“So many women I talked to tell me that they gravitate towards careers and professions that they know they´re going to be great in. Most girls are taught to avoid risk and failure. We are taught to play it safe. In other words, we are raising our girls to be perfect rather than brave.” Reshma Saujani.
I want the following excerpt to be a contribution to inspire women to take risks without the fear of failure and persevere in their journey to keep exploring the multiple uses of data.
How do you use tech/data to tackle important issues? Tell us about your work.
I am currently the Head of Exploration for the UNDP Ecuador Accelerator Lab. I use data innovation to reframe and shed light on seemingly impossible development issues. Data innovation combines non-traditional and traditional sources of information to provide new insights to better target policy responses. By combining new sources of data, such as social media, mobile phones, GPS records, satellite imagery with public registers, or household surveys, it is possible to have a more complete, coherent, and up-to-date overview of a constantly evolving problem.
Another key task to innovate with data is to map the actors that are data holders and build not only strategic partnerships, but also trustworthy relationships. Collaboration is fundamental to create valuable information for policymakers to course-correct programs, as well as for communities to empower their decision process.
What was the most impactful project you worked on in the past year?
This past year, I used data innovation to identify sustainable practices for cattle farmers in the Ecuadorian Amazon. Ecuador, like most countries in the Amazon region, loses hundreds of hectares of rainforest each year; 99 per cent of deforestation is caused by activities related to agriculture, and 64 per cent of it is due to the creation of pastureland for livestock farming and other purposes.
Uncommon data sources were combined, including open-source satellite images, cadaster data, and national cattle vaccination records to find farmers who outperform their peers with similar resources, meaning that they had an efficient cattle production without cutting down the forest. Once these farmers are identified by running an econometrical model, qualitative field research is done to understand their uncommon behaviors or coping mechanisms that enable them to find sustainable practices.
By tracking deforestation and cattle efficiency at the farm level, land cover maps offering new insights about the drivers of deforestation and farmers’ land use were created. Important efforts are being made so that the Ministries of Environment and Agriculture take up this work to reinforce the national strategies aimed to protect nature and wildlife and promote sustainable production.
What is one unexpected learning from 2020?
It was unexpected to realise that most interventions in sustainable production are at the farm level, but they are designed without data at that level. Another surprising learning was that cutting over one hectare of forest is considered deforestation by the government, while cutting trees at a smaller scale is not. This could be a perverse incentive for farmers to get rid of their remaining forest.
What are some innovations from the pandemic that have caught your eye?
Data innovation is at its highest during uncertain times. The innovation that caught my attention the most during the pandemic was the development of a free web application to track down those who had been in contact with people infected with the coronavirus. In South-Africa, a range of actors collaborated to develop the Covi-ID app, including bankers, scientists, entrepreneurs, and students.
The innovation of this work is twofold. Firstly, it collects data in a very creative and simple manner. Every user of the app is assigned a QR code, either on their smartphones or printed on paper to make the solution inclusive. This code is scanned using Bluetooth to generate a geolocation receipt; the scanning of the code can take place pretty much everywhere. This mechanism enables “contact tracers” to warn those who have been in contact with infected users by knowing when and where the encounter took place.
Secondly, the data management model was designed with a privacy-first perspective, meaning that users keep control of their data and must agree to have their information released to health authorities if they test positive, allowing users control over who gets access to the data, for what purpose, and for how long. Blockchain technology is used to assure the self-sovereign identity of the user, meaning that the data is not centralised in a government or private-sector database.
What are your priorities for 2021?
What tool or technique particularly interests you for 2021?
Which other countries inspire you and why?
During this year, I will be working to generate a data management model based on the principle of self-sovereign identity to collect nominal information of young informal workers. It was inspirational to learn about the South African Covi-ID experience that aims to share information in a safe and efficient way prioritising privacy first and building a data ecosystem with various actors to protect it.
To collect young people’s information, a web application will be developed to reinforce users’ ownership and control over the data, and to consider the “informant” as its main user. The app, designed based on the user´s needs, is a job and learning platform that delivers real-time labor market insights and training opportunities, as well as a proper work calculator that assesses the level of informality of the worker and provides information on labor rights and regulations.
To guarantee users’ sovereignty over their data, blockchain will be used to create a data wallet rather than gathering all the data in a single database. This technique has a decentralised and trust nature with multiple benefits including greater transparency, enhanced security, and easier traceability.
Informality is a complex problem that jeopardises the well-being of the worker and his family throughout their life cycle. To be deprived from formal work affects their level of earnings, but also the opportunity to have access to the social protection system. In Ecuador, as in many countries of Latin-America, at least 60 per cent of the economy is informal and 7 out of 10 youngsters don´t have access to the social security system.
This solution goes beyond surveys, extractive data processes, and conventional data management models in order to collect information from young informal workers aiming to design equitable and inclusive labor policy responses.