Cuebiq’s Data for Good initiative is being continued with support from the Spectus.ai data cleanroom and their Social Impact professionals. Their commitment to positive social impact through the ethical and responsible use of location-based data makes further insights possible. We invite you to visit https://spectus.ai/social-impact/ for more on contributions to academia and research partners.
We had the pleasure of sitting down with Brennan Lake, Cuebiq’s Senior Director of Research Partnerships and Data, to ask him a few questions about Cuebiq’s Data for Good program. Read on to learn about some exciting new Data for Good initiatives he’s working on, as well as how he interfaces with Cuebiq’s Data Science and Engineering teams to effect positive social change.
Can you tell us about your background and how you came to work at Cuebiq?
My background has traditionally been in international relations and international development. I also worked abroad in tech — I went to Argentina and co-founded an e-commerce software-as-a-service startup, which introduced me to the world of tech and SaaS platforms. After that, I moved back to Boston to run an international development NGO, as social-impact oriented work has always been a passion of mine. I worked there and grew that NGO for five years, and then started looking for a new challenge to give me the opportunity to merge my backgrounds at the intersection of tech and social impact work.
In my work at the NGO, we were constantly being told to be more data-driven; but in developing countries, a lot of data collection consists of paper-based surveys in communities that are hard to reach. So, I was really interested in the power of big data and location data to answer sociological questions in these areas at a greater scale. I was also really drawn to the fact that at such an early stage of the company, Cuebiq was already thinking about giving back and creating social value from its data assets.
What is Cuebiq’s Data for Good initiative and how does it work?
Data for Good is our program through which we seek to improve lives through the novel use of location data. We do that in order to provide benefits to the millions of anonymous users who are sharing their location data with us every day. Specifically, we pursue and achieve that mission by supporting academic research and humanitarian initiatives related to mobility. We work with academia and researchers — for example, we’ve done work with MIT Media Lab looking at the impact of economic segregation on the development of urban neighborhoods. We also work with University of Washington and other universities to understand evacuation patterns before, during, and after natural disasters.
Together, we develop research projects where we think our data can make an impact. We seek out projects where the results are actually going to create positive social impact and inform policy.
What is a Data for Good initiative you’ve worked on that’s been particularly rewarding?
We’ve done a lot of work in disaster response in the past. Through working with academia, we’ve used our data to map evacuation patterns and forecast behaviors for future natural disasters. But now we’re starting to build our capabilities in house to process information on evacuations closer to real time, so that we can provide emergency managers and first responders with insights to help them gain mission-critical awareness on the ground. We’re really excited to be building this out with our Data Science and Engineering teams.
Can you tell us about Cuebiq’s partnership with Politecnico di Milano?
Our relationship with Politecnico di Milano developed organically, since a lot of our data scientists and management team came from Politecnico. As a result of this, researchers at the university were able to see what their alumni were graduating to go off and build using Cuebiq data, and recognized the potential value for different research around the world.
In one such project, Cuebiq is collaborating with Politecnico di Milano to assess “transport poverty” in Maputo, using high-precision location data, with the goal of creating more accessible and inclusive transportation systems in Mozambique. This collaboration is part of the Safari Njema project, funded by the Polisocial Award 2018 by Politecnico di Milano.
How do you interface with Data Science and Engineering to make Data for Good a reality?
Data for Good would not be possible without our amazing Data Science and Engineering teams. Specifically, we see in them a really strong ethical imperative and enthusiasm for participating in Data for Good projects, whether it be creating new data sets for specific use cases like mapping evacuations, or figuring out how we can better deliver data for population-sparse areas of the world. These teams are always really proactive about problem-solving, to make sure our partners have the data they need to do research that will deliver a high impact downstream.
Our Data Science and Engineering teams are also developing cutting-edge techniques related to differential privacy in order to better prevent misuse while preserving the data’s utility for aggregate analyses of human mobility.
What has been the most challenging part of building out Cuebiq’s Data for Good program?
We’re a fast-growing startup, so making sure we have the human resources to work on Data for Good initiatives could potentially be a problem. However, we’ve been lucky to have a very dedicated team supporting Data for Good, not only in Data Science and Engineering, but across the board, from the executive team throughout the entire organization. This will only improve as we expand our technical human resources — we’re always looking for new Data Science and Engineering talent who are interested in contributing to these initiatives.
What do you see as the future of Cuebiq’s Data for Good program? How do you anticipate it will grow or change?
I would say I think that Data for Good is most successful when we’re bringing diverse groups of stakeholders to the table, not only on the researcher or Data Science side, but also on the practitioner side. That’s why we’re excited to be working with partners like the World Bank and UNICEF — it takes the work we’ve been doing on the research side and puts it into practice, to help inform policy-making. At the end of the day, the data is most powerful when it’s put in the hands of people on the front lines of these issues.
Interested in working at Cuebiq? If so, be sure to check out our careers page for new job openings.