives of citizens. In Fresno, California, the police department's $600,000 Real Time Crime Center is providing a model for other such centres that have opened in New York, Houston, and Seattle over the decade between 2006 and 2016. The group of technologies used in these centres includes ShotSpotter, which uses microphones around the city to triangulate the…
Content Type: Examples
By 2016, a logical direction for data-driven personalisation efforts to go was toward the "Internet of Emotions": equipping devices with facial, vocal, and biometric sensors that use affective computing to analyse and influence the feelings of device owners. Of particular concern is the potential for using subtle cues to manipulate people in a more nuanced way than is presently discussed. The beginnings of this are already visible in the example of an Amazon Echo that displayed the items a…
Content Type: Examples
In 2015, ABI Research discovered that the power light on the front of Alphabet's Nest Cam was deceptive: even when users had used the associated app to power down the camera and the power light went off, the device continued to monitor its surroundings, noting sound, movement, and other activities. The proof lay in the fact that the device's power drain diminished by an amount consistent with only turning off the LED light. Alphabet explained the reason was that the camera had to be ready to be…
Content Type: Examples
Because banks often decline to give loans to those whose "thin" credit histories make it hard to assess the associated risk, in 2015 some financial technology startups began looking at the possibility of instead performing such assessments by using metadata collected by mobile phones or logged from internet activity. The algorithm under development by Brown University economist Daniel Björkegren for the credit-scoring company Enterpreneurial Finance Lab was built by examining the phone records…
Content Type: Examples
A new generation of technology has given local law enforcement officers in some parts of the US unprecedented power to peer into the lives of citizens. The police department of Frenso California uses a cutting-edge Real Time Crime Center that relies on software like Beware.
As officers respond to calls, Beware automatically runs the address. The program also scoures billions of data points, including arrest reports, property records, commercial databases, deep Web searches and the man’s social…
Content Type: Examples
In 2016, the American Civil Liberties Union of Northern California published a report revealing that the social media monitoring service Geofeedia had suggested it could help police track protesters. The report's publication led Twitter and Facebook to restrict Geofeedia's access to their bulk data. ACLUNC argued that even though the data is public, using it for police surveillance is an invasion of privacy. Police are not legally required to get a warrant before searching public data; however…
Content Type: Examples
At the Sixth Annual Conference on Social Media Within the Defence and Military Sector, held in London in 2016, senior military and intelligence officials made it clear that governments increasingly view social media as a tool for the Armed Forces and a "new front in warfare". Social media are also viewed as a source of intelligence on civilian populations and enemies and as a vector for propaganda. The conference was sponsored by Thales, which was working with the National Research Council of…
Content Type: Examples
As GPS began being increasingly incorporated into smartphones, satnav manufacturers like the Dutch company TomTom were forced to search for new revenue streams. In 2011, TomTom was forced to apologise when the Dutch newspaper AD reported that the company had sold driving data collected from customers to police, which used it to site speed cameras in locations where speeding was common. TomTom said that any information it shares had been anonymised; however, in response to the newspaper story…
Content Type: Examples
Uber has closely studied how dynamic pricing functions and when it's acceptable to users. One discovery is that round numbers signal haste and sloppiness where riders appear to believe that more precise numbers (for example, 2.1 instead of 2) have been carefully worked out by an algorithm. The company's head of head of economic research Keith Chen says that riders will pay up to 9.9 times the normal price if their phone's battery is almost dead, information the Uber app openly collects in order…
Content Type: Examples
In 2016, researchers at MIT's Computer Science and Artificial Intelligence Laboratory developed a new device that uses wireless signals that measure heartbeats by bouncing off a person's body. The researchers claim that this system is 87% accurate in recognising joy, pleasure, sadness, or anger based on the heart rate after first measuring how the individual's body reacts in various emotional states. Unlike a medical electrocardiogram, it does not require a sensor to be attached to the person's…
Content Type: Examples
In 2016, the Big Data lab at the Chinese search engine company Baidu published a study of an algorithm it had developed that it claimed could predict crowd formation and suggested it could be used to warn authorities and individuals of public safety threats stemming from unusually large crowds. The study, which was inspired by a New Year's Eve 2014 stampede in Shanghai that killed more than 30 people, correlated aggregated data from Baidu Map route searches with the crowd density at the places…
Content Type: Examples
For some months in 2017, in one of a series of high-risk missteps, Uber violated Apple's privacy guidelines by tagging and identifying iPhones even after their users had deleted Uber's app. When Apple discovered the deception, CEO Tim Cook told Uber CEO Travis Kalanick to cease the practice or face having the Uber app barred from the App Store.
External Link to Story
https://www.nytimes.com/2017/04/23/technology/travis-kalabnick-pushes-uber-and-himself-to-the-precipice.html
Content Type: News & Analysis
Ask people around you if they live in a smart city, and more likely than not they will answer that they don’t. I can tell you that because I have tried.
When giving talks about this very topic in cities like Berlin, The Hague and Stockholm, I always ask this question at the start. The rough ratio I tend to get is that: 15 per cent hesitantly raise their hand to say they do, 60 per cent don’t, 20 per cent just look confused and 5 per cent are not listening.
And yet most people who live in cities…
Content Type: Advocacy
On 20 March 2015, Privacy International and Open Rights Group submitted comments on the UK Government's draft Equipment Interference Code of Practice.
The UK has been hacking for over a decade, yet the release of the draft Code of Practice is the first time the UK intelligence services have sought public authorisation for their activities. Indeed, it is the first time the intelligence services have publicly acknowledged they engage in hacking.
Unfortunately, the draft Code of…