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,

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, 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. 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, 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)”.

Collective bargaining on digital platforms and data stewardship

Paper by Astha Kapoor: “… there is a need to think of exploitation on platforms not only through the lens of labour rights but also that of data rights. In the current context, it is impossible to imagine well-being without more agency on the way data are collected, stored and used. It is imperative to envision structures through which worker communities and representatives can be more involved in determining their own data lives on platforms. There is a need to organize and mobilize workers on data rights.

One of the ways in which this can be done is through a mechanism of community data stewards who represent the needs and interests of workers to their platforms, thus negotiating and navigating the data-based decisions. This paper examines the need for data rights as a critical requirement for worker well-being in the platform economy and the ways in which it can be actualized. It argues, given that workers on platforms produce data through collective labour on and off the platform, that worker data are a community resource and should be governed by representatives of workers who can negotiate with platforms on the use of that data for workers and for the public interest. The paper analyses the opportunity for a community data steward mechanism that represents workers’ interests and intermediates on data issues, such as transparency and accountability, with offline support systems. And is also a voice to online action to address some of the injustices of the data economy. Thus, a data steward is a tool through which workers better control their data—consent, privacy and rights—better and organize online. Essentially, it is a way forward for workers to mobilize collective bargaining on data rights.

The paper covers the impact of the COVID-19 pandemic on workers’ rights and well-being. It explores the idea of community data rights on the platform economy and why collective bargaining on data is imperative for any kind of meaningful negotiation with technology companies. The role of a community data steward in reclaiming workers’ power in the platform economy is explained, concluding with policy recommendations for a community data steward structure in the Indian context….(More)”.

Monitoring the R-Citizen in the Time of Coronavirus

Paper by John Flood and Monique Lewis: “The COVID pandemic has overwhelmed many countries in their attempts at tracking and tracing people infected with the disease. Our paper examines how tracking and tracing is done looking at manual and technological means. It raises the issues around efficiency and privacy, etc. The paper investigates more closely the approaches taken by two countries, namely Taiwan and the UK. It shows how tracking and tracing can be handled sensitively and openly compared to the bungled attempts of the UK that have led to the greatest number of dead in Europe. The key messages are that all communications around tracking and tracing need to open, clear, without confusion and delivered by those closest to the communities receiving the messages.This occurred in Taiwan but in the UK the central government chose to close out local government and other local resources. The highly centralised dirigiste approach of the government alienated much of the population who came to distrust government. As local government was later brought into the COVID fold the messaging improved. Taiwan always remained open in its communications, even allowing citizens to participate in improving the technology around COVID. Taiwan learnt from its earlier experiences with SARS, whereas the UK ignored its pandemic planning exercises from earlier years and even experimented with crude ideas of herd immunity by letting the disease rip through the population–an idea soon abandoned.

We also derive a new type of citizen from the pandemic, namely the R citizen. This unfortunate archetype is both a blessing and a curse. If the citizen scores over 1 the disease accelerates and the R citizen is chastised, whereas if the citizen declines to zero it disappears but receives no plaudits for their behaviour. The R citizen can neither exist or die, rather like Schrödinger’s cat. R citizens are of course datafied individuals who are assemblages of data and are treated as distinct from humans. We argue they cannot be so distinguished without rendering them inhuman. This is as much a moral category as it is a scientific one….(More)”.

Mining Twitter Data to Identify Topics of Discussion by Indian Feminist Activists

Brief by the Center on Gender Equity and Health at the University of California at San Diego (UC San Diego): “Over the past decade, social media platforms have become ubiquitous, serving as a democratic space for activism and providing new opportunities for social movements. Twitter has emerged as a popular tool used by feminist activists for spreading awareness and organizing. Research examining feminist movements on social media have highlighted the role of Twitter in emphasizing issues related to gender-based violence (GBV) victimization including the MeToo movement, as well as calling out male privilege and regressive gender norms.

Scholars have examined the high levels of engagement in Twitter discussions and debates by grassroots feminists, as well as the effect of this activity on advancing the feminist agenda in the digital space and amplifying minority voices. Studying Twitter conversations of feminist activists can help identify gender issues that need attention but are underprioritized politically. This brief presents findings from
our analysis of a corpus of tweets by 59 Indian feminist activists, tweeted between March and August 2020. The analysis examines how the feminist community in India has used Twitter as a tool for activism during the COVID-19 pandemic. In addition to providing insights related to mainstream gender issues in India, this analysis hopes to contribute to methodological advancement in gender research….(More)”.

Improved targeting for mobile phone surveys: A public-private data collaboration

Blogpost by Kristen Himelein and Lorna McPherson: “Mobile phone surveys have been rapidly deployed by the World Bank to measure the impact of COVID-19 in nearly 100 countries across the world. Previous posts on this blog have discussed the sampling and  implementation challenges associated with these efforts, and coverage errors are an inherent problem to the approach. The survey methodology literature has shown mobile phone survey respondents in the poorest countries are more likely to be male, urban, wealthier, and more highly educated. This bias can stem from phone ownership, as mobile phone surveys are at best representative of mobile phone owners, a group which, particularly in poor countries, may differ from the overall population; or from differential response rates among these owners, with some groups more or less likely to respond to a call from an unknown number. In this post, we share our experiences in trying to improve representativeness and boost sample sizes for the poor in Papua New Guinea (PNG)….(More)”.

Nudging in Singapore: Current Implementation in Three Key Areas

Paper by Benjamin H. Detenber: “The city state of Singapore has a long history of social engineering efforts, yet only recently have social scientists and civil servants started to use behavioural insights (BI) to create ‘nudges’ and integrate them into the daily lives of citizens. Colloquially known as a nanny state for its extensive social programmes and sometimes heavy-handed approach to guiding social behaviour, Singapore is often regarded favourably by its neighbours in terms of its cleanliness, efficiency, and productivity. Yet how it manages its populace and the restrictions it imposes on unwanted behaviours are sometimes viewed sceptically by others in Asia and the West. Thus, many in the Singapore Civil Service have come to see nudging as a less coercive way to promote social welfare and well-being. This article reviews some of the latest actions in three areas: finance, health, and the environment. In discussing the range of nudging practices, their effectiveness will be assessed and some of the implications for society and individuals will be addressed. To the extent that Singapore can be considered a bellwether or harbinger, its use of nudges may offer a glimpse of what lies ahead for other countries in the region….(More)”.

Inside India’s booming dark data economy

Snigdha Poonam and Samarath Bansal at the Rest of the World: “…The black market for data, as it exists online in India, resembles those for wholesale vegetables or smuggled goods. Customers are encouraged to buy in bulk, and the variety of what’s on offer is mind-boggling: There are databases about parents, cable customers, pregnant women, pizza eaters, mutual funds investors, and almost any niche group one can imagine. A typical database consists of a spreadsheet with row after row of names and key details: Sheila Gupta, 35, lives in Kolkata, runs a travel agency, and owns a BMW; Irfaan Khan, 52, lives in Greater Noida, and has a son who just applied to engineering college. The databases are usually updated every three months (the older one is, the less it is worth), and if you buy several at the same time, you’ll get a discount. Business is always brisk, and transactions are conducted quickly. No one will ask you for your name, let alone inquire why you want the phone numbers of five million people who have applied for bank loans.

There isn’t a reliable estimate of the size of India’s data economy or of how much money it generates annually. Regarding the former, each broker we spoke to had a different guess: One said only about one or two hundred professionals make up the top tier, another that every big Indian city has at least a thousand people trading data. To find them, potential customers need only look for their ads on social media or run searches with industry keywords and hashtags — “data,” “leads,” “database” — combined with detailed information about the kind of data they want and the city they want it from.

Privacy experts believe that the data-brokering industry has existed since the early days of the internet’s arrival in India. “Databases have been bought and sold in India for at least 15 years now. I remember a case from way back in 2006 of leaked employee data from (one of India’s first online job portals) being sold on CDs,” says Nikhil Pahwa, the editor and publisher of MediaNama, which covers technology policy. By 2009, data brokers were running SMS-marketing companies that offered complementary services: procuring targeted data and sending text messages in bulk. Back then, there was simply less data, “and those who had it could sell it at whatever price,” says Himanshu Bhatt, a data broker who claims to be retired. That is no longer the case: “Today, everyone has every kind of data,” he said.

No broker we contacted would openly discuss their methods of hunting, harvesting, and selling data. But the day-to-day work generally consists of following the trails that people leave during their travels around the internet. Brokers trawl data storage websites armed with a digital fishing net. “I was shocked when I was surfing [cloud-hosted data sites] one day and came across Aadhaar cards,” Bhatt remarked, referring to India’s state-issued biometric ID cards. Images of them were available to download in bulk, alongside completed loan applications and salary sheets.

Again, the legal boundaries here are far from clear. Anybody who has ever filled out a form on a coupon website or requested a refund for a movie ticket has effectively entered their information into a database that can be sold without their consent by the company it belongs to. A neighborhood cell phone store can sell demographic information to a political party for hyperlocal campaigning, and a fintech company can stealthily transfer an individual’s details from an astrology app onto its own server, to gauge that person’s creditworthiness. When somebody shares employment history on LinkedIn or contact details on a public directory, brokers can use basic software such as web scrapers to extract that data.

But why bother hacking into a database when you can buy it outright? More often, “brokers will directly approach a bank employee and tell them, ‘I need the high-end database’,” Bhatt said. And as demand for information increases, so, too, does data vulnerability. A 2019 survey found that 69% of Indian companies haven’t set up reliable data security systems; 44% have experienced at least one breach already. “In the past 12 months, we have seen an increasing trend of Indians’ data [appearing] on the dark web,” says Beenu Arora, the CEO of the global cyberintelligence firm Cyble….(More)”.

A New Normal for Data Collection: Using the Power of Community to Tackle Gender Violence Amid COVID-19

Claudia Wells at SDG Knowledge Hub: “A shocking increase in violence against women and girls has been reported in many countries during the COVID-19 pandemic, amounting to what UN Women calls a “shadow pandemic.”

The jarring facts are:

  • Globally 243 million women and girls have been subjected to sexual and/or physical violence by an intimate partner in the past 12 months.
  • The UNFPA estimates that the pandemic will cause a one-third reduction in progress towards ending gender-based violence by 2030;
  • UNFPA predicts an additional 15 million cases of gender-based violence for every three months of lockdown.
  • Official data captures only a fraction of the true prevalence and nature of gender-based violence.

The response to these new challenges were discussed at a meeting in July with a community-led response delivered through local actors highlighted as key. This means that timely, disaggregated, community-level data on the nature and prevalence of gender-based violence has never been more important. Data collected within communities can play a vital role to fill the gaps and ensure that data-informed policies reflect the lived experiences of the most marginalized women and girls.

Community Scorecards: Example from Nepal

Collecting and using community-level data can be challenging, particularly under the restrictions of the pandemic. Working in partnerships is therefore vital if we are to respond quickly and flexibly to new and old challenges.

A great example of this is the Leave No One Behind Partnership, which responds to these challenges while delivering on crucial data and evidence at the community level. This important partnership brings together international civil society organizations with national NGOs, civic platforms and community-based organizations to monitor progress towards the SDGs….

While COVID-19 has highlighted the need for local, community-driven data, public health restrictions have also made it more challenging to collect such data. For example the usual focus group approach to creating a community scorecard is no longer possible.

The coalition in Nepal  therefore faces an increased demand for community-driven data while needing to develop a “new normal for data collection.”. Partners must: make data collection more targeted; consider how data on gender-based violence are included in secondary sources; and map online resources and other forms of data collection.

Addressing these new challenges may include using more blended collection approaches such as  mobile phones or web-based platforms. However, while these may help to facilitate data collection, they come with increased privacy and safeguarding risks that have to be carefully considered to ensure that participants, particularly women and girls, are not at increased risk of violence or have their privacy and confidentiality exposed….(More)”.

Leveraging Telecom Data to Aid Humanitarian Efforts

Data Collaborative Case Study by Michelle Winowatan, Andrew J. Zahuranec, Andrew Young, and Stefaan Verhulst: “Following the 2015 earthquake in Nepal, Flowminder, a data analytics nonprofit, and NCell, a mobile operator in Nepal, formed a data collaborative. Using call detail records (CDR, a type of mobile operator data) provided by NCell, Flowminder estimated the number of people displaced by the earthquake and their location. The result of the analysis was provided to various humanitarian agencies responding to the crisis in Nepal to make humanitarian aid delivery more efficient and targeted.

Data Collaboratives Model: Based on our typology of data collaborative practice areas, the initiative follows the trusted intermediary model of data collaboration, specifically a third-party analytics approach. Third-party analytics projects involve trusted intermediaries — such as Flowminder — who access private-sector data, conduct targeted analysis, and share insights with public or civil sector partners without sharing the underlying data. This approach enables public interest uses of private-sector data while retaining strict access control. It brings outside data expertise that would likely not be available otherwise using direct bilateral collaboration between data holders and users….(More)”.

Blockchain Chicken Farm: And Other Stories of Tech in China’s Countryside

Book by By Xiaowei R. Wang: “In Blockchain Chicken Farm, the technologist and writer Xiaowei Wang explores the political and social entanglements of technology in rural China. Their discoveries force them to challenge the standard idea that rural culture and people are backward, conservative, and intolerant. Instead, they find that rural China has not only adapted to rapid globalization but has actually innovated the technology we all use today. From pork farmers using AI to produce the perfect pig, to disruptive luxury counterfeits and the political intersections of e-commerce villages, Wang unravels the ties between globalization, technology, agriculture, and commerce in unprecedented fashion. Accompanied by humorous “Sinofuturist” recipes that frame meals as they transform under new technology, Blockchain Chicken Farm is an original and probing look into innovation, connectivity, and collaboration in the digitized rural world.

FSG Originals × Logic dissects the way technology functions in everyday lives. The titans of Silicon Valley, for all their utopian imaginings, never really had our best interests at heart: recent threats to democracy, truth, privacy, and safety, as a result of tech’s reckless pursuit of progress, have shown as much. We present an alternate story, one that delights in capturing technology in all its contradictions and innovation, across borders and socioeconomic divisions, from history through the future, beyond platitudes and PR hype, and past doom and gloom. Our collaboration features four brief but provocative forays into the tech industry’s many worlds, and aspires to incite fresh conversations about technology focused on nuanced and accessible explorations of the emerging tools that reorganize and redefine life today….(More)”.