city & municipal

#Bring back our girls

Curated on May 7, 2014August 15, 2018 by Stefaan Verhulst

The Guardian: “The abduction of more than 200 schoolgirls in Nigeria has lead to campaigns calling for their rescue, on social media and offline all around the world.
After Nigerian protestors marched on parliament in the capital Abuja calling for action on April 30, people in cities around the world have followed suit and organised their own marches.
A social media campaign under the hashtag #Bringbackourgirls started trending in Nigeria two weeks ago and has now been tweeted more than one million times. It was first used on April 23 at the opening ceremony for a UNESCO event honouring the Nigerian city of Port Harcourt as the 2014 World Book Capital City. A Nigerian lawyer in Abuja, Ibrahim M. Abdullahi, tweeted the call in a speech by Dr. Oby Ezekwesili, Vice President of the World Bank for Africa to “Bring Back the Girls!”

Another mass demonstration took place outside the Nigerian Defence Headquarters in Abuja on May 6 and many other protests have been organised in response to a social media campaign asking for people around the world to march and wear red in solidarity. People came out in protest at the Nigerian embassy in London, in Los Angeles and New York.

A global “social media march” has also been organised asking supporters to use their networks to promote the campaign for 200 minutes on May 8.
A petition started on Change.org by a Nigerian woman in solidarity with the schoolgirls has now been signed by more than 300,000 supporters.
Amnesty International and UNICEF have backed the campaign, as well as world leaders and celebrities, including Hilary Clinton, Malala Yousafzai and rappers Wyclef Jean and Chris Brown, whose mention of the campaign was retweeted more than 10,000 times.

After three weeks of silence the Nigerian President Goodluck Jonathan vowed to find the schoolgirls on April 3, stating: “wherever these girls are, we’ll get them out”. On the same day, John Kerry pledged assistance from the US.”

you are here: “Every day for the next year, we will make a map of a city in which we have lived.
Each of these maps will be an aggregation of thousands of microstories, tracing the narratives of our collective experience. We will make maps of the little things that make up life — from the trees we hug, to the places where we crashed our bikes, to the benches where we fell in love.
Over time, we will grow this to 100 different maps of 100 different cities, creating an atlas of human experience.
We hope that by showing these stories, we empower people to make their city — and therefore the world — a more beautiful place.

You Are Here is a project of the Social Computing Group at the MIT Media Lab.

MAPS: https://web.archive.org/web/http://youarehere.cc/#/maps “

The "Accessibility Map"

Curated on May 7, 2014May 29, 2019 by Stefaan Verhulst

Webby 2014 Nominee: “Project Goal is to make information about accessible venues accessible to people.

About venues where people with disabilities can engage in sports and recreational activities, and live full lives without any barriers or stereotypes.

The Solution

To develop a website where everyone can not only find accessible venues in each city, but also add new venues to the website’s database.
Creating the accessibility rating list for russian cities to get an idea how accessible a particular city is, will draw the local governement’ s attention to this problem.
The foundation of the website is an interactive map of accessible venues in Russia, which can help people with disabilities find locations where they can participate in sports, take classes or recreate.
All you need to do is choose the necessary city and street, and the map will show all the accessible venues in the city.

The Result

After a few months of operation:
— over 14 000 venues
— over 600 cities
— millions of people with disabilities have become able to live full lives

Project’s Website: kartadostupnosti.ru“

Sharing in a Changing Climate

Curated on May 7, 2014August 3, 2018 by Stefaan Verhulst

Helen Goulden in the Huffington Post: “Every month, a social research agency conducts a public opinion survey on 30,000 UK households. As part of this households are asked about what issues they think are the most important; things such as crime, unemployment, inequality, public health etc. Climate change has ranked so consistently low on these surveys that they don’t both asking any more.
On first glance, it would appear that most people don’t care about a changing climate.
Yet, that’s simply not true. Many people care deeply, but fleetingly – in the same way they may consider their own mortality before getting back to thinking about what to have for tea. And others care, but fail to change their behaviour in a way that’s proportionate to their concerns. Certainly that’s my unhappy stomping ground.
Besides what choices do we really have? Even the most progressive, large organisations have been glacial to move towards any form of real form of sustainability. For many years we have struggled with the Frankenstein-like task of stitching ‘sustainability’ onto existing business and economic models and the results, I think, speak for themselves.
That the Collaborative Economy presents us with an opportunity – in Napster-like ways – to disrupt and evolve toward something more sustainable is compelling idea. Looking out to a future filled with opportunities to reconfigure how we produce, consume and dispose of the things we want and need to live, work and play.
Whether the journey toward sustainability is short or long, it will be punctuated with a good degree of turbulence, disruption and some largely unpredictable events. How we deal with those events and what role communities, collaboration and technology play may set the framework and tone for how that future evolves. Crises and disruption to our entrenched living patterns present ripe opportunities for innovation and space for adopting new behaviours and practices.
No-one is immune from the impact of erratic and extreme weather events. And if we accept that these events are going to increase in frequency, we must draw the conclusion that emergency state and government resources may be drawn more thinly over time.
Across the world, there is a fairly well organised state and international infrastructure for dealing with emergencies , involving everyone from the Disaster Emergency Committee, the UN, central and local government and municipalities, not for profit organisations and of course, the military. There is a clear reason why we need this kind of state emergency response; I’m not suggesting that we don’t.
But through the rise of open data and mass participation in platforms that share location, identity and inventory, we are creating a new kind of mesh; a social and technological infrastructure that could considerably strengthen our ability to respond to unpredictable events.
In the last few years we have seen a sharp rise in the number of tools and crowdsourcing platforms and open source sensor networks that are focused on observing, predicting or responding to extreme events:
• Apps like Shake Alert, which emits a minute warning that an earthquake is coming
• Rio’s sensor network, which measures rainfall outside the city and can predict flooding
• Open Source sensor software Arduino which is being used to crowd-source weather and pollution data
• Propeller Health, which is using Asthma sensors on inhalers to crowd-source pollution hotspots
• Safecast, which was developed for crowdsourcing radiation levels in Japan
Increasingly we have the ability to deploy open source, distributed and networked sensors and devices for capturing and aggregating data that can help us manage our responses to extreme weather (and indeed, other kinds of) events.
Look at platforms like LocalMind and Foursquare. Today, I might be using them to find out whether there’s a free table at a bar or finding out what restaurant my friends are in. But these kind of social locative platforms present an infrastructure that could be life-saving in any kind of situation where you need to know where to go quickly to get out of trouble. We know that in the wake of disruptive events and disasters, like bombings, riots etc, people now intuitively and instinctively take to technology to find out what’s happening, where to go and how to co-ordinate response efforts.
During the 2013 Bart Strike in San Francisco, ventures like Liquid Space and SideCar enabled people to quickly find alternative places to work, or alternatives to public transport, to mitigate the inconvenience of the strike. The strike was a minor inconvenience compared to the impact of a hurricane and flood but nevertheless, in both those instances, ventures decided waive their fees; as did AirBnB when 1,400 New York AirBnB hosts opened their doors to people who had been left homeless through Hurricane Sandy in 2012.
The impulse to help is not new. The matching of people’s offers of help and resources to on-the-ground need, in real time, is.”

On the barriers for local government releasing open data

Curated on May 7, 2014August 3, 2018 by Stefaan Verhulst

Paper by Peter Conradie and Dr. Sunil Choenni in Government Information Quarterly: “Due to expected benefits such as citizen participation and innovation, the release of Public Sector Information as open data is getting increased attention on various levels of government. However, currently data release by governments is still novel and there is little experience and knowledge thus far about its benefits, costs and barriers. This is compounded by a lack of understanding about how internal processes influence data release. Our aim in this paper is to get a better understanding of these processes and how they influence data release, i.e., to find determinants for the release of public sector information. For this purpose, we conducted workshops, interviews, questionnaires, desk research and practice based cases in the education program of our university, involving six local public sector organizations. We find that the way data is stored, the way data is obtained and the way data is used by a department are crucial indicators for open data release. We conclude with the lessons learned based on our research findings. These findings are: we should take a nuanced approach towards data release, avoid releasing data for its own sake, and take small incremental steps to explore data release.”

Out in the Open: An Open Source Website That Gives Voters a Platform to Influence Politicians

Curated on May 6, 2014August 3, 2018 by Stefaan Verhulst

Klint Finley in Wired: “This is the decade of the protest. The Arab Spring. The Occupy Movement. And now the student demonstrations in Taiwan.
Argentine political scientist Pia Mancini says we’re caught in a “crisis of representation.” Most of these protests have popped up in countries that are at least nominally democratic, but so many people are still unhappy with their elected leaders. The problem, Mancini says, is that elected officials have drifted so far from the people they represent, that it’s too hard for the average person to be heard.
“If you want to participate in the political system as it is, it’s really costly,” she says. “You need to study politics in university, and become a party member and work your way up. But not every citizen can devote their lives to politics.”

Democracy OS is designed to address that problem by getting citizens directly involved in debating specific proposals when their representatives are actually voting on them.

That’s why Mancini started the Net Democracy foundation, a not-for-profit that explores ways of improving civic engagement through technology. The foundation’s first project is something called Democracy OS, an online platform for debating and voting on political issues, and it’s already finding a place in the world. The federal government in Mexico is using this open-source tool to gather feedback on a proposed public data policy, and in Tunisia, a non-government organization called iWatch has adopted it in an effort to give the people a stronger voice.
Mancini’s dissatisfaction with electoral politics stems from her experience working for the Argentine political party Unión Celeste y Blanco from 2010 until 2012. “I saw some practices that I thought were harmful to societies,” she says. Parties were too interested in the appearances of the candidates, and not interested enough in their ideas. Worse, citizens were only consulted for their opinions once every two to four years, meaning politicians could get away with quite a bit in the meantime.
Democracy OS is designed to address that problem by getting citizens directly involved in debating specific proposals when their representatives are actually voting on them. It operates on three levels: one for gathering information about political issues, one for public debate about those issues, and one for actually voting on specific proposals.
Various communities now use a tool called Madison to discuss policy documents, and many activists and community organizations have adopted Loomio to make decisions internally. But Democracy OS aims higher: to provide a common platform for any city, state, or government to actually put proposals to a vote. “We’re able to actually overthrow governments, but we’re not using technology to decide what to do next,” Mancini says. “So the risk is that we create power vacuums that get filled with groups that are already very well organized. So now we need to take it a bit further. We need to decide what democracy for the internet era looks like.”

Software Shop as Political Party

Today Net Democracy is more than just a software development shop. It’s also a local political party based in Beunos Aires. Two years ago, the foundation started pitching the first prototype of the software to existing political parties as a way for them to gather feedback from constituents, but it didn’t go over well. “They said: ‘Thank you, this is cool, but we’re not interested,’” Mancini remembers. “So we decided to start our own political party.”
The Net Democracy Party hasn’t won any seats yet, but it promises that if it does, it will use Democracy OS to enable any local registered voter to tell party representatives how to vote. Mancini says the party representatives will always vote the way constituents tell them to vote through the software.

‘We’re not saying everyone should vote on every issue all the time. What were saying is that issues should be open for everyone to participate.’

She also uses the term “net democracy” to refer to the type of democracy that the party advocates, a form of delegative democracy that attempts to strike a balance between representative democracy and direct democracy. “We’re not saying everyone should vote on every issue all the time,” Mancini explains. “What were saying is that issues should be open for everyone to participate.”
Individuals will also be able to delegate their votes to other people. “So, if you’re not comfortable voting on health issues, you can delegate to someone else to vote for you in that area,” she says. “That way people with a lot of experience in an issue, like a community leader who doesn’t have lobbyist access to the system, can build more political capital.”
She envisions a future where decisions are made on two levels. Decisions that involve specific knowledge — macroeconomics, tax reforms, judiciary regulations, penal code, etc. — or that affect human rights are delegated “upwards” to representatives. But then decisions related to local issues — transport, urban development, city codes, etc. — cab be delegated “downwards” to the citizens.

The Secret Ballot Conundrum

Ensuring the integrity of the votes gathered via Democracy OS will be a real challenge. The U.S. non-profit organization Black Box Voting has long criticized electronic voting schemes as inherently flawed. “Our criticism of internet voting is that it is not transparent and cannot be made publicly transparent,” says Black Box Voting founder Bev Harris. “With transparency for election integrity defined as public ability to see and authenticate four things: who can vote, who did vote, vote count, and chain of custody.”
In short, there’s no known way to do a secret ballot online because any system for verifying that the votes were counted properly will inevitably reveal who voted for what.
Democracy OS deals with that by simply doing away with secret ballots. For now, the Net Democracy party will have people sign-up for Democracy OS accounts in person with their government issued ID cards. “There is a lot to be said about how anonymity allows you to speak more freely,” Mancini says. “But in the end, we decided to prioritize the reliability, accountability and transparency of the system. We believe that by making our arguments and decisions public we are fostering a civic culture. We will be more responsible for what we say and do if it’s public.”
But making binding decisions based on these online discussions would be problematic, since they would skew not just towards those tech savvy enough to use the software, but also towards those willing to have their names attached to their votes publicly. Fortunately, the software isn’t yet being used to gather real votes, just to gather public feedback….”

The Universe Is Programmable. We Need an API for Everything

Curated on May 5, 2014August 15, 2018 by Stefaan Verhulst

Keith Axline in Wired: “Think about it like this: In the Book of Genesis, God is the ultimate programmer, creating all of existence in a monster six-day hackathon.
Or, if you don’t like Biblical metaphors, you can think about it in simpler terms. Robert Moses was a programmer, shaping and re-shaping the layout of New York City for more than 50 years. Drug developers are programmers, twiddling enzymes to cure what ails us. Even pickup artists and conmen are programmers, running social scripts on people to elicit certain emotional results.

Keith Axline in Wired: “Everyone is becoming a programmer. The next step is to realize that everything is a program.

The point is that, much like the computer on your desk or the iPhone in your hand, the entire Universe is programmable. Just as you can build apps for your smartphones and new services for the internet, so can you shape and re-shape almost anything in this world, from landscapes and buildings to medicines and surgeries to, well, ideas — as long as you know the code.
That may sound like little more than an exercise in semantics. But it’s actually a meaningful shift in thinking. If we look at the Universe as programmable, we can start treating it like software. In short, we can improve almost everything we do with the same simple techniques that have remade the creation of software in recent years, things like APIs, open source code, and the massively popular code-sharing service GitHub.
The great thing about the modern software world is that you don’t have to build everything from scratch. Apple provides APIs, or application programming interfaces, that can help you build apps on their devices. And though Tim Cook and company only give you part of what you need, you can find all sorts of other helpful tools elsewhere, thanks to the open source software community.
The same is true if you’re building, say, an online social network. There are countless open source software tools you can use as the basic building blocks — many of them open sourced by Facebook. If you’re creating almost any piece of software, you can find tools and documentation that will help you fashion at least a small part of it. Chances are, someone has been there before, and they’ve left some instructions for you.
Now we need to discover and document the APIs for the Universe. We need a standard way of organizing our knowledge and sharing it with the world at large, a problem for which programmers already have good solutions. We need to give everyone a way of handling tasks the way we build software. Such a system, if it can ever exist, is still years away — decades at the very least — and the average Joe is hardly ready for it. But this is changing. Nowadays, programming skills and the DIY ethos are slowly spreading throughout the population. Everyone is becoming a programmer. The next step is to realize that everything is a program.

What Is an API?

The API may sound like just another arcane computer acronym. But it’s really one of the most profound metaphors of our time, an idea hiding beneath the surface of each piece of tech we use everyday, from iPhone apps to Facebook. To understand what APIs are and why they’re useful, let’s look at how programmers operate.
If I’m building a smartphone app, I’m gonna need — among so many other things — a way of validating a signup form on a webpage to make sure a user doesn’t, say, mistype their email address. That validation has nothing to do with the guts of my app, and it’s surprisingly complicated, so I don’t really want to build it from scratch. Apple doesn’t help me with that, so I start looking on the web for software frameworks, plugins, Software Developer Kits (SDKs) — anything that will help me build my signup tool.
Hopefully, I’ll find one. And if I do, chances are it will include some sort of documentation or “Readme file” explaining how this piece of code is supposed to be used so that I can tailor it to my app. This Readme file should contain installation instructions as well as the API for the code. Basically, an API lays out the code’s inputs and outputs. It shows what me what I have to send the code and what it will spit back out. It shows how I bolt it onto my signup form. So the name is actually quite explanatory: Application Programming Interface. An API is essentially an instruction manual for a piece of software.
Now, let’s combine this with the idea that everything is an application: molecules, galaxies, dogs, people, emotional states, abstract concepts like chaos. If you do something to any these things, they’ll respond in some way. Like software, they have inputs and outputs. What we need to do is discover and document their APIs.
We aren’t dealing with software code here. Inputs and outputs can themselves be anything. But we can closely document these inputs and their outputs — take what we know about how we interface with something and record it in a standard way that it can be used over and over again. We can create a Readme file for everything.
We can start by doing this in small, relatively easy ways. How about APIs for our cities? New Zealand just open sourced aerial images of about 95 percent of its land. We could write APIs for what we know about building in those areas, from properties of the soil to seasonal weather patterns to zoning laws. All this knowledge exists but it hasn’t been organized and packaged for use by anyone who is interested. And we could go still further — much further.
For example, between the science community, the medical industry and the billions of human experiences, we could probably have a pretty extensive API mapped out of the human stomach — one that I’d love to access when I’m up at 3am with abdominal pains. Maybe my microbiome is out of whack and there’s something I have on-hand that I could ingest to make it better. Or what if we cracked the API for the signals between our eyes and our brain? We wouldn’t need to worry about looking like Glassholes to get access to always-on augmented reality. We could just get an implant. Yes, these APIs will be slightly different for everyone, but that brings me to the next thing we need.

A GitHub for Everything

We don’t just need a Readme for the Universe. We need a way of sharing this Readme and changing it as need be. In short, we need a system like GitHub, the popular online service that lets people share and collaborate on software code.
Let’s go back to the form validator I found earlier. Say I made some modifications to it that I think other programmers would find useful. If the validator is on GitHub, I can create a separate but related version — a fork — that people can find and contribute to, in the same way I first did with the original software.

This creates a tree of knowledge, with giant groups of people creating and merging branches, working on their small section and then giving it back to the whole.

GitHub not only enables this collaboration, but every change is logged into separate versions. If someone were so inclined, they could go back and replay the building of the validator, from the very first save all the way up to my changes and whoever changes it after me. This creates a tree of knowledge, with giant groups of people creating and merging branches, working on their small section and then giving it back to the whole.
We should be able to funnel all existing knowledge of how things work — not just software code — into a similar system. That way, if my brain-eye interface needs to be different, I (or my personal eye technician) can “fork” the API. In a way, this sort of thing is already starting to happen. People are using GitHub to share government laws, policy documents, Gregorian chants, and the list goes on. The ultimate goal should be to share everything.
Yes, this idea is similar to what you see on sites like Wikipedia, but the stuff that’s shared on Wikipedia doesn’t let you build much more than another piece of text. We don’t just need to know what things are. We need to know how they work in ways that let us operate on them.

The Open Source Epiphany

If you’ve never programmed, all this can sound a bit, well, abstract. But once you enter the coding world, getting a loose grasp on the fundamentals of programming, you instantly see the utility of open source software. “Oooohhh, I don’t have to build this all myself,” you say. “Thank God for the open source community.” Because so many smart people contribute to open source, it helps get the less knowledgeable up to speed quickly. Those acolytes then pay it forward with their own contributions once they’ve learned enough.
Today, more and more people are jumping on this train. More and more people are becoming programmers of some shape or form. It wasn’t so long ago that basic knowledge of HTML was considered specialized geek speak. But now, it’s a common requirement for almost any desk job. Gone are the days when kids made fun of their parents for not being able to set the clock on the VCR. Now they get mocked for mis-cropping their Facebook profile photos.
These changes are all part of the tech takeover of our lives that is trickling down to the masses. It’s like how the widespread use of cars brought a general mechanical understanding of engines to dads everywhere. And this general increase in aptitude is accelerating along with the technology itself.
Steps are being taken to make programming a skill that most kids get early in school along with general reading, writing, and math. In the not too distant future, people will need to program in some form for their daily lives. Imagine the world before the average person knew how to write a letter, or divide two numbers, compared to now. A similar leap is around the corner…”

A New Map Gives New Yorkers the Power to Report Traffic Hazards

Curated on May 1, 2014August 15, 2018 by Stefaan Verhulst

Sarah Goodyear in the Atlantic/Cities: “Ask any New Yorker about unsafe conditions on the city’s streets. Go ahead, ask.
You might want to sit down. This is going to take a while.
New York City’s streets are some of the most heavily used public spaces in the nation. A lot of the time, the swirling mass of users share space remarkably well. Every second in New York, it sometimes seems, a thousand people just barely miss colliding, thanks to a finely honed sense of self-preservation and spatial awareness.
The dark side is that sometimes, they do collide. These famously chaotic and contested streets are often life-threatening. Drivers routinely drive well over the 30 mph speed limit, run red lights, and fail to yield to pedestrians in crosswalks. Pedestrians step out into traffic, sometimes without looking at what’s coming their way. Bicyclists ride the wrong way up one-way streets.
In recent years, the city has begun to address the problem, mainly through design solutions like better bike infrastructure, pedestrian refuges, and crosswalk countdown clocks. Still, last year, 286 New Yorkers died in traffic crashes.
Mayor Bill de Blasio vowed almost as soon as he was sworn into office in January to pursue an initiative called Vision Zero, which aims to eliminate traffic fatalities through a combination of design, enforcement, and education.
A new tool in the Vision Zero effort was unveiled earlier this week: a map of the city on which people can log their observations and complaints about chronically unsafe conditions. The map offers a menu of icons including red-light running, double-parking, failure to yield, and speeding, and allows users to plot them on a map of the city’s streets. Sites where pedestrian fatalities have occurred since 2009 are marked, and the most dangerous streets in each borough for people on foot are colored red.

The map, a joint project of DOT, the NYPD, and the Taxi and Limousine Commission, has only been live for a couple of days. Already, it is speckled with dozens of multicolored dots indicating problem areas. (Full disclosure: The map was designed by OpenPlans, a nonprofit affiliated with Streetsblog, where I worked several years ago.)…”

Saving Big Data from Big Mouths

Curated on May 1, 2014July 18, 2019 by Stefaan Verhulst

Cesar A. Hidalgo in Scientific American: “It has become fashionable to bad-mouth big data. In recent weeks the New York Times, Financial Times, Wired and other outlets have all run pieces bashing this new technological movement. To be fair, many of the critiques have a point: There has been a lot of hype about big data and it is important not to inflate our expectations about what it can do.
But little of this hype has come from the actual people working with large data sets. Instead, it has come from people who see “big data” as a buzzword and a marketing opportunity—consultants, event organizers and opportunistic academics looking for their 15 minutes of fame.
Most of the recent criticism, however, has been weak and misguided. Naysayers have been attacking straw men, focusing on worst practices, post hoc failures and secondary sources. The common theme has been to a great extent obvious: “Correlation does not imply causation,” and “data has biases.”
Critics of big data have been making three important mistakes:
First, they have misunderstood big data, framing it narrowly as a failed revolution in social science hypothesis testing. In doing so they ignore areas where big data has made substantial progress, such as data-rich Web sites, information visualization and machine learning. If there is one group of big-data practitioners that the critics should worship, they are the big-data engineers building the social media sites where their platitudes spread. Engineering a site rich in data, like Facebook, YouTube, Vimeo or Twitter, is extremely challenging. These sites are possible because of advances made quietly over the past five years, including improvements in database technologies and Web development frameworks.
Big data has also contributed to machine learning and computer vision. Thanks to big data, Facebook algorithms can now match faces almost as accurately as humans do.
And detractors have overlooked big data’s role in the proliferation of computational design, data journalism and new forms of artistic expression. Computational artists, journalists and designers—the kinds of people who congregate at meetings like Eyeo—are using huge sets of data to give us online experiences that are unlike anything we experienced in paper. If we step away from hypothesis testing, we find that big data has made big contributions.
The second mistake critics often make is to confuse the limitations of prototypes with fatal flaws. This is something I have experienced often. For example, in Place Pulse—a project I created with my team the M.I.T. Media Lab—we used Google Street View images and crowdsourced visual surveys to map people’s perception of a city’s safety and wealth. The original method was rife with limitations that we dutifully acknowledged in our paper. Google Street View images are taken at arbitrary times of the day and showed cities from the perspective of a car. City boundaries were also arbitrary. To overcome these limitations, however, we needed a first data set. Producing that first limited version of Place Pulse was a necessary part of the process of making a working prototype.
A year has passed since we published Place Pulse’s first data set. Now, thanks to our focus on “making,” we have computer vision and machine-learning algorithms that we can use to correct for some of these easy-to-spot distortions. Making is allowing us to correct for time of the day and dynamically define urban boundaries. Also, we are collecting new data to extend the method to new geographical boundaries.
Those who fail to understand that the process of making is iterative are in danger of being too quick to condemn promising technologies. In 1920 the New York Times published a prediction that a rocket would never be able to leave atmosphere. Similarly erroneous predictions were made about the car or, more recently, about iPhone’s market share. In 1969 the Times had to publish a retraction of their 1920 claim. What similar retractions will need to be published in the year 2069?
Finally, the doubters have relied too heavily on secondary sources. For instance, they made a piñata out of the 2008 Wired piece by Chris Anderson framing big data as “the end of theory.” Others have criticized projects for claims that their creators never made. A couple of weeks ago, for example, Gary Marcus and Ernest Davis published a piece on big data in the Times. There they wrote about another of one of my group’s projects, Pantheon, which is an effort to collect, visualize and analyze data on historical cultural production. Marcus and Davis wrote that Pantheon “suggests a misleading degree of scientific precision.” As an author of the project, I have been unable to find where I made such a claim. Pantheon’s method section clearly states that: “Pantheon will always be—by construction—an incomplete resource.” That same section contains a long list of limitations and caveats as well as the statement that “we interpret this data set narrowly, as the view of global cultural production that emerges from the multilingual expression of historical figures in Wikipedia as of May 2013.”
Bickering is easy, but it is not of much help. So I invite the critics of big data to lead by example. Stop writing op–eds and start developing tools that improve on the state of the art. They are much appreciated. What we need are projects that are worth imitating and that we can build on, not obvious advice such as “correlation does not imply causation.” After all, true progress is not something that is written, but made.”