Making We the People More User-Friendly Than Ever

Curated on Posted on by Stefaan Verhulst

The White House: “With more than 14 million users and 21 million signatures, We the People, the White House’s online petition platform, has proved more popular than we ever thought possible. In the nearly three years since launch, we’ve heard from you on a huge range of topics, and issued more than 225 responses.

But we’re not stopping there. We’ve been working to make it easier to sign a petition and today we’re proud to announce the next iteration of We the People.

Since launch, we’ve heard from users who wanted a simpler, more streamlined way to sign petitions without creating an account and logging in every time. This latest update makes that a reality.

We’re calling it “simplified signing” and it takes the account creation step out of signing a petition. As of today, just enter your basic information, confirm your signature via email and you’re done. That’s it. No account to create, no logging in, no passwords to remember.

We the People User Statistics

That’s great news for new users, but we’re betting it’ll be welcomed by our returning signers, too. If you signed a petition six months ago and you don’t remember your password, you don’t have to worry about resetting it. Just enter your email address, confirm your signature, and you’re done.

Go check it out right now on petitions.whitehouse.gov.“

Predicting crime, LAPD-style

Curated on Posted on by Stefaan Verhulst

The Guardian: “The Los Angeles Police Department, like many urban police forces today, is both heavily armed and thoroughly computerised. The Real-Time Analysis and Critical Response Division in downtown LA is its central processor. Rows of crime analysts and technologists sit before a wall covered in video screens stretching more than 10 metres wide. Multiple news broadcasts are playing simultaneously, and a real-time earthquake map is tracking the region’s seismic activity. Half-a-dozen security cameras are focused on the Hollywood sign, the city’s icon. In the centre of this video menagerie is an oversized satellite map showing some of the most recent arrests made across the city – a couple of burglaries, a few assaults, a shooting.

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On a slightly smaller screen the division’s top official, Captain John Romero, mans the keyboard and zooms in on a comparably micro-scale section of LA. It represents just 500 feet by 500 feet. Over the past six months, this sub-block section of the city has seen three vehicle burglaries and two property burglaries – an atypical concentration. And, according to a new algorithm crunching crime numbers in LA and dozens of other cities worldwide, it’s a sign that yet more crime is likely to occur right here in this tiny pocket of the city.
The algorithm at play is performing what’s commonly referred to as predictive policing. Using years – and sometimes decades – worth of crime reports, the algorithm analyses the data to identify areas with high probabilities for certain types of crime, placing little red boxes on maps of the city that are streamed into patrol cars. “Burglars tend to be territorial, so once they find a neighbourhood where they get good stuff, they come back again and again,” Romero says. “And that assists the algorithm in placing the boxes.”
Romero likens the process to an amateur fisherman using a fish finder device to help identify where fish are in a lake. An experienced fisherman would probably know where to look simply by the fish species, time of day, and so on. “Similarly, a really good officer would be able to go out and find these boxes. This kind of makes the average guys’ ability to find the crime a little bit better.”
Predictive policing is just one tool in this new, tech-enhanced and data-fortified era of fighting and preventing crime. As the ability to collect, store and analyse data becomes cheaper and easier, law enforcement agencies all over the world are adopting techniques that harness the potential of technology to provide more and better information. But while these new tools have been welcomed by law enforcement agencies, they’re raising concerns about privacy, surveillance and how much power should be given over to computer algorithms.
P Jeffrey Brantingham is a professor of anthropology at UCLA who helped develop the predictive policing system that is now licensed to dozens of police departments under the brand name PredPol. “This is not Minority Report,” he’s quick to say, referring to the science-fiction story often associated with PredPol’s technique and proprietary algorithm. “Minority Report is about predicting who will commit a crime before they commit it. This is about predicting where and when crime is most likely to occur, not who will commit it.”…”

Finding Mr. Smith or why anti-corruption needs open data

Curated on Posted on by Stefaan Verhulst

Martin Tisne: “Anti-corruption groups have been rightly advocating for the release of information on the beneficial or real owners of companies and trust. The idea is to crack down on tax evasion and corruption by identifying the actual individuals hiding behind several layers of shell companies.
But knowing that “Mr. Smith” is the owner of company X is of no interest, unless you know who Mr. Smith is.
The real interest lies in figuring out that Mr. Smith is linked to company Y, that has been illegally exporting timber from country Z, and that Mr. Smith is the son-in-law of the mining minister of yet another country, who has been accused of embezzling mining industry revenues.
For that, investigative journalists, prosecution authorities, civil society groups like Global Witness and Transparency International will need access not just to public registries of beneficial ownership but also contract data, political exposed persons databases (“PEPs” databases), project by project extractive industry data, and trade export/import data.
Unless those datasets are accessible, comparable, linked, it won’t be possible. We are talking about millions of datasets – no problem for computers to crunch, but impossible to go through manually.
This is what is different in the anti-corruption landscape today, compared to 10 years ago. Technology makes it possible. Don’t get me wrong – there are still huge, thorny political obstacles to getting the data even publicly available in the first place. But unless it is open data, I fear those battles will have been in vain.
That’s why we need open data as a topic on the G20 anti-corruption working group.”

How a Sensor-Filled World Will Change Human Consciousness

Curated on Posted on by Stefaan Verhulst

Scientific American: “Here’s a fun experiment: Try counting the electronic sensors surrounding you right now. There are cameras and microphones in your computer. GPS sensors and gyroscopes in your smartphone. Accelerometers in your fitness tracker. If you work in a modern office building or live in a newly renovated house, you are constantly in the presence of sensors that measure motion, temperature and humidity.
Sensors have become abundant because they have, for the most part, followed Moore’s law: they just keep getting smaller, cheaper and more powerful. A few decades ago the gyroscopes and accelerometers that are now in every smartphone were bulky and expensive, limited to applications such as spacecraft and missile guidance. Meanwhile, as you might have heard, network connectivity has exploded. Thanks to progress in microelectronics design as well as management of energy and the electromagnetic spectrum, a microchip that costs less than a dollar can now link an array of sensors to a low-power wireless communications network….”

A New Way to Look at Law, With Data Viz and Machine Learning

Curated on Posted on by Stefaan Verhulst

  in Wired:

Ravel displays search results as an interactive visualization. Image: Ravel
“On TV, being a lawyer is all about dazzling jurors with verbal pyrotechnics. But for many lawyers–especially young ones–the job is about research. Long, dry, tedious research.
It’s that less glamorous side of the profession that Daniel Lewis and Nik Reed are trying to upend with Ravel. Using data visualization, language analysis, and machine learning, the Stanford Law grads are aiming to reinvent legal research–and perhaps give young lawyers a deeper understanding of their field in the process.
Lawyers have long relied on subscription services like LexisNexis and WestLaw to do their jobs. These services offer indispensable access to vast databases of case documents. Lewis remembers seeing the software on the computers at his Dad’s law firm when he used to hang out there as a kid. You’d put in a keyword, say, securities fraud, and get back a long, rank-ordered list of results relevant to that topic.
Years later, when Lewis was embarking on his own legal career as a first year at Stanford Law, he was struck by how little had changed. “The tools and technologies were the same,” he says. “It was surprising and disconcerting.” Reed, his classmate there, was also perplexed, especially having spent some time in the finance industry working with its high-powered tools. “There was all this cool stuff that everyone else was using in every other field, and it just wasn’t coming to lawyers,” he says.

Early users have reported that Ravel cut their overall research time by up to two thirds….

Ravel’s most ambitious features, however, are intended to help with the analysis of cases. These tools, saved for premium subscribers, are designed to automatically surface the key passages in whatever case you happen to be looking at, sussing out instances when they’ve been cited or reinterpreted in cases that followed.
To do this, Ravel effectively has to map the law, an undertaking that involves both human insight and technical firepower. The process, roughly: Lewis and Reed will look at a particular case, pinpoint the case it’s referencing, and then figure out what ties them together. It could be a direct reference, or a glancing one. It might show up as three paragraphs in that later ruling, or just a sentence.
Once those connections have been made, they’re handed off to Ravel’s engineers. The engineers, which make up more than half of the company’s ten-person team, are tasked with building models that can identify those same sorts of linkages in other cases, using natural language processing. In effect, Ravel’s trying to uncover the subtle linguistic patterns undergirding decades of legal rulings.
That all goes well beyond visual search, and the idea of future generations of lawyers learning from an algorithmic analysis of the law seems quietly dangerous in its own way (though a sterling conceit for a near-future short story!)
Still, compared to the comparatively primitive tools that still dominate the field today, Lewis and Reed see Ravel as a promising resource for young lawyers and law students. “It’s about helping them research more confidently,” Lewis says. “It’s about making sure they understand the story in the right way.” And, of course, about making all that research a little less tedious, too.”

Behavioural Sciences in Practice: Lessons for EU Policymakers

Curated on Posted on by Stefaan Verhulst

Chapter by Di Porto, Fabiana and Rangone, Nicoletta, for the book by Anne-Lise Sibony and Alberto Alemanno (eds), on Nudging and the Law. What can EU Learn from Behavioural Sciences? (Forthcoming): “This chapter establishes how the regulatory process should change in order to bring out and use evidence from cognitive sciences. It further discusses the impact of cognitive sciences on the regulatory toolkit, positing that, on the one hand, traditional tools should be rethought about; and, on the other, that the regulatory toolkit should be enriched by two more strategies: empowerment and nudging (where the first eases the overcoming of cognitive and behavioural limitations, while the second exploits them).“

A brief history of open data

Curated on Posted on by Stefaan Verhulst

Article by Luke Fretwell in FCW: “In December 2007, 30 open-data pioneers gathered in Sebastopol, Calif., and penned a set of eight open-government data principles that inaugurated a new era of democratic innovation and economic opportunity.
“The objective…was to find a simple way to express values that a bunch of us think are pretty common, and these are values about how the government could make its data available in a way that enables a wider range of people to help make the government function better,” Harvard Law School Professor Larry Lessig said. “That means more transparency in what the government is doing and more opportunity for people to leverage government data to produce insights or other great business models.”
The eight simple principles — that data should be complete, primary, timely, accessible, machine-processable, nondiscriminatory, nonproprietary and license-free — still serve as the foundation for what has become a burgeoning open-data movement.

The benefits of open data for agencies

  • Save time and money when responding to Freedom of Information Act requests.
  • Avoid duplicative internal research.
  • Use complementary datasets held by other agencies.
  • Empower employees to make better-informed, data-driven decisions.
  • Attract positive attention from the public, media and other agencies.
  • Generate revenue and create new jobs in the private sector.

Source: Project Open Data

In the seven years since those principles were released, governments around the world have adopted open-data initiatives and launched platforms that empower researchers, journalists and entrepreneurs to mine this new raw material and its potential to uncover new discoveries and opportunities. Open data has drawn civic hacker enthusiasts around the world, fueling hackathons, challenges, apps contests, barcamps and “datapaloozas” focused on issues as varied as health, energy, finance, transportation and municipal innovation.
In the United States, the federal government initiated the beginnings of a wide-scale open-data agenda on President Barack Obama’s first day in office in January 2009, when he issued his memorandum on transparency and open government, which declared that “openness will strengthen our democracy and promote efficiency and effectiveness in government.” The president gave federal agencies three months to provide input into an open-government directive that would eventually outline what each agency planned to do with respect to civic transparency, collaboration and participation, including specific objectives related to releasing data to the public.
In May of that year, Data.gov launched with just 47 datasets and a vision to “increase public access to high-value, machine-readable datasets generated by the executive branch of the federal government.”
When the White House issued the final draft of its federal Open Government Directive later that year, the U.S. open-government data movement got its first tangible marching orders, including a 45-day deadline to open previously unreleased data to the public.
Now five years after its launch, Data.gov boasts more than 100,000 datasets from 227 local, state and federal agencies and organizations….”

How Long Is Too Long? The 4th Amendment and the Mosaic Theory

Curated on Posted on by Stefaan Verhulst

Law and Liberty Blog: “Volume 8.2 of the NYU Journal of Law and Liberty has been sent to the printer and physical copies will be available soon, but the articles in the issue are already available online here. One article that has gotten a lot of attention so far is by Steven Bellovin, Renee Hutchins, Tony Jebara, and Sebastian Zimmeck titled “When Enough is Enough: Location Tracking, Mosaic Theory, and Machine Learning.” A direct link to the article is here.
The mosaic theory is a modern corollary accepted by some academics – and the D.C. Circuit Court of Appeals in Maynard v. U.S. – as a twenty-first century extension of the Fourth Amendment’s prohibition on unreasonable searches of seizures. Proponents of the mosaic theory argue that at some point enough individual data collections, compiled and analyzed together, become a Fourth Amendment search. Thirty years ago the Supreme Court upheld the use of a tracking device for three days without a warrant, however the proliferation of GPS tracking in cars and smartphones has made it significantly easier for the police to access a treasure trove of information about our location at any given time.
It is easy to see why this theory has attracted some support. Humans are creatures of habit – if our public locations are tracked for a few days, weeks, or a month, it is pretty easy for machines to learn our ways and assemble a fairly detailed report for the government about our lives. Machines could basically predict when you will leave your house for work, what route you will take, when and where you go grocery shopping, all before you even do it, once it knows your habits. A policeman could observe you moving about in public without a warrant of course, but limited manpower will always reduce the probability of continuous mass surveillance. With current technology, a handful of trained experts could easily monitor hundreds of people at a time from behind a computer screen, and gather even more information than most searches requiring a warrant. The Supreme Court indicated a willingness to consider the mosaic theory in U.S. v. Jones, but has yet to embrace it…”

The article in Law & Liberty details the need to determine at which point machine learning creates an intrusion into our reasonable expectations of privacy, and even discusses an experiment that could be run to determine how long data collection can proceed before it is an intrusion. If there is a line at which individual data collection becomes a search, we need to discover where that line is. One of the articles’ authors, Steven Bollovin, has argued that the line is probably at one week – at that point your weekday and weekend habits would be known. The nation’s leading legal expert on criminal law, Professor Orin Kerr, fired back on the Volokh Conspiracy that Bollovin’s one week argument is not in line with previous iterations of the mosaic theory.

Estonian plan for 'data embassies' overseas to back up government databases

Curated on Posted on by Stefaan Verhulst

Graeme Burton in Computing: “Estonia is planning to open “data embassies” overseas to back up government databases and to operate government “in the cloud“.
The aim is partly to improve efficiency, but driven largely by fear of invasion and occupation, Jaan Priisalu, the director general of Estonian Information System Authority, told Sky News.
He said: “We are planning to actually operate our government in the cloud. It’s clear also how it helps to protect the country, the territory. Usually when you are the military planner and you are planning the occupation of the territory, then one of the rules is suppress the existing institutions.
“And if you are not able to do it, it means that this political price of occupying the country will simply rise for planners.”
Part of the rationale for the plan, he continued, was fear of attack from Russia in particular, which has been heightened following the occupation of Crimea, formerly in Ukraine.
“It’s quite clear that you can have problems with your neighbours. And our biggest neighbour is Russia, and nowadays it’s quite aggressive. This is clear.”
The plan is to back up critical government databases outside of Estonia so that affairs of state can be conducted in the cloud, even if the country is invaded. It would also have the benefit of keeping government information out of invaders’ hands – provided it can keep its government cloud secure.
According to Sky News, the UK is already in advanced talks about hosting the Estonian government databases and may make the UK the first of Estonia’s data embassies.
Having wrested independence from the Soviet Union in 1991, Estonia has experienced frequent tension with its much bigger neighbour. In 2007, for example, after the relocation of the “Bronze Soldier of Tallinn” and the exhumation of the soldiers buried in a square in the centre of the capital to a military cemetery in April 2007, the country was subject to a prolonged cyber-attack sourced to Russia.
Russian hacker “Sp0Raw” said that the most efficient of the online attacks on Estonia could not have been carried out without the approval of Russian authorities and added that the hackers seemed to act under “recommendations” from parties in government. However, claims by Estonia that the Russian government was directly involved in the attacks were “empty words, not supported by technical data”.
Mike Witt, deputy director of the US Computer Emergency Response Team (CERT), suggested that the distributed denial-of-service (DDOS) attacks, while crippling to the Estonian government at the time, were not significant in scale from a technical standpoint. However, the Estonian government was forced to shut down many of its online operations in response.
At the same time, the Estonian government has been accused of implementing anti-Russian laws and discriminating against its large ethnic Russian population.
Last week, the Estonian government unveiled a plan to allow anyone in the world to apply for “digital citizenship“ of the country, enabling them to use Estonian online services, open bank accounts, and start companies without having to physically reside in the country.”

ShouldWe

Curated on Posted on by Stefaan Verhulst

About ShouldWe.org: “ShouldWe is about all of us. We believe people deserve to know not just what decisions are being taken in their name but why.  Our vision is of a world where everyone is able to interrogate policymakers’ arguments by accessing simple information about issues of public policy, and the evidence that supports it.
ShouldWe.org is a non-partisan, crowd-sourced, online guide to policy debates and the evidence which informs them. We serve journalists, analysts and advocates by aggregating the most authoritative policy information, from both sides, in one place. Our mission is to improve democratic scrutiny by resourcing journalists and other active citizens to learn more about the causes and consequences of the decisions which affect our lives.
We are a not-for-profit organisation. Please help us by contributing and editing content, telling your colleagues and friends, and letting us know how we can make ShouldWe.org better.
Learn how to create a ShouldWe page here
Find out how to help ShouldWe in other ways here.
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