Charting the ‘Data for Good’ Landscape

Curated on Posted on by Stefaan Verhulst

Report by Jake Porway at Data.org: “There is huge potential for data science and AI to play a productive role in advancing social impact. However, the field of “data for good” is not only overshadowed by the public conversations about the risks rampant data misuse can pose to civil society, it is also a fractured and disconnected space. There are a myriad of different interpretations of what it means to “use data for good” or “use AI for good”, which creates duplicate efforts, nonstrategic initiatives, and confusion about what a successfully data-driven social sector could look like. To add to that, funding is scarce for a field that requires expensive tools and skills to do well. These enduring challenges result in work being done at an activity and project level, but do not create a coherent set of building blocks to constitute a strong and healthy field that is capable of solving a new class of systems-level problems.

We are taking one tiny step forward in trying to make a more coherent Data for Good space with a landscape that makes clear what various Data for Good initiatives (and AI for Good initiatives) are trying to achieve, how they do it, and what makes them similar or different from one another. One of the major confusion points in talking about “Data for Good” is that it treats all efforts as similar by the mere fact that they use “data” and seek to do something “good”. This term is so broad as to be practically meaningless; as unhelpful as saying “Wood for Good”. We would laugh at a term as vague as “Wood for Good”, which would lump together activities as different as building houses to burning wood in cook stoves to making paper, combining architecture with carpentry, forestry with fuel. However, we are content to say “Data for Good”, and its related phrases “we need to use our data better” or “we need to be data-driven”, when data is arguably even more general than something like wood.

We are trying to bring clarity to the conversation by going beyond mapping organizations into arbitrary groups, to define the dimensions of what it means to do data for good. By creating an ontology for what Data for Good initiatives seek to achieve, in which sector, and by what means, we can gain a better understanding of the underlying fundamentals of using data for good, as well as creating a landscape of what initiatives are doing.

We hope that this landscape of initiatives will help to bring some more nuance and clarity to the field, as well as identify which initiatives are out there and what purpose they serve. Specifically, we hope this landscape will help:

  • Data for Good field practitioners align on a shared language for the outcomes, activities, and aims of the field.
  • Purpose-driven organizations who are interested in applying data and computing to their missions better understand what they might need and who they might go to to get it.
  • Funders make more strategic decisions about funding in the data/AI space based on activities that align with their interests and the amount of funding already devoted to that area.
  • Organizations with Data for Good initiatives can find one another and collaborate based on similarity of mission and activities.

Below you will find a very preliminary landscape map, along with a description of the different kinds of groups in the Data for Good ecosystem and why you might need to engage with them….(More)”.

Repository of Behavioral Interventions in Latin America and the Caribbean

Curated on Posted on by Stefaan Verhulst

Inter-American Development Bank (IDB): “How do you keep people from gathering with friends and family during a pandemic? How do you improve school attendance among preschoolers? How do you make sure taxpayers pay their fair share? These are some of the questions researchers seek to solve so countries can continue to grow and prosper. Many issues come down to human behavior and how the right policy tools can nudge people into doing things that will benefit themselves and society. A new repository collects these tools and the lessons learned from behavioral interventions in Latin America and the Caribbean, making them available for policymakers across the region and beyond.

For nearly a decade, the Inter-American Development Bank (IDB) has been working with local and national governments in the region to advance knowledge and expertise on individual and collective decision-making. The goal is to address biases that guide people’s behavior in detrimental ways. By designing strategies to correct them, we can help people make wiser choices in areas that range from education and savings to health, tax compliance, and labor markets….

To collect our findings and make the lessons we learned over the years available to policymakers and researchers, we recently created the largest online repository of quantitative behavioral economics field experiments conducted in Latin America and the Caribbean. The repository is aimed specifically at policymakers and is available in Spanish and English….(More)”.

Could Trade Agreements Help Address the Wicked Problem of Cross-Border Disinformation?

Curated on Posted on by Stefaan Verhulst

Essay by Susan Ariel Aaronson: “Whether produced domestically or internationally, disinformation is a “wicked” problem that has global impacts. Although trade agreements contain measures that address cross-border disinformation, domestically created disinformation remains out of their reach. This paper looks at how policy makers can use trade agreements to mitigate disinformation and spam while implementing financial and trade sanctions against entities and countries that engage in disseminating cross-border disinformation. Developed and developing countries will need to work together to solve this global problem….(More)”.

A New Tool Shows How Google Results Vary Around the World

Curated on Posted on by Stefaan Verhulst

Article by Tom Simonite: “Google’s claim to “organize the world’s information and make it universally accessible and useful” has earned it an aura of objectivity. Its dominance in search, and the disappearance of most competitors, make its lists of links appear still more canonical. An experimental new interface for  Google Search aims to remove that mantle of neutrality.

Search Atlas makes it easy to see how Google offers different responses to the same query on versions of its search engine offered in different parts of the world. The research project reveals how Google’s service can reflect or amplify cultural differences or government preferences—such as whether Beijing’s Tiananmen Square should be seen first as a sunny tourist attraction or the site of a lethal military crackdown on protesters.

Divergent results like that show how the idea of search engines as neutral is a myth, says Rodrigo Ochigame, a PhD student in science, technology, and society at MIT and cocreator of Search Atlas. “Any attempt to quantify relevance necessarily encodes moral and political priorities,” Ochigame says.

Ochigame built Search Atlas with Katherine Ye, a computer science PhD student at Carnegie Mellon University and a research fellow at the nonprofit Center for Arts, Design, and Social Research.

Just like Google’s homepage, the main feature of Search Atlas is a blank box. But instead of returning a single column of results, the site displays three lists of links, from different geographic versions of Google Search selected from the more than 100 the company offers. Search Atlas automatically translates a query to the default languages of each localized edition using Google Translate.

Ochigame and Ye say the design reveals “information borders” created by the way Google’s search technology ranks web pages, presenting different slices of reality to people in different locations or using different languages.

When they used their tool to do an image search on “Tiananmen Square,” the UK and Singaporean versions of Google returned images of tanks and soldiers quashing the 1989 student protests. When the same query was sent to a version of Google tuned for searches from China, which can be accessed by circumventing the country’s Great Firewall, the results showed recent, sunny images of the square, smattered with tourists.

Google’s search engine has been blocked in China since 2010, when the company said it would stop censoring topics the government deemed sensitive, such as the Tiananmen massacre. Search Atlas suggests that the China edition of the company’s search engine can reflect the Chinese government’s preferences all the same. That pattern could result in part from how the corpus of web pages from any language or region would reflect cultural priorities and pressures….(More)”

Search Atlas graph showing different search results
An experimental interface for Google Search found that it offered very different views of Beijing’s Tiananmen Square to searchers from the UK (left), Singapore (center), and China. COURTESY OF SEARCH ATLAS

Policy Impacts

Curated on Posted on by Stefaan Verhulst

About: “Over the past 50 years, researchers have made great strides in analyzing public policy. With better data and improved research methods, we know more than ever about the impacts of government spending.

But despite these advances, it remains surprisingly challenging to answer basic questions about which policies have been most effective.

The difficulty arises because methods for evaluating policy effectiveness are not standardized. This makes it challenging, if not impossible, to compare and contrast across different policies.

Policy Impacts seeks to promote a unified approach for policy evaluation. We seek to promote the Marginal Value of Public Funds, a standardized metric for policy evaluation. We have created the Policy Impacts library, a collaborative effort to track the returns to a wide range of government policies…(More).

Guide on Geospatial Data Integration in Official Statistics

Curated on Posted on by Stefaan Verhulst

Report by PARIS21: “National geospatial integration agencies can provide detailed, timely and relevant data about people, businesses, buildings, infrastructures, agriculture, natural resources and anthropogenic impacts on the biosphere. There is a clear benefit to integrating geospatial data into traditional national statistical systems. Together they provide a very clear picture of the social, economic and environmental issues that underpin sustainable development and allow for more informed policy making. But the question is where to start?

geospatial data integration

This new PARIS21 publication provides a practical guide, based on five principles for national statistics offices to form stronger partnerships with national geospatial integration agencies….(More)”.

Why don’t they ask us? The role of communities in levelling up

Curated on Posted on by Stefaan Verhulst

Report by the Institute of Community Studies: “We are delighted to unveil a landmark research report, Why don’t they ask us? The role of communities in levelling up. The new report reveals that current approaches to regeneration and economic transformation are not working for the majority of local communities and their economies.

Its key findings are that:

  • Interventions have consistently failed to address the most deprived communities, contributing to a 0% average change in the relative spatial deprivation of the most deprived local authorities areas;
  • The majority of ‘macro funds’ and economic interventions over the last two decades have not involved communities in a meaningful nor sustainable way;
  • The focus of interventions to build local economic resilience typically concentrate on a relatively small number of approaches, which risks missing crucial dimensions of local need, opportunity and agency, and reinforcing gaps between the national and the hyper-local;
  • Interventions have tended to concentrate on ‘between-place’ spatial disparities in economic growth at the expense of ‘within-place’ inequalities that exist inside local authority boundaries, which is where the economic strength or weakness of a place is most keenly felt by communities.
  • Where funds and interventions have had higher levels of community involvement, these have typically been disconnected from the structures where decisions are taken, undermining their aim of building community power into local economic solutions…(More)”.

Closing the Data Gap: How Cities Are Delivering Better Results for Residents

Curated on Posted on by Stefaan Verhulst

Report by The Monitor Institute by Deloitte: “Better services. Smarter and more efficient use of tax dollars. Greater transparency and civic engagement. These are the results from the data-driven transformation in city halls across the country. The movement that began in just a handful of cities six years ago has now spread far and wide. Hundreds of cities, both large and small and in every region of the country, have embraced a new approach to local governance. Moving beyond old practices based on precedent or instinct, city leaders and staff are instead using data to make more effective operational, programmatic, and policy decisions. And residents are reaping real benefits, from improved services to greater visibility into how their local government works…

  • Performance management: The percentage of cities monitoring and analyzing their progress toward key goals has more than doubled (from 30% to 75%)
  • Public engagement: The percentage of cities engaging with residents on a goal and communicating progress has more than tripled (from 19% to 70%)
  • Releasing data: The percentage of cities with a platform and process to release data to residents has more than tripled (from 18% to 67%)
  • Taking action: The percentage of cities modifying existing programs based on data analytics has more than doubled (from 28% to 61%).

The results: greater transparency around how and why decisions are made, more effective and efficient operations, and improved services. For example, 60% of city officials surveyed in the WWC network reported improved emergency response times, and 70% reported that their cities are systematically using data-informed decision-making to respond to the COVID-19 crisis. More than half of survey respondents also reported improving their use of data to make budget decisions, award city contracts and/or shift procurement dollars, and deliver city services more efficiently, effectively, and/or equitably.

This kind of progress builds residents’ trust in government, produces better outcomes, and reflects the broad culture shift underway in city governments across the country — demonstrating that an evidence-informed approach is possible for all U.S. cities. Today, more than 250 municipal governments across the country are changing how they do business and tackling local challenges by putting into place critical data infrastructure and/or improving data skills….(More)”.

Sovereignty and Data Localization

Curated on Posted on by Stefaan Verhulst

Paper by Emily Wu: “Data localization policies impose obligations on businesses to store and process data locally, rather than in servers located overseas. The adoption of data localization laws has been increasing, driven by the fear that a nation’s sovereignty will be threatened by their inability to exert full control over data stored outside their borders. This is particularly relevant to the US given its dominance in many areas of the digital ecosystem including artificial intelligence and cloud computing.

Unfortunately, data localization policies are causing more harm than good. They are ineffective at improving security, do little to simplify the regulatory landscape, and are causing economic harms to the markets where they are imposed. In order to move away from these policies, the fear of sovereignty dilution must be addressed by alternative means. This will be achieved most effectively by focusing on both technical concerns and value concerns.

To address technical concerns, the US should:

1. Enact a federal national privacy law to reduce the fears that foreign nations have about the power of US tech companies.

2. Mandate privacy and security frameworks by industry to demonstrate the importance that US industry places on privacy and security, recognizing it as fundamental to their business success.

3. Increase investment in cybersecurity to ensure that in a competitive market, the US has the best offering in both customer experience and security assurance

4. Expand multi-lateral agreements under CLOUD Act to help alleviate the concerns that data stored by US companies will be inaccessible to foreign governments in relevant to a criminal investigation…(More)”

Federal Statistical Needs for a National Advanced Industry and Technology Strategy

Curated on Posted on by Stefaan Verhulst

Position paper by Robert D. Atkinson: “With the rise of China and other robust economic competitors, the United States needs a more coherent national advanced technology strategy.1 Effectively crafting and implementing such a strategy requires the right kind of economic data. In part because of years of budget cuts to federal economic data agencies, coupled with a long-standing disregard of the need for sectoral and firm-level economic data to inform an industrial strategy, the federal government is severely lacking in the kinds of data needed.

Notwithstanding the hundreds of millions of dollars spent every year and the thousands of economists working for the federal government, the exact nature of the challenges to U.S. capabilities with regard to the competitiveness of America’s traded sectors is only weakly understood. At least since after the Great Depression, the federal government has never felt the need to develop strategic economic intelligence in order to fully understand the competitive position of its traded sectors or to help support overall economic productivity.2 Rather, most of the focus goes to understanding the ups and downs of the business cycle….

If the U.S. government is going to develop more effective policies to spur competitiveness, growth, and opportunity it will need to support better data collection. It should be able to understand the U.S. competitive position vis-à-vis other nations on key technologies and industries, as well as key strengths and weaknesses and where specific policies are needed.

Better data can also identify weaknesses in U.S. competitiveness that policy can address. For example, in the 1980s, studies conducted as part of the Census of Manufactures (studies that have long been discontinued) found many smaller firms lagging behind badly in costs and quality for reasons including inefficient work organization and obsolete machinery and equipment. End-product manufacturers bought parts and components from many of these smaller enterprises at prices higher than those paid by foreign-based firms with more efficient suppliers, contributing to the cost and quality disadvantages of U.S.-based manufacturers. Legislators heeded the findings in crafting what is now called the Manufacturing Extension Partnership, a program that, if too small in scale to have a significant impact on U.S. manufacturing overall, continues to provide meaningful assistance to thousands of companies each year.5

Moreover, as the federal government institutes more technology and industry policies and programs—as exemplified in the Senate U.S. Innovation and Competition Act—better data will be important to evaluate their effectiveness.

Finally, data are a key 21st century infrastructure. In a decentralized economy, good outcomes are possible only if organizations make good decisions—and that requires data, which, because of its public goods nature, is a quintessential role of government….(More)”.