How to use data for good — 5 priorities and a roadmap


Stefaan Verhulst at apolitical: “…While the overarching message emerging from these case studies was promising, several barriers were identified that if not addressed systematically could undermine the potential of data science to address critical public needs and limit the opportunity to scale the practice more broadly.

Below we summarise the five priorities that emerged through the workshop for the field moving forward.

1. Become People-Centric

Much of the data currently used for drawing insights involve or are generated by people.

These insights have the potential to impact people’s lives in many positive and negative ways. Yet, the people and the communities represented in this data are largely absent when practitioners design and develop data for social good initiatives.

To ensure data is a force for positive social transformation (i.e., they address real people’s needs and impact lives in a beneficiary way), we need to experiment with new ways to engage people at the design, implementation, and review stage of data initiatives beyond simply asking for their consent.

(Photo credit: Image from the people-led innovation report)

As we explain in our People-Led Innovation methodology, different segments of people can play multiple roles ranging from co-creation to commenting, reviewing and providing additional datasets.

The key is to ensure their needs are front and center, and that data science for social good initiatives seek to address questions related to real problems that matter to society-at-large (a key concern that led The GovLab to instigate 100 Questions Initiative).

2. Establish Data About the Use of Data (for Social Good)

Many data for social good initiatives remain fledgling.

As currently designed, the field often struggles with translating sound data projects into positive change. As a result, many potential stakeholders—private sector and government “owners” of data as well as public beneficiaries—remain unsure about the value of using data for social good, especially against the background of high risks and transactions costs.

The field needs to overcome such limitations if data insights and its benefits are to spread. For that, we need hard evidence about data’s positive impact. Ironically, the field is held back by an absence of good data on the use of data—a lack of reliable empirical evidence that could guide new initiatives.

The field needs to prioritise developing a far more solid evidence base and “business case” to move data for social good from a good idea to reality.

3. Develop End-to-End Data Initiatives

Too often, data for social good focus on the “data-to-knowledge” pipeline without focusing on how to move “knowledge into action.”

As such, the impact remains limited and many efforts never reach an audience that can actually act upon the insights generated. Without becoming more sophisticated in our efforts to provide end-to-end projects and taking “data from knowledge to action,” the positive impact of data will be limited….

4. Invest in Common Trust and Data Steward Mechanisms 

For data for social good initiatives (including data collaboratives) to flourish and scale, there must be substantial trust between all parties involved; and amongst the public-at-large.

Establishing such a platform of trust requires each actor to invest in developing essential trust mechanisms such as data governance structures, contracts, and dispute resolution methods. Today, designing and establishing these mechanisms take tremendous time, energy, and expertise. These high transaction costs result from the lack of common templates and the need to each time design governance structures from scratch…

5. Build Bridges Across Cultures

As C.P. Snow famously described in his lecture on “Two Cultures and the Scientific Revolution,” we must bridge the “two cultures” of science and humanism if we are to solve the world’s problems….

To implement these five priorities we will need experimentation at the operational but also institutional level. This involves the establishment of “data stewards” within organisations that can accelerate data for social good initiative in a responsible manner integrating the five priorities above….(More)”