Facebook will let researchers study how advertisers targeted users with political ads prior to Election Day

Curated on Posted on by Stefaan Verhulst

Nick Statt at The Verge: “Facebook is aiming to improve transparency around political advertising on its platform by opening up more data to independent researchers, including targeting information on more than 1.3 million ads that ran in the three months prior to the US election on November 3rd of last year. Researchers interested in studying the ads can apply for access to the Facebook Open Research and Transparency (FORT) platform here.

The move is significant because Facebook has long resisted willfully allowing access to data around political advertising, often citing user privacy. The company has gone so far as to even disable third-party web plugins, like ProPublica’s Facebook Political Ad Collector tool, that collect such data without Facebook’s express consent.

Numerous research groups around the globe have spent years now studying Facebook’s impact on everything from democratic elections to news dissemination, but sometimes without full access to all the desired data. Only last year, after partnering with Harvard University’s Social Science One (the group overseeing applications for the new political ad targeting initiative), did Facebook better formalize the process of granting anonymized user data for research studies.

In the past, Facebook has made some crucial political ad information in its Ad Library available to the public, including the amount spent on certain ads and demographic information about who saw those ads. But now the company says it wants to do more to improve transparency, specifically around how advertisers target certain subsets of users with political advertising….(More)”.

Sustainable Rescue: data sharing to combat human trafficking

Curated on Posted on by Stefaan Verhulst

Interview with Paul Fockens of  Sustainable Rescue: “Human trafficking still takes place on a large scale, and still too often under the radar. That does not make it easy for organisations that want to combat human trafficking. Sharing of data between various sorts of organisations, including the government, the police, but also banks play a crucial role in mapping the networks of criminals involved in human trafficking, including their victims. Data sharing contributes to tackling this criminal business not only reactively, but also proactively….Sustainable Rescue tries to make the largely invisible human trafficking visible. Bundling data and therefore knowledge is crucial in this. Paul: “It’s about combining the routes criminals (and their victims) take from A to B, the financial transactions they make, the websites they visit, the hotels where they check in et cetera. All those signs of human trafficking can be found in the data of various types of organisations: the police, municipalities, the Public Prosecution Service, charities such as the Salvation Army, but also banks and insurance institutions. The problem here is that you need to collect all pieces of the puzzle to get clear insights from them. As long as this relevant data is not combined through data sharing, it is a very difficult job to get these insights. In nine out of ten cases, these authorities are not willing and/or allowed to share their data, mainly because of the privacy sensitivity of this data. However, in order to eliminate human trafficking, that data will have to be bundled. Only then analyses can be made about the patterns of a network of human trafficking.”…(More)”.

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

Curated on Posted on by Stefaan Verhulst

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)”.

Nowcasting Gentrification Using Airbnb Data

Curated on Posted on by Stefaan Verhulst

Paper by Shomik Jain, Davide Proserpio, Giovanni Quattrone, and Daniele Quercia: “There is a rumbling debate over the impact of gentrification: presumed gentrifiers have been the target of protests and attacks in some cities, while they have been welcome as generators of new jobs and taxes in others. Census data fails to measure neighborhood change in real-time since it is usually updated every ten years. This work shows that Airbnb data can be used to quantify and track neighborhood changes. Specifically, we consider both structured data (e.g. number of listings, number of reviews, listing information) and unstructured data (e.g. user-generated reviews processed with natural language processing and machine learning algorithms) for three major cities, New York City (US), Los Angeles (US), and Greater London (UK). We find that Airbnb data (especially its unstructured part) appears to nowcast neighborhood gentrification, measured as changes in housing affordability and demographics. Overall, our results suggest that user-generated data from online platforms can be used to create socioeconomic indices to complement traditional measures that are less granular, not in real-time, and more costly to obtain….(More)”.

How COVID-19 Is Accelerating the Shift Toward a Quantified Society

Curated on Posted on by Stefaan Verhulst

Essay by Jesse Hirsh: “The COVID-19 pandemic is accelerating global digital transformation and the adoption of digital technologies. It is also enacting a political and cultural shift toward a quantified society: a society in which measurement and predictive modelling dominate (political) decision making, and where surveillance is expansive and pervasive.

While viruses and disease have always been with us, what’s changing is our ability to measure and understand them. This ability comes at a time when globalization (and, by extension, climate change) has transformed the kinds of viruses and diseases we will face.

The knowledge of what can kill us — or is killing us — compels governments and health authorities to both take action in response and gather more data to understand the threat. Like many disasters or other globally impactful events, the COVID-19 pandemic is accelerating the development and implementation of quantification technologies.

Health researchers are now measuring the spread of a virus across the population in ways not previously possible, through the use of a set of data that is ever-growing, especially in countries such as China that have less regard for personal privacy. Canada and the United States are not yet conducting tracking and tracing of infections at a level that would enable containment. This level, however, is due to inadequate staffing rather than insufficient data. Still, the desire for more information remains.

As a result, our ability to measure human health and disease transmission is set to reach new records and capabilities. Through sources ranging from individuals’ use of digital health tools to contact tracing records, health-related data is amassing at a prodigious rate.

What are the impacts or consequences of this dramatic increase in both health data and the perceived value or urgency of that data?…(More)”.

10 Questions That Will Determine the Future of Work

Curated on Posted on by Stefaan Verhulst

Article by Jeffrey Brown and Stefaan Verhulst: “…But in many cases, policymakers face a blizzard of contradictory information and forecasts that can lead to confusion and inaction. Unable to make sense of the torrent of data being thrown their way, policymakers often end up being preoccupied by the answers presented — rather than reflecting on the questions that matter.

If we want to design “good” future-of-work policies, we must have an inclusive and wide-ranging discussion of what we are trying to solve before we attempt to develop and deploy solutions….

We have found that policymakers often fail to ask questions and are often uncertain about the variables that underpin a problem.

In addition, few of the interventions that have been deployed make the best use of data, an emerging but underused asset that is increasingly available as a result of the ongoing digital transformation. If civil society, think tanks and others fail to create the space for a sustainable future-of-work policy to germinate, “solutions” without clearly articulated problems will continue to dictate policy…

Our 100 Questions Initiative seeks to interrupt this cycle of preoccupation with answers by ensuring that policymakers are, first of all, armed with a methodology they can use to ask the right questions and from there, craft the right solutions.

We are now releasing the top 10 questions and are seeking the public’s assistance through voting and providing feedback on whether or not these are really the right questions we should be asking:

Preparing for the Future of Work

  1. How can we determine the value of skills relevant to the future-of work-marketplace, and how can we increase the value of human labor in the 21st century?
  2. What are the economic and social costs and benefits of modernizing worker-support systems and providing social protection for workers of all employment backgrounds, but particularly for women and those in part-time or informal work?
  3. How does the current use of AI affect diversity and equity in the labor force? How can AI be used to increase the participation of underrepresented groups (including women, Black people, Latinx people, and low-income communities)? What aspects/strategies have proved most effective in reducing AI biases?…(More) (See also: https://future-of-work.the100questions.org/)

Data Combination for Problem-solving: A Case of an Open Data Exchange Platform

Curated on Posted on by Stefaan Verhulst

Paper by Teruaki Hayashi et al: “In recent years, rather than enclosing data within a single organization, exchanging and combining data from different domains has become an emerging practice. Many studies have discussed the economic and utility value of data and data exchange, but the characteristics of data that contribute to problem solving through data combination have not been fully understood. In big data and interdisciplinary data combinations, large-scale data with many variables are expected to be used, and value is expected to be created by combining data as much as possible. In this study, we conduct three experiments to investigate the characteristics of data, focusing on the relationships between data combinations and variables in each dataset, using empirical data shared by the local government. The results indicate that even datasets that have a few variables are frequently used to propose solutions for problem solving. Moreover, we found that even if the datasets in the solution do not have common variables, there are some well-established solutions to the problems. The findings of this study shed light on mechanisms behind data combination for problem-solving involving multiple datasets and variables…(More)”.

Silo Busting: The Challenges and Successes of Intergovernmental Data Sharing

Curated on Posted on by Stefaan Verhulst

Report by Jane Wiseman: “Even with the stumbles that have occurred in standing up a national system for sharing pandemic-related health data, it has been far more successful than previous efforts to share data between levels of government—or across government agencies at the same level.

This report offers a rich description of what intergovernmental data sharing can offer by describing a range of federal, state, and local data sharing initiatives in various policy arenas, such as social services, transportation, health, and criminal justice.

The report identifies seven common challenges that serve as barriers to more effective data sharing.  It uses insights developed from the range of case studies to identify key factors for successful intergovernmental data sharing, such as committed leadership, effective processes, and data quality. It then offers a set of recommendations to guide government officials on ways they could undertake data sharing initiatives, along with specific action steps they could take. For example, establishing an “ask once” goal for government data collection in order to reduce burdens on the public and businesses.

We hope this report provides leaders at all levels of government a roadmap that they can use to improve service delivery to the public and businesses, make better decisions about resource allocation in programs, and operate more seamlessly in serving citizens….(More)”.

Connected Devices – an Unfair Competition Law Approach to Data Access Rights of Users

Curated on Posted on by Stefaan Verhulst

Paper by Josef Drexl: “On the European level, promoting the free flow of data and access to data has moved to the forefront of the policy goals concerning the digital economy. A particular aspect of this economy is the advent of connected devices that are increasingly deployed and used in the context of the Internet of Things (IoT). As regards these devices, the Commission has identified the particular problem that the manufacturers may try to remain in control of the data and refuse data access to third parties, thereby impeding the development of innovative business models in secondary data-related markets. To address this issue, this paper discusses potential legislation on data access rights of the users of connected devices. The paper conceives refusals of the device manufacturers to grant access to data vis-à-vis users as a form of unfair trading practice and therefore recommends embedding data access rights of users in the context of the European law against unfair competition. Such access rights would be complementary to other access regimes, including sector-specific data access rights of competitors in secondary markets as well as access rights available under contract and competition law. Against the backdrop of ongoing debates to reform contract and competition law for the purpose of enhancing data access, the paper seeks to draw attention to a so far not explored unfair competition law approach….(More)”.

Data for Good: New Tools to Help Small Businesses and Communities During the COVID-19 Pandemic

Curated on Posted on by Stefaan Verhulst

Blogpost by Laura McGorman and Alex Pompe at Facebook: “Small businesses and people around the world are suffering devastating financial losses due to the ongoing COVID-19 pandemic, and public institutions need real time information to help. Today Facebook is launching new datasets and insights to help support economic recovery through our Data for Good program. 

Researchers estimate that over the next five years, the global economy could suffer over $80 trillion in losses due to COVID-19. Small businesses in particular are being hit hard — our Global State of Small Business Report found that over one in four had closed their doors in 2020. Governments around the world are looking to effectively distribute financial aid as well as accurately forecast when and how economies will recover. These four datasets — Business Activity Trends, Commuting Zones, Economic Insights from the Symptom Survey and the latest Future of Business Survey results — will help researchers, nonprofits and local officials identify which areas and businesses may need the most support.

Business Activity Trends

Many factors influence the pandemic’s impact on local economies around the world. However, real time information on business activity is scarce, leaving institutions seeking to provide economic aid with limited information on how to distribute it. To address these information gaps, we partnered with the University of Bristol to aggregate information from Facebook Business Pages to estimate the change in activity among local businesses around the world and how they respond and recover from crises over time.

UK graph showing average business activity
The above graph shows the drop in Business Page posting on Facebook across cities in the UK the day after the Prime Minister announced lockdown measures. Business Activity Trends can be used to determine how businesses and customers are reacting to local COVID-19 containment policies.

“Determining whether small and medium businesses are open is very important to assess the recovery after events like mandatory stay-at-home orders,” said Dr. Flavia De Luca, Senior Lecturer in Structural and Earthquake Engineering at the University of Bristol. “The traditional way of collecting this information, such as surveys and interviews, are usually costly, time consuming, and do not scale. By using real time information from Facebook, we hope to make it easier for public institutions to better respond to these events.”…(More)”.