From Numbers in the Computer Screen to Mud on your Toes

Even before finishing my PhD I had doubts. I loved science, but somehow academia felt less interesting. For most people, myself included back then, science and academia refer to the same concept. You do science working either on basic research or applied research, which mostly correlates respectively with either creating new knowledge within publicly funded institutions or finding applications of the new knowledge at the private sector. That is it. My neck of the woods was basic research. PhD in solar physics at one of the highest regarded institutions in the world, the Max Planck. The message there was clear: here we make top researchers. I still remember the “Career Day” PowerPoint presentation at one of the retreats where the narrative was that only the best get to stay in academia, while saying that staying in academia is the highest goal for scientists: If Option A wasn’t working, option B was far below in status and not really an option, but something for those failing option A to consider.

When I finished my PhD, I was proud, but I was also uneasy about the normative academic path ahead. I followed the advice of a friend and interviewed at a major consulting firm (McKinsey). Incidentally this was also the time the European Space Agency did the Astronaut Selection and I was part of the selection process. I remember that during the tests and interviews in both cases, my scientific skills were highly regarded, more even than the scientific knowledge. They liked the problem solving and hypothesis attitude, more than knowing the laws of plasma dynamics. I also cold-emailed the three top academic places in the USA I cloud think of. They were not a continuation of my PhD work, but I also realized once I leave academia, I could not come back, so this was my only chance to give it a last shot. I ended up going to one of these, the rocket lab in Washington DC.

I worked as a postdoc for two years, kept writing papers, going to conferences, and doing occasional public outreach, like organizing global events for the “2009 International Year of Astronomy.” Outreach was in a sense the most fulfilling activity, but the research itself was the most exciting and challenging. The discontent with this hard choice grew and I decided to leave at the end of my second year in the postdoc. Leaving this job is one of the most difficult things I have done. It was fascinating to work with satellites and rockets, at a top institution in the world. For someone who comes from a small rural village in northern Spain, it is a long way from home. Moreover, I had no idea what else to do. I felt like I was climbing higher and higher a tall mountain, but it was not the mountain I wanted to climb. To climb the mountain I liked, I had to find it, and I also had to go back down to the lowest part and start again. I applied for, and won, a three months science policy fellowship at the National Academies. My rocket science boss candidly told me he thought it was a mistake if I wanted to stay in academia. I remember being very nervous even asking him to let me go. Academia is very unforgiving, pausing my research and publication cadence could have huge impact in my academic credentials. On top of that, as a non-American I needed his permission to attend the Fellowship while keeping my work visa.

The Fellowship was great to open the eyes beyond academia and into what science policy is. Most of my cohort of policy fellows were in the same spot of recent PhDs wanting to leave academia and not sure how. At the end of the three months I had to go back to the lab. Instead, I told my boss I was leaving. I would lose my work visa, my right to stay in the USA, and it also meant the end of my academic career. I had few weeks to get out the country or find a job, somewhere, somehow. My boss didn´t really support that decision, but he said he saw it coming, accepted it, and was keen to help me figure out what I actually wanted.

The USA is known for giving people a chance if you work hard: the “American dream.” I also knew that my country, Spain, was deep at the time (2010) in an economic crisis, so I better try out there. Turns out finding a job in the USA is extremely hard even for a (foreign) “rocket scientist.” Either they saw no need for one, they saw lack of “real” experience, or they did not want the trouble to get me a work visa. In my extreme, and now embarrassing, naivete, as plan B, I decided to go to Africa and do science policy there. I don´t really know what I had in mind, but since in Africa many countries speak French, I signed up to take a French class. It turns out that one of the colleagues in class knew of a new NGO on climate change that was just starting. I interviewed there and got the same answer: no need for a rocket scientist. I did, however, spend a weekend soon after drafting some numbers for the mathematical model the NGO was working on. From my point of view, it was very simple mathematically and it was interesting to plug numbers of something I cared about in the real world. I had a quick call with the executive team, and on the spot they hired me to continue building it: I was to start working at once from Spain, fly for meetings every two weeks, while they began the visa process right away.

I tell the story with some details, because that moment, that arrived from a combination of serendipity and relentless attempts, is the moment I broke the frame I was trapped, as a “scientist.” Before this moment, I was labeled as having “no experience” outside academia; after this, I had proven that my skills were valuable in the job market. While preparing this book, I sat down with the NGO boss to ask him why he gave me that chance. It turns out a big part of his trust on my potential was that he also comes from academia, as an engineer. He sees the handicaps many academics have when trying to work outside, but he also sees the advantages if the person manages to adjust. In particular, it was the capacity to talk both in deep technical terms with economic and environmental experts, and also with journalists, politicians, and people with no technical background. From my point of view, I was just leaning on my science outreach experience for this. Just as many academic scientists do, I gave talks about our work to the public. He used an interesting term, “vertical and horizontal vision: Vertical to go as deep or shallow as needed, adjusting the narrative, and horizontal to engage all types of stakeholders, from theoretical mathematicians to heads of state.” These are skills that I have worked constantly on since leaving academia, and I believe are core to impact science. The NGO proved not only the breakpoint to leave academia, but also a place I was thrown to learn by doing, combining research, policy, implementation, and marketing. The work we did on the NGO is the story I shared on the last part of the climate change chapter.

After two years at the NGO, our data website vendor offered me to go with them to build a new company, Mapbox. They again valued that vertical and horizontal vision. They saw me contributing code to the website and presenting the tool to both a climate change conservative think-tanks, and most liberal researchers. When I also interviewed the Mapbox CEO for this book, he pointed to what I already thought of him, and the USA. He didn´t really care much about the degree, or the academic research; they wanted people that got things done, the things they needed to be done. “Points on the board” he would call it, core to typical Silicon Valley ethos. In fact, since day one, Mapbox has been a mix of artists, philosophers, and graduates from international relations. Only a minority of computer science graduates. I was then the only former academic. Moreover, I realized my academic training, while very useful for the skills I had already used in the NGO, also came with handicaps. For instance, as we were building a project, there were times I realized halfway through that there was a better structure to do it, or a better tool. In academia, it is almost always okay to start over. In academia, the focus is on gaining understanding. In a startup it’s always better to deliver it, and then find incremental ways for improvement. The relentless focus on “shipping it” is another Silicon Valley commandment. My work as Chief Scientist at the startup would often involve having to understand new things, but always as a milestone to deliver something. This was uncomfortable at times. It was like running a sprint, and having a double finish line, the one you liked, and the one that matters. As time went by, the company hired a few more academics we had to manage, and I could absolutely feel the same pattern. Just like the NGO boss had seen.

Years later, and having help grow the company from around ten to around one hundred people, I moved to the World Bank. This was the first “Data Scientist” staff position the World Bank had advertised, at the Innovation Labs. When I also met recently with my manager while preparing this book, he highlighted the same pattern of vertical and horizontal vision as a key part of the hiring committee decision. It is not common to see someone with deep technical experience, and strong communications, able to integrate these technical skills into non-technical processes that depend more on strategy, diplomacy, policy. In the years I spent there, I was part of many teams working bridging technical and non-technical aspects of development and technology: Our work focused on how the latest technologic and scientific advances made sense, or not, for development outcomes, in developing countries with developing data. Managing the hyped promises and expectations on both sides. Including my own.

The president of the World Bank, Jim Kim, with whom I could work directly on occasions, has a very interesting background that also reflects this attitude. When he was young, he created an organization, ‘Partners in Health’, on health care for developing countries which was extremely critical towards the World Bank and wanted to close it as paternalistic and theoretical, too far from the human reality of poverty up close([[Notes#3]]). One of the lessons he shared in staff meetings, and on a Forbes profile in 2016 ([[Notes#4]]), is that “Finance and macroeconomics are complicated, but you can actually learn them. The hardest thing to learn is mud-between-your-toes, on-the-ground development work. You can’t learn that quickly. You can’t learn that through trips where you’re treated like a head of state. You have to have kind of done that before.” This echoed very deeply in my idea of impact science. One can learn physics or biology, and these gained skills do have a potential impact in our lives, but to actually realize that impact, one needs on-the-ground experience. You can do some impact science from the lab or from a paper, but one must also go where the intended impact could use some science. I perfectly remember listening to him telling this story, and just a few days later going on a work trip to Dakar, Senegal, to learn about their data science ecosystem, and to help grow it. I remember traveling a few hours to a small village where an innovative NGO, “IamtheCode,” was teaching women and girls technology and entrepreneurship. I had so many ideas of open and free software they could use to calculate all kinds of metrics and create data-driven policies. I also remember with embarrassment that most people that attended had no computers let alone laptops, neither they had good data, nor good internet connections. I was right on the value of my ideas, but my approach was useless. I had to mentally switch mode from a paternalistic push, to an iterative dialogue of needs and potential, which continues to this day. To reflect on the words of Jim Kim, the village was too dry to have mud on their unpaved streets, but my feet were dusty while I did my best to help create impact there, on the ground. This is a feeling I have looked for ever since, like the story of Bhutan I shared in the first chapter.

My time as a World Banker was a fantastic chapter that also taught me the timeliness of impact science today. In a world with incredibly efficient digital dividends, it is key to help leverage the latest and most efficient science and technology trends across the globe. Like the circular economy. Like sensors and the internet of things. Like drones. Especially in developing economies. Especially in the constrained context of a developing country, for development goals. Otherwise these digital dividends, would only increase the digital divide and inequality in the world: The developed places, with more funding, more structure, education, and less constraints would absorb the benefits, increasing the divide, or even leveraging it: when a person in Nairobi uses Facebook, gets a ride with Uber, or finds a gig via TaskRabbit, part of the benefits go to Silicon Valley. There is no technical reason it could be precisely in the other direction, where the world would also help drive finance to the developing world, instead to Silicon Valley. That was my goal on one of the projects we did during the time I worked with the World Bank in Philippines and China with regional and city planners. Their strategy and measurement of “accessibility metrics” -how quickly people can get to a hospital, for example- has for long been an incredibly expensive endeavor involving expensive sensors, models, and software. Things like cameras in traffic lights to measure rush-hour locations and times. Meanwhile, any city today has plenty of taxi drivers, or ride sharing apps that can use the software we created to locally map the topology and traffic of their road and street network. Basically using those cars providing rides to people as anonymized traffic beacons. Moreover, much of the software used to develop this solution comes from the open software movement developed by Silicon Valley in their quest for their own apps and services. In a real and beautiful sense these improved data science tools help reduce the digital divide, not just increase it.

There are many other examples of scientists doing this journey from academic science to impact science. The Spanish marine biologist Enric Sala beautifully personifies another such case. He was an academic of marine reserves, environmental protection studies and climate change. After his PhD, in 2000, he got a prestigious position as professor at one of the top academic places on his field, at the Scripps Institution of Oceanography in La Jolla, California. Years later, in 2007, at an even more distinguished institution of National Council for Scientific Research (CSIC), back in Spain. During these years he was fully dedicated to publishing the importance of marine conservation, the effects of climate change and ever-increasing details of the decreasing health of very vulnerable oceans, wild marine life, and coasts around the world. As he told me when we discussed about this idea of impact science, he got tired of being the scribe, the witness, of the marine destruction, so he left academia and started a journey driven by the compass of impact, not only knowledge creation. He led a project to create the business model concept of “Fish Bank” ([[Notes#5]]). The basic idea being that the reduced profits of not catching fish on these protected areas are vastly compensated by the fish caught overflowing around that area. Moreover, one can include extra benefits setting up sustainable tourism alongside the reserve; that now also harbors more biodiversity. Enric presented this business model with specific simulations and potential pilot sites, but also took into account the economic incentives, financial mechanisms, and politic arguments to align all the incentives from all stakeholders. And indeed, the coauthors of the paper, alongside academics, are a Minister of Foreign Affairs of Netherlands, a World Bank expert, an executive of an insurance company, and an environmental activist. Armed with this multi-stakeholder argument, in parallel, he scoped an action plan. He joined forces with the National Geographic to brand a series of expeditions to pristine oceans. He also had to find a set of donors and benefactors to support the activities financially. These donors and collaborators included the actor Leonardo di Caprio. Enric then used all that economic, financial, narrative, and visual leverage, combined with a thick stack of academic papers, and the sustainability model, to lobby governments to protect the oceans. While it is hard to directly link the protection of seas to a particular advocacy group, this project (called “Pristine Seas”) has made twenty-six expeditions, countless numbers of incredibly powerful videos, data for many academic papers, and was also involved in the creation of eighteen marine reserves, and an extra five million square km of sea protected (an area larger than the European Union).

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