Leveraging Data Science For Social Change: An Interview with Ken Abante
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Leveraging Data Science For Social Change: An Interview with Ken Abante

If you wish to empower others using data, learning data science is not enough. Engaging in politics is necessary to see the change that you seek. In a recent interview with policy analyst Ken Abante, he discusses how systems change is within our reach if the work that we do with data is driven by the intention to empower the voiceless and powerless.

Interview by Meg Ruiz, Junior Content Designer at Eskwelabs

In this rapidly changing world, Eskwelabs introduces "Skills of the Future," a content category that features interviews and conversations with leading experts in technology, data, education, and business. We believe it is critical to keep up with the latest trends and developments in these areas and understand the skills that will be in high demand in the future of work years.

Ken is a policy researcher, organizer, and a co-founder of WeSolve Foundation, a youth-powered coalition incubator and collaboration accelerator for systems change in the Philippines. His particular areas of interest are public finance, public transportation, and public data.  He trains public servants and has served in positions in government, academe, civil society, and business. Last April, we had the opportunity of discussing with him certain instances where data science played an important role in policymaking.

Can you tell us about your background in Data Science?

I don’t consider myself a data scientist but I consider myself a policy researcher, teacher, and organizer. In my field of policy analysis, one of the things we do is we look at evidence—evidence to achieve a certain public outcome or social outcome.

The core discipline of policy analysis is to look at three angles of policy reform. For a reform to be successful, you have to ask three questions:

  1. Tama ba? Is it technically correct? Is it ethical and equitable? Is it the right thing to do?
  2. Kaya ba? Is there time and budget for it? Is there staff for it? Does the team have the skills to pursue that reform or policy?
  3. This is very important—susuportahan ba? Is there an alignment of powers and decision makers who support the reform? An alignment of political actors? Do the stakeholders who are most affected by the reforms support the policy?

So those are the three basic questions in policy analysis. Data scientists are very good, I think, in two of those angles—tama ba and kaya ba? Political supportability is an angle I think that data scientists can learn from policy analysts. In fact, I appreciate data science as a field but if you really want data for impact you have to engage in politics.

You don't necessarily have to run for public office, but you have to ask yourself, does the change that you seek rearrange existing power dynamics that favor those who are already rich and powerful? Do they empower the people who are most affected by the reforms to claim their rightful place at the negotiating table? So it's very, very important to have that angle in any data-for-impact effort.

My course in college was actually management engineering. For a time I think it was in second year, I wanted to quit the course. On one hand, I was seeing all of these different social issues. On the other hand, I was studying integrals, I was studying balance sheets, I was studying all of these like calculus: What do these equations mean for a person who is hungry now or a person who is suffering or Farmers who have lost their land?

I couldn’t see the connection until my college accounting professor Dr. Darwin Yu guided us in ourservice learning project with the National Children’s Hospital, a public hospital that serves indigent children. We used data to evaluate and give recommendations to their services. I realized that even a “boring” field like accounting can have an impact as long as you use those skills for public service . 

Just because you have data, just because you have the best technical analysis, does not mean you will have the impact that you want. It needs to empower the people who are most affected by the reforms. In WeSolve, we call this data for empowerment.

What other skills should people who want to use data for impact or data empowerment should embody? What other mindset?

I think humility and empathy are important, even more than technical skills. Those who succeed in this field are those who are humble enough to know they cannot do it alone and they're able to build communities with a shared goal and a shared vision. These people are also humble enough to step back, support, and let other people lead. 

Next is empathy for the people who are most affected by whatever policy. It means being able to listen to the real concerns that they raise. Recently, we posted a solidarity statement on the transport strike against the public utility vehicle (PUV) phaseout and in support of a just transition for transport workers under the PUV modernization program . Not all transport workers joined the strike, but people stood in solidarity with the transport workers’ basic concerns. People understood that the strike is the last option for them to air their grievances. The core of the concern was that transport workers are not against modernization, but they want a just transition where no one is left behind. . As people who want to use data for impact, it’s important to understand the political contexts and power dynamics in which our data is collected, analyzed, and used .

What advice would you give to aspiring data professionals or people in the field or just starting their careers and want to create this change?

Just try it. You can explore because there are many organizations where you can volunteer— organizations like Move as One. We have a young mobility leaders program and if you're interested in budgeting, we have a young budget leaders program. We also have a fellowship in WeSolve where we train fellows in this type of policy and systems change work. Join us!

Check out opportunities for impact here: https://wesolve.ph

Ken's story has not only inspired us to use data and our technical skills for social good, but also affirmed that data literacy is a skill for everyone and that anyone has the potential to make a difference. As a community, we are united in our desire to create progressive change—and Ken's example exhibits the growth mindset and perseverance that is needed to achieve this goal. We’ll continue Ken’s interview in our next article to explore more stories from the field that will enable us to use data for positive impact.