How do you tackle the world’s most complex socio-economic problems at a time of big data? It is widely recognized today that using data can greatly improve decision-making, optimize operations, and lead to new insights to address increasingly complex problems such as migration, obesity, urbanization, climate change amongst others.
When it comes to data science, however, the private sector leads the way. Not only do companies typically own and control access to vast troves of data, but they also typically possess the leading talent in the field. A central question for those concerned with the public good in our times is: How can governments, public agencies, nonprofits and other philanthropic organizations take advantage of the proliferation of data—and the potential of data science–to better serve their own needs and goals?
At the EFC’s 2017 Annual General Assembly and Conference which focused on“Courage to re-embrace solidarity in Europe –Can philanthropy take the lead?” in Warsaw last month, we both spoke at a session that tried to answer this question. The session “Data Science at the service of Philanthropy” was wonderfully chaired by David Gutelius (The Data Guild) and curated by Ciro Cattuto (ISI Foundation) with support from the Fondazione CRT, Compagnia di San Paolo, Fondazione Cariplo and Fondazione ISI. We were joined by Joanna Macrae (GiveDirectly) and Juan Mateos-Garcia (NESTA).
Our two presentations were based on our Data Collaboratives initiative, which seeks to improve children’s lives through the exchange of data and expertise across sectors.
What’s the value of Data Collaboratives?
Sharing corporate data for the social good is an emerging phenomenon – often called data philanthropy. The Govlab’s Data Collaboratives Explorer has documented over 100 cases where the exchange of corporate data sought to create public value. Case studies contained within the Explorer show that data can be used, among other goals, to enhance:
- Situational Awareness and Response, leading to a greater understanding and ability to track conditions on the ground to improve interventions. For example, The World Bank and Orbital Insights are using satellite imagery data to track global poverty.
- Public Service Design and Delivery, for instance by enhancing access to previously inaccessible datasets to enable more accurate modeling of public service design and delivery. The TrafficJam Challenge, for example, made transit data available to spark the development of data-driven solutions to Toronto’s commuting troubles.
- Knowledge Creation and Transfer, in some cases by bringing more diverse datasets to bear to fill knowledge gaps and ensure that the most useful information for solving a problem is at hand. For example, the Digital Ecologies Research Partnership is sharing public user data with academic institutions to support research on Internet social behavior.
- Prediction and Forecasting, sometimes through new predictive capabilities to help institutions be more proactive, putting in place mechanisms based on sound evidence that mitigate problems or avert crises before they occur. IBM researchers at Green Horizons, for example, are using government air quality data to predict how pollution spreads throughout the city of Beijing.
- Impact Assessment and Evaluation, often by improving access to additional datasets tohelp institutions monitor and evaluate the real-world impacts of policies. For instance, Researchers at the University of Twente were given access to millions of tweets to evaluate the effectiveness of cancer early detection campaigns on social media.
Using Data Collaboratives to Improve Children’s Lives
The problems we seek to address within the UNICEF/GovLab Data Collaboratives cover a wide range of complex issues. For example:
- Suicide is the second highest cause of death among young people aged 15-24 in India, accounting for about 60,000 deaths in 2013. To better understand this growing phenomenon, data scientists from the ISI Foundation in Italy and Microsoft Research in Israel are exploring how different kinds of search queries online could be used as proxies for broader insights and more informed interventions on the ground.
- Researchers from Telefonica in Santiago, Chile, are looking at data from the use of cellphones to better understand how people move in megacities. As cities continue to expand, the poor have to travel greater distances to work, study, and live. Insights from this research can be used to advocate with transport authorities for regulations, policies and programs that increase the safety of children and women.
- Similar data, along with satellite imagery, can also help identify the needs of millions of refugees in the border between Syria and Jordan. Since humanitarian access to those areas is limited, this kind of data would allow for the ability to track the distribution of aid and monitor the movement of populations dispersed throughout the country in a more strategic way.
- Data science can also be used to mine publicly available data. Researchers from the ISI Foundation are scraping social media sites and online forums to help advocacy campaigns that seek to reverse the increase in C-sections in Brazil. The number of C-sections grew from 15% in the 1970’s to 56% today. In private hospitals, that number can be as high as 90%. Improved visibility of public attitudes towards natural births would enable UNICEF and partners to better target public engagement actions.
Complex problems affecting children are universal in nature and childhood obesity is a case in point. In Scotland, more than 210,000 children currently live in poverty in Scotland, and 28% are overweight or obese. Data Collaboratives are being set up in Scotland with a wide range of partners to look at food production, access, consumption, advertisement as well as access to green spaces for exercising. These problems cannot be fully addressed by one organization alone, but by connecting the dots across a range of them – from supermarkets to school meal programs.
Data collaboratives = #Data4Solidarity
The theme of the EFC’s annual conference focused on solidarity (#Courage4Solidarity) – a theme well aligned with the Data Collaboratives initiative. “Solidarity’ refers to the “unity or agreement of feeling or action, especially among individuals with a common interest; mutual support within a group.” The Data Collaboratives initiative is also about matching problems with potential problem-solvers in the form of data and expertise, united with a single purpose: using the latest technologies to do some good in the world.