Helsinki invites cyclists to collect data on street conditions and earn money


Article at the Mayor.eu: “From Saturday 10 July, cyclists in Helsinki will be able to earn money doing what they love whilst simultaneously helping the municipality repair damaged streets. This was announced on 28 June when the City of Helsinki shared that all residents are invited to take part in a game to map out 300 kilometres of cycling paths in the capital.

In a press release, the City of Helsinki reports that anyone can participate as long as they have a bicycle and a smartphone. To take part, one must simply download the free application Crowdchupa and attach their phone to their bicycle. The device will then record footage of the streets and Artificial Intelligence will be used to identify damage that must be repaired.

To make this even more interesting, the Crowdchupa application will allow participants to earn money. The application features a map which depicts various objects (such as coins and berries) on the streets. Cyclists must drive over these virtual objects to collect them and earn money….(More)”.

New Study Uses Crowdsourcing to Strengthen American Democracy


Press Release: “Americans have always disagreed about politics, but now levels of anti-democratic attitudes, support for partisan violence, and partisan animosity have reached concerning levels. While there are many ideas for tackling these problems, they have never been gathered, tested, and evaluated in a unified effort. To address this gap, the Stanford Polarization and Social Change Lab is launching a major new initiative. The Strengthening Democracy Challenge will collect and rigorously test up to 25 interventions to reduce anti-democratic attitudes, support for partisan violence, and partisan animosity in one massive online experiment with up to 30,000 participants. Interventions can be contributed by academics, practitioners, or others with interest in strengthening democratic principles in the US. The researchers who organize the challenge — a multidisciplinary team with members at Stanford, MIT, Northwestern, and Columbia Universities — believe that crowdsourcing ideas, combined with the rigor of large-scale experimentation, can help address issues as substantial and complex as these….

Researchers with diverse backgrounds and perspectives are invited to submit interventions. The proposed interventions must be short, doable in an online form, and follow the ethical guidelines of the challenge. Academic and practitioner experts will rate the submissions and an editorial board will narrow down the 25 best submissions to be tested, taking novelty and expected success of the ideas into account. Co-organizers of the challenge include James Druckman, Payson S. Wild Professor of Political Science at Northwestern University; David Rand, the Erwin H. Schell Professor and Professor of Management Science and Brain and Cognitive Sciences at MIT; James Chu, Assistant Professor of Sociology at Columbia University; and Nick Stagnaro, Post-Doctoral Fellow at MIT. The organizing team is supported by Polarization and Social Change Lab’s Chrystal RedekoppJoe Mernyk, and Sophia Pink.

The study participants will be a large sample of up to 30,000 self-identified Republicans and Democrats, nationally representative on several major demographic benchmarks….(More)”.

Understanding crowdsourcing projects: A review on the key design elements of a crowdsourcing initiative


Paper by Rea Karachiwalla and Felix Pinkow: “Crowdsourcing has gained considerable traction over the past decade and has emerged as a powerful tool in the innovation process of organizations. Given its growing significance in practice, a profound understanding of the concept is crucial. The goal of this study is to develop a comprehensive understanding of designing crowdsourcing projects for innovation by identifying and analyzing critical design elements of crowdsourcing contests. Through synthesizing the principles of the social exchange theory and absorptive capacity, this study provides a novel conceptual configuration that accounts for both the attraction of solvers and the ability of the crowdsourcer to capture value from crowdsourcing contests. Therefore, this paper adopts a morphological approach to structure the four dimensions, namely, (i) task, (ii) crowd, (iii) platform and (iv) crowdsourcer, into a conceptual framework to present an integrated overview of the various crowdsourcing design options. The morphological analysis allows the possibility of identifying relevant interdependencies between design elements, based on the goals of the problem to be crowdsourced. In doing so, the paper aims to enrich the extant literature by providing a comprehensive overview of crowdsourcing and to serve as a blueprint for practitioners to make more informed decisions when designing and executing crowdsourcing projects….(More)”.

Spies Like Us: The Promise and Peril of Crowdsourced Intelligence


Book Review by Amy Zegart of “We Are Bellingcat: Global Crime, Online Sleuths, and the Bold Future of News” by Eliot Higgins: “On January 6, throngs of supporters of U.S. President Donald Trump rampaged through the U.S. Capitol in an attempt to derail Congress’s certification of the 2020 presidential election results. The mob threatened lawmakers, destroyed property, and injured more than 100 police officers; five people, including one officer, died in circumstances surrounding the assault. It was the first attack on the Capitol since the War of 1812 and the first violent transfer of presidential power in American history.

Only a handful of the rioters were arrested immediately. Most simply left the Capitol complex and disappeared into the streets of Washington. But they did not get away for long. It turns out that the insurrectionists were fond of taking selfies. Many of them posted photos and videos documenting their role in the assault on Facebook, Instagram, Parler, and other social media platforms. Some even earned money live-streaming the event and chatting with extremist fans on a site called DLive. 

Amateur sleuths immediately took to Twitter, self-organizing to help law enforcement agencies identify and charge the rioters. Their investigation was impromptu, not orchestrated, and open to anyone, not just experts. Participants didn’t need a badge or a security clearance—just an Internet connection….(More)”.

Innovating Public Service Delivery Through Crowdsourcing: What Role for The Third Sector and Civil Society?


Paper by Nathalie Colasanti, Chiara Fantauzzi, and Rocco Frondizi: “The purpose of this paper is to study the involvement of the “crowd” in designing innovative public policies, and the possibility for the Third Sector to play a role in this process. To do so, we want to answer the following research question: what is the extent to which crowdsourcing is adopted in financing and delivering public services within New Public Governance arenas? In order to answer it, we employ the following approach. First of all, we will set public innovation into the context of New Public Governance; secondly, we will analyse definitions for crowdsourcing, and thirdly, we will provide an overview and crisis of crowdsourcing examples to demonstrate their significance as novel forms of public service finance and delivery. This approach evidences the potential and the outcomes of applying crowdsourcing in the public sector, and indicates the role of the actors involved: the adoption of a leadership role by the Third Sector could facilitate crowdsourcing processes. The outcome of the application of crowdsourcing in the public sector is a greater involvement of the civil society in its relationship with the State….(More)”.

Crowdsourcing: Citizens as coproducers of public services


Paper by Helen K. Liu: “Crowdsourcing serves as a distributed problem‐solving production model for modern governments, and it has the potential to transform citizens into coproducers of public services. To consolidate the theoretical basis, this article provides a typology for crowdsourcing public services based on theories of coproduction, public sector volunteerism, and government–citizen relations. This typology includes two dimensions—the policy stage, and the functionality of citizens’ effort—and four types of crowdsourcing, namely, complementary crowdsourcing in service implementation, supplementary crowdsourcing in service implementation, complementary crowdsourcing in policy and service design, and supplementary crowdsourcing in policy design. Four cases are selected for illustration. Designing crowdsourcing based on citizen and government relationships will help designers align goals and tasks to the right coproducers and enhance relationships in a democratic way. Furthermore, this typology will allow the field to systematically and collectively build knowledge….(More)”.

How spooks are turning to superforecasting in the Cosmic Bazaar


The Economist: “Every morning for the past year, a group of British civil servants, diplomats, police officers and spies have woken up, logged onto a slick website and offered their best guess as to whether China will invade Taiwan by a particular date. Or whether Arctic sea ice will retrench by a certain amount. Or how far covid-19 infection rates will fall. These imponderables are part of Cosmic Bazaar, a forecasting tournament created by the British government to improve its intelligence analysis.

Since the website was launched in April 2020, more than 10,000 forecasts have been made by 1,300 forecasters, from 41 government departments and several allied countries. The site has around 200 regular forecasters, who must use only publicly available information to tackle the 30-40 questions that are live at any time. Cosmic Bazaar represents the gamification of intelligence. Users are ranked by a single, brutally simple measure: the accuracy of their predictions.

Forecasting tournaments like Cosmic Bazaar draw on a handful of basic ideas. One of them, as seen in this case, is the “wisdom of crowds”, a concept first illustrated by Francis Galton, a statistician, in 1907. Galton observed that in a contest to estimate the weight of an ox at a county fair, the median guess of nearly 800 people was accurate within 1% of the true figure.

Crowdsourcing, as this idea is now called, has been augmented by more recent research into whether and how people make good judgments. Experiments by Philip Tetlock of the University of Pennsylvania, and others, show that experts’ predictions are often no better than chance. Yet some people, dubbed “superforecasters”, often do make accurate predictions, largely because of the way they form judgments—such as having a commitment to revising predictions in light of new data, and being aware of typical human biases. Dr Tetlock’s ideas received publicity last year when Dominic Cummings, then an adviser to Boris Johnson, Britain’s prime minister, endorsed his book and hired a controversial superforecaster to work at Mr Johnson’s office in Downing Street….(More)”.

As Jakarta floods again, humanitarian chatbots on social media support community-led disaster response


Blog by Petabencana: “On February 20th, #banjir and #JakartaBanjir were the highest trending topics on Twitter Indonesia, as the capital city was inundated for the third major time this year, following particularly heavy rainfall from Friday night (19/2/2021) to Saturday morning (20/02/2021). As Jakarta residents turned to social media to share updates about the flood, they were greeted by “Disaster Bot” – a novel AI-assisted chatbot that monitors social media for posts about disasters and automatically invites users to submit more detailed disaster reports. These crowd-sourced reports are used to map disasters in real-time, on a free and open source website, PetaBencana.id.

As flooding blocked major thoroughfares and toll roads, disrupted commuter lines, and cut off electricity to over 60,000 homes, residents continued to share updates about the flood situation in order to stay alert and make timely decisions about safety and response. Hundreds of residents submitted flood reports to PetaBencana.id, alerting each other about water levels, broken infrastructures and road accessibility. The Jakarta Emergency Management Agency also updated the map with official information about flood affected  areas, and monitored the map to respond to resident needs. PetaBencana.id experienced a 2000% in activity in under 12 hours as residents actively checked the map to understand the flooding situation, avoid flooded areas, and make decisions about safety and response. 

Residents share updates about flood-affected road access through the open source information sharing platform, PetaBencana.id. Thousands of residents used the map to navigate safely as heavy rainfall inundated the city for the third major time this year.

As flooding incidents continue to occur with increasing intensity across the country, community-led information sharing is once again proving its significance in supporting response and planning at multiple scales. …(More)”.

These crowdsourced maps will show exactly where surveillance cameras are watching


Mark Sullivan at FastCompany: “Amnesty International is producing a map of all the places in New York City where surveillance cameras are scanning residents’ faces.

The project will enlist volunteers to use their smartphones to identify, photograph, and locate government-owned surveillance cameras capable of shooting video that could be matched against people’s faces in a database through AI-powered facial recognition.

The map that will eventually result is meant to give New Yorkers the power of information against an invasive technology the usage of which and purpose is often not fully disclosed to the public. It’s also meant to put pressure on the New York City Council to write and pass a law restricting or banning it. Other U.S. cities, such as Boston, Portland, and San Francisco, have already passed such laws.

Facial recognition technology can be developed by scraping millions of images from social media profiles and driver’s licenses without people’s consent, Amnesty says. Software from companies like Clearview AI can then use computer vision algorithms to match those images against facial images captured by closed-circuit television (CCTV) or other video surveillance cameras and stored in a database.

Starting in May, volunteers will be able to use a software tool to identify all the facial recognition cameras within their view—like at an intersection where numerous cameras can often be found. The tool, which runs on a phone’s browser, lets users place a square around any cameras they see. The software integrates Google Street View and Google Earth to help volunteers label and attach geolocation data to the cameras they spot.

The map is part of a larger campaign called “Ban the Scan” that’s meant to educate people around the world on the civil rights dangers of facial recognition. Research has shown that facial recognition systems aren’t as accurate when it comes to analyzing dark-skinned faces, putting Black people at risk of being misidentified. Even when accurate, the technology exacerbates systemic racism because it is disproportionately used to identify people of color, who are already subject to discrimination by law enforcement officials. The campaign is sponsored by Amnesty in partnership with a number of other tech advocacy, privacy, and civil liberties groups.

In the initial phase of the project, which was announced last Thursday, Amnesty and its partners launched a website that New Yorkers can use to generate public comments on the New York Police Department’s (NYPD’s) use of facial recognition….(More)”.

Twitter’s misinformation problem is much bigger than Trump. The crowd may help solve it.


Elizabeth Dwoskin at the Washington Post: “A pilot program called Birdwatch lets selected users write corrections and fact checks on potentially misleading tweets…

The presidential election is over, but the fight against misinformation continues.

The latest volley in that effort comes from Twitter, which on MondayannouncedBirdwatch, a pilot project that uses crowdsourcing techniques to combat falsehoods and misleading statements on its service.

The pilot, which is open to only about 1,000 select users who can apply to be contributors, will allow people to write notes with corrections and accurate information directly into misleading tweets — a method that has the potential to get quality information to people more quickly than traditional fact-checking. Fact checks that are rated by other contributors as high quality may get bumped up or rewarded with greater visibility.

Birdwatch represents Twitter’s most experimental response to one of the biggest lessons that social media companies drew from the historic events of 2020: that their existing efforts to combat misinformation — including labeling, fact-checking and sometimes removing content — were not enough to prevent falsehoods about a stolen election or the coronavirus from reaching and influencing broad swaths of the population. Researchers who studied enforcement actions by social media companies last year found that fact checks and labels are usually implemented too late, after a post or a tweet has gone viral.

The Birdwatch project — which for the duration of the pilot will function as a separate website — is novel in that it attempts to build new mechanisms into Twitter’s product that foreground fact-checking by its community of 187 million daily users worldwide. Rather than having to comb through replies to tweets to sift through what’s true or false — or having Twitter employees append to a tweet a label providing additional context — users will be able to click on a separate notes folder attached to a tweet where they can see the consensus-driven responses from the community. Twitter will have a team reviewing winning responses to prevent manipulation, though a major question is whether any part of the process will be automated and therefore more easily gamed….(More)”