My Tedx: The future is not about data

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How many people need to die before we listen to the facts? 1? 10? 100?

Let’s look at the reaction to the appearance of HIV/AIDS in the USA: By 1983 we knew about the spread of the disease through various channels, for example blood transfusions. So, how many people need to die, before we listen to those facts? The answer, 5000. At least 5000 people died in the 3 years that it took to start implementing the scientific recommendations experts had called for. The Science was clear, but experts were just not getting through.

Scientific facts alone don’t change the world. Specially in complex situations like this one. There could be other reasons, there could be implementation reasons, economic reasons, political reasons, strategic reasons, … Science is an important part, but is only part of the equation; and definitely is not only about pushing the facts by publishing the facts. Science should be fully engaged in the way we make decisions.

But don’t get me wrong, I’m a Scientist. The whole package with extras. Hard core scientist nerd, PhD in astrophysics and postdoc. I do love science. Science is arguably one of the most wonderfuls tools humans have invented to Understand. To understand nature, to understand the world. But if Science is about everything, how many of you, when you are watching in TV these documentaries about science or about zebras in africa…. instead of thinking how amazing it is that we can understand what’s happening there… you think “it’s a good one for a little nap” or “I’m not in the mood”, “I’m stressed”, or you change the channel, you flip the page …

To understand what’s happening here we need to go back a little bit; back when scientists were called “natural philosophers”. Think about the old scientists like Gauss, or Newton,.. they were astronomers and geologists and mathematicians, andand, and… there were inquisitive people of the world. But as science evolved; it went deeper and deeper into fields that needed more specialization. We started to constrict science into silos, silos of knowledge. Segmenting reality. So scientists started to be astronomers or geologist or mathematicians. Scientists started to engage mostly within their own silo with their own peers, not with other silos, or society in general. And somehow we were okay with that.

Siloed science, segmenting reality, a paper at a time. [[Flickr: Mike Lewinski]](https://www.flickr.com/photos/ikewinski/7314030462/in/photolist-c9jjru-c9ja5A-8QdSmX-8QgWZd-8QgUTY-8qoAmQ-85H9JM-6xsePy-5S7KSp-5S7Kz4-5Qngf7-5QhZP6-5bNqm4-5bSFQA-4sMZcF-4sMZ5H-4sS3Pq-2GytxD)

On top of that, as a scientist your credentials, your funding, your job, depends on publications and the citations of those publications. So if the expectation is to understand everything, you only have time to do what ends up in a paper. There is, however, a strong case to make that scientists are not so because of the facts in the head, or a paper, but because of the way they look at the world, on how we understand.

That’s the reason I left research. That’s the reason I left, back then, my dream job of rocket scientist, for a six months fellowship with no employment prospects afterwards. As much as I loved it, I felt frustrated. There is so much more in science than publishing.

We need science not because of the facts, but because it helps you, help us, all of us, move forward, understand what’s happening. What explains those facts, that data. In this world that depends more and more on technology, that depends more and more on science, there is less and less people that understand Science and Technology.

With this hypothesis in mind I decided to test it. Let’s see what happens. What happens if a scientist that is a researcher, stops being a researcher and keeps being a scientist. I started to look for places to apply the tools I learned, the mathematics. In the end it turns out that the physics of plasma waves in the Sun, is similar to the physics to explain traffic partners in the cities. That’s the kind of work we are doing at the World Bank Innovation Labs. I want to share with you three examples.

Derhi, India.

This is Derhi. It’s a little village in India. If you were there, you would see electrical transformers. You would see the light cables. Electrification is a very important in Development; not only provides more safety, and better jobs but also, for example, allows kids to do their homework after sunset. Electrification, or having lights at night, is very important. But if you were in Derhi at night you wouldn’t see any; because there is no current on those cables. Electricity generation and transmission is a very complicated problem. What we did here is try to measure and monitor this problem. We used satellites that go every night and take pictures of the whole country, and then with a process that is rather complicated, remove the clouds, take into account the moon shining, … but conceptually is very simple: Can we ask how much light there is on every single village? — and there 600,000 villages that we know of — .

India at night. [nightlights.io](http://nightlights.io)

The point is that if you are able to ask the questions of how much light there is in every village every night, we can understand not only were there is light or not, but also when there are blackouts. Furthermore, because these satellites have been doing this for the last 15 years we can also know how effective we were doing this in the past, and how and where we can implement the programs moving forward that best use our resources. So that kids can do their homework after sunset with artificial lights.

Doing homework after sunset. A luxury for those with lights. [USAID]

The second project I want to share is in China, on a very rural province in China. If you live here, one of the problems you have is Accessibility; or in other words, how do you go to the market to sell your product if you’re a farmer, or how do you go to the hospital, or how kids go to school. And it takes a lot of time, because the roads can be like this one, muddy.

What if this is your road to go to school? [Kai Kaiser. Philippines.]

Typically the measure of Accessibility is the percentage of all-weather roads. But we can push it further, make it better, we can make it about the people; we can make it about how much does it take for you from this village — from all villages to get the closest, whichever it is, hospital. So the complexity of the problem becomes simple in a map.

Improving the pink roads makes people in the North reach the closest hospital much quicker. [[Rural Roads](https://github.com/WorldBank-Transport/Rural-Road-Accessibility)]

If you live in the province that is colored green it means that you are going to reach the hospital in less that one hour. If you live in the red part it means it takes a lot of time. So we need to make the red part of the country become greener. We need to calculate which are the roads that, if you upgrade them, makes this change. We can be much better, we can push ourselves to understand the complexity of what’s happening.

Ever stuck in traffic? Those taxis are reporting how to make it better. [Flickr: Manila]

The third example I want to share with you is traffic. How many of you have been stuck in traffic in the city? Probably everyone. In developing countries is worse not only because the roads are not prepared for the number of cars we see, but also maintenance is an issue. Trip cables, traffic lights, signals are not properly maintained. In practice what happens is that you have traffic agents taking calls all the time from colleagues writing reports of what the traffic is and what is the traffic loads, And there are literally pages and pages with this information. We can do better than this. In this case, the idea is to leverage these apps you can call on your phone to call for a taxi. Because every driver in the city has the app running, and is sending the location of all the cars on the fleet, every few seconds. If you put that in a in a map you have a live picture of the phones moving slowly across the city. You get the information of the traffic, and how much time they stop on the intersection, or the traffic light. You can now know how to tweak those traffic lights in response to the life information of traffic. All without having to build more infrastructure.

Using taxis as traffic sensors [[OpenTraffic](http://opentraffic.io/)]

That’s why I think the future is not about data; but about absorbing complexity. We’ve never had as much data as we have today. It’s growing exponentially, most of the data we have today has been generated the last two years. We have never had as many people looking at that data. The opportunity to make data-driven decisions is unprecedented.

What are we going to do with this? I don’t think that more data, just more data, is going to solve our biggest problems, or most personal ones. Think about the environmental crisis, think about migration and refugees, think about the economic crisis, or think about your personal projects or if you get diagnosed with a complicated illness.

When someone comes to you with data, when an expert comes with data -especially if it’s an expect — , when someone comes asking your vote — especially if they want to ask for your vote —, be very unapologetic to ask questions, to try to understand. Because understanding is one of the most empowering tools we have; and science is a tool to understand. You still have your culture, your education, your personality, your feelings… everything, but then you also have these tool to allow you to absorb what it means, to understand the facts that you have around you.

Science gives you visibility of what are the options ahead, and a what are the consequences of choosing one or the other option. It gives you the empowerment to take the right steps knowing what is likely to happen next, having taking into account all the information you had.

We need to recall science as a way of looking at the world versus a body of knowledge.

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