Women in Big Data Brussels' Podcast

Data, Humanitarian Aid & Migration - A Talk with Tuba Bircan (VUB & Cambridge University)

March 30, 2023 ICT Innovation Talks Episode 9
Women in Big Data Brussels' Podcast
Data, Humanitarian Aid & Migration - A Talk with Tuba Bircan (VUB & Cambridge University)
Show Notes Transcript Chapter Markers

Listen, and get insights into Data, Humanitarian Aid & Migration in this talk with Tuba Bircan, Research Professor of Sociology at the VUB, Social Scientist at the Wellcome Connecting Science and also at the Kavli Centre for Ethics, Science, and the Public at Cambridge University. We talk about Tuba's interest in this episode's topic, the social initiative Needs Map, and the book Data Science for Migration and Mobility, co-authored by Tuba.

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Note: Podcast transcription edited to improve readability.

Desiree Timmermans  00:03

Hello, welcome to the Women in Big Data Brussels Podcast, where we talk about big data topics with diversity and inclusiveness in mind. We do this to inspire you and to connect, engage, grow, and champion the success of women in big data. The aim of this podcast is to reveal to you what you can do with big data, how organizations and societies use it, and the potential of big data to create a better future for everyone.

Tuba Bircan  00:30
So needs map, as I said, is a social initiative, a nonprofit organization. And the idea is how can we match the people in need and people and institutions and organizations who would like to provide support.

Desiree Timmermans  00:46
In this 9th episode, we talk about Data, Humanitarian Aid, and Migration with Tuba Bircan. She's a research professor of sociology at the VUB, and Social Scientist at the Welcome Connecting Science, and also at the Kavli Centre for Ethics, Science, and the Public at Cambridge University. We talk about Tuba's interest in this episode's topic, the social initiative Needs Map, and the book Data Science for Migration and Mobility, co-authored by Tuba.

Let's start.

Desiree Timmermans  01:20
Welcome Tuba. I'm really excited to talk with you about Data, Migration, and Humanitarian Aid, as these are topics that are also close to your heart. So, can you tell us what it means to you and what you want to achieve?

Tuba Bircan  01:33
Thanks a lot for the invitation. It's a pleasure to be here.

So I'm to Tuba Bircan. I'm currently a Senior Social Scientist at the Welcome Connecting Science and the Kavli Research Centre for Ethics, Science and the Public at the University of Cambridge. But I'm also a Research Professor of Sociology at the Free University of Brussels.

I am a statistician by training, and I've been in social sciences for quite some time. So I started with political science but jumped between different social sciences. So I can call myself an interdisciplinary researcher. And I have worked on qualitative, but also quantitative, and mostly advanced statistical methods and applications in social sciences, which was, in a way, the seed of my interest in big data and AI applications.

And for the last eight years, I've been working on how to ensure the ethically and socially responsible use of big data and AI for tackling societal and political challenges.

Desiree Timmermans  02:30
Well, that's good to hear. And if we look at this topic, what does it mean to you?

Tuba Bircan  02:36
Of course, we do know that big data and AI have been gaining importance all around, also in our daily life. However, most of the time, we consider it too technical. And it is mostly dominated by data scientists and computer scientists who have been developing it. However, there is a human and societal aspect to it.

In fact, AI is everywhere on our mobile phones and our social media data. So, I do believe that it infused to our daily life so much that we have to understand the impact on human beings and societies. That's why I believe that we should also have more social scientists involved in collaboration with people who are working with big data. Because we are not only talking about the technical challenges with these rapidly emerging technologies, we are also talking about the societal challenges.

Desiree Timmermans  03:29
What kind of social challenges are you working on at this moment?

Tuba Bircan  03:33
I'm working on migration and humanitarian data, particularly. And also public attitudes towards these new technologies in different areas like health. But specifically for migration and humanitarian aid, we are working with particularly mobile phone data, internet-derived data, like: social media data and search data, as well as satellite data. So we do know that big data is not perfect. We do know that it is big in terms of volume, but we are talking about the veracity of it, where we already agree that this data is constantly generating with a lot of errors in it. So, it is not only about correcting the errors in the algorithms because we do know that for instance, bias might exist: it can be in the algorithm, or it can be in the interpretation and the use of it.

So there are various cases we see that AI applications fail to comply with the ethical expectations, and there were setbacks. To give you a very basic example from: Amazon's recruitment tool, or when we talk about allocation of the police force in an area, or in migration when we talk about using facial recognition of iris scans for the refugees to have access to fundamental rights.

In short, it is rapidly evolving, as I said, but we are still working on it. As the EU, the AI principles try to make that we have a human aspect in the utilization of these things. So that's why we are talking about the existing bias and how to overcome them in the data as well as algorithms. But more importantly, how they are used.

Just to sum up, I can say that when we are talking about AI systems overall, it is important to remember that these are tools and have been used by people. So, these systems are mimicking us. I think we have to work a bit harder to make sure that we develop unbiased systems, where unfortunately, we as a society or the communities are still biased, have stereotypes, have discrimination, and inequality.

Desiree Timmermans  05:40
Yes, I understand. And the bottleneck is us: it's humans.

Tuba Bircan  05:44

Desiree Timmermans  05:46
And you're also the founder of Needs Maps. And it maps, for example, the needs in Turkey due to the massive earthquake on February 6, 2023. So what exactly is Need Maps? And how does it work? And, of course, can the listeners also contribute?

Tuba Bircan  06:03
Thanks a lot for raising this because it's a topic that is very close to my heart. I am one of the founders of the European office of Needs Map. In fact, Needs Map is a nonprofit organization founded in 2015 in Turkey, but we are active in Brussels since 2022. And, of course, we wanted to have things in a more settled and systematic way. But then we are going through this catastrophic tragedy as of the beginning of February. So Needs Map, as I said, is a social initiative, a nonprofit organization. And the idea is: how can we match the people in need and people and institutions and organizations who would like to provide support? So we do know that, especially during the humanitarian crisis - or when we have disasters or tragedies, e.g., a wildfire, earthquake, or flood, this could be a conflict - people really want to help. And there are a lot of civil initiatives that are on the field to help too. But because of the nature and the systematic development of the situation, it is very difficult to coordinate.

Needs Map is a technological product itself. We are talking about a GIS-based system where people can enter their needs. Assume that I'm sitting in Leuven, and I can say that: oh, there is a family who needs some stationary or computer support for their kids. But this information had to be really accurate because we have an assessment and accuracy setting for checking colleagues. So once it is entered into the system, our people check the validity. And if that's the case, it appears online on the map. And then, if you are someone or an institute who would like to help, you can go, and check what type of needs there are and what you would like to do.

I think it is crucial to mention that Needs Map is not a transfer point: we just coordinate. So the support provider can directly help the person in need. Of course, on normal days and under expected conditions, it works way easier. But when we have this, for instance, earthquake case, you know, the earthquake happened in 11 different cities. And it's a very large geographical area, as big as Belgium, to give a scale. And we are talking about more than 50,000 people who unfortunately lost their lives. We are talking about 15 million people affected and still more than 100,000 under the rubble. So it's a huge tragedy. And there, of course, we get a lot of support. But we are working with many NGOs.

The first thing that I'd like to mention is that for people who would like to help, we developed a platform, which is a web-based platform called: disaster platform. We are working with more than 20 organizations, including, e.g. public authorities and NGOs. And we try to make sure that we are working in harmony because all the civil initiatives are trying to do the same things. And we do know what each other does and where the needs are.

Secondly, we do have several campaigns. For instance, the first campaign is 'One Home, One Rent', which means: we would like to initiate that these people who had to leave and are internally displaced get new homes and rental places. But it is very difficult in terms of finances, and also arrangements. So what we do is on this campaign, people can go and say: I would like to cover the rental costs of a family for that long. So they can really donate to a specific region. In addition, we have the 'I Am With You' campaign, where we would like to support the university students who have been affected: not only the ones whose families were there but also those who were affected because they were studying at the universities in the area. So you can provide scholarships to University students. We have so many different campaigns that we do scientifically proven. For instance, we do have blockchain technology, which is called SOS chain, where we also try to synchronize global things. Because we do know that a lot of people in the UK asked me how can I send money, do you have a UK account? I have to say that Needs Map is being settled in the UK too, but we do have a European bank account, and we are working with other NGOs, too.

In short, we need volunteers who would like to work with us. It doesn't need to be on the field and in Turkey because this is a technological product. So we are very open to interns and volunteers interested in such things. Secondly, you can donate because we do have accounts. And if you go to NeedsMap.coop, you will see that on the first page, we give many bank account numbers if you would like to donate. But in addition to that, we would like to underline that support is not needed in the short run. So we need a sustainable support system for the mid and long-term. And I also have to say that we are working with several organizations that have come up with their own projects. To sum up, for instance, one of the companies from Germany is helping us build a school with five classrooms and a daycare, so we are working with a municipality. Another group of companies from the UK is helping us build a fully functional hospital. So we are also open to any ideas because, in some cases, the organizations particularly come up with some ideas. We know that we will need support in the long run, so contact me by checking our website for any further information: needsmap.coop

Desiree Timmermans  11:43
And if we look at Needs Map, I understood that there is a project called Disaster Map. Can you tell us a bit more about it?

Tuba Bircan  11:53
Yes, of course. It's one of the most relevant ones today because we are trying to build a technological platform and a product group that we can use to end poverty - humanitarian aid.

And particular, the disaster map is one of the joint initiatives of this platform. It started after one of the earthquakes in Turkey, and we are working with GIS technologies: where we map the region of the disaster. And today, if they go, they will see this southern Turkey and Syrian earthquake. And they will also see that we try to cover the area as much as possible. We are trying to estimate the number of the population affected by the disaster, and on different scales: heavily affected or lowly affected. So when we look at that, you will see that it is around 15 million people: where more than 500,000 people were severely affected by the earthquakes.

In addition to that, you will see a map, because we map: where the warehouses are, where the tents are, where people can gather, as well as the damaged buildings. So we wanted to show specific districts: it's a very precise mapping of different areas and districts to see the status of the buildings.

Besides, we also estimate specific demographics to see how many children have been affected, what is the proportion of women, and what is the proportion of the elderly. These are also important for the initiatives, where they particularly developed some projects or support for the elderly, extremely ill, children, or women. To give you an example, based on our estimations, one of the women's sentry products companies sent more than 1 million products to the areas that we helped them to identify. So it was really tailor-made support.

And, of course, how it happens: where do we get the data? That is very important. The technology is there, but we need the grassroots data. We already have almost 14,000 volunteers working with us on the field. What they have to do is share the location, as we need the coordinates. They take very detailed photos of the area, and they take notes. And based on that, we gather the information. We have a technical team cleaning up the information and matching the photographs with the coordinates, and the maps that we already have on Turkey.  Our volunteers are all over the world. We are not only working with the Turkish volunteers - of course, that's the majority - but everyone can volunteer to help us.

In addition to that, we do have our major offices in Ankara in Istanbul - in the big cities - where we have our colleagues and volunteers who are working on the desk to really improve the technology and the precision because: we are talking about basic predictive models. And the data to train is lacking, so we are trying to improve the data for that. So it is about mapping the aftermath, predicting the impacted areas and people, estimating the need, and then matching the needs with the people who would like to support them.

Desiree Timmermans  15:12
What an amazing initiative. Thanks for sharing that with us. And for the listeners: go to the website of Needs Map and see what you can do -  needsmap.coop

And for me, Tuba, I went to the website, and I saw a map with so many flags in Turkey: what do I need to do, because I was overwhelmed. There's so much help needed.

Tuba Bircan  15:32
Yeah, unfortunately, that's the case in many countries. And the map was built before the earthquake. So it also has other needs. It is not only about earthquakes. If you're particularly interested in the earthquake, it's better to go to the region at the Syrian border: around Aleppo. But what you can do is: you can click on every single flag, and normally you can see what they need.

What I suggest is that rather than going on every single flag, if you scroll down: you're going to see a list of existing ongoing projects because these are, in a way, categorized versions of them. So, you can think: okay, I'm going to help people with getting computers, or I'm going to help helpless people. These can give you an idea about which areas you can really help.

In short, you can go through the website, check different campaigns, and contact us if you have any questions. But we are also open to suggestions because that happens a lot as we have such a broad volunteer network. So if people want to come up with ideas, we are more than happy to discuss them too.

Desiree Timmermans  16:44
Okay, thank you very much. And are there already supporters from Belgium, for instance?

Tuba Bircan  16:50
Yes: King Baudouin Foundation. They are aware of our work. So they supported a couple of activities. And we were so lucky because they also, let's say, mobilized their stakeholders for us. In addition, Fari was a supporter from day one; I have to thank them too. So yeah, there are several stakeholders in Belgium who are aware. And we have our office in Brussels very recently.

Desiree Timmermans  17:14
And besides Needs Map, you also have the time to coauthor a book Data Science for Migration and Mobility.

Tuba Bircan  17:22
Thanks for bringing it up. So, let's go back to academic work because: that's my major job. I'm a researcher, and I put a lot of effort into studying and understanding the use of big data and AI for studying migration and humanitarian aid.

So the book is called Data Science for Migration and Mobility, you know, you can really get it from two sides. It is for studying migration and mobility. But we also would like to make the nuance that for migration, so you know, to take the advantage of these technologies: so assuming that the gain will be for migrants and migration.

It is an edited book with 19 chapters from more than 30 authors from all over the world. And the idea of this book is twofold. First, we would like to familiarize the social scientists who would like to learn more about machine learning techniques, deep learning techniques, and big data sources for migration. It is a handbook. But on the other hand, we also would like to introduce the concepts, theories, and the importance of the social and societal approach to migration studies as a theme for data scientists and computer scientists. Because they have the technical skills and the competencies, and the social scientists know the contexts. They've been working on these topics for long.

We want to build a space for collaboration. That's why this book has one part devoted to introducing the data sources: very clearly explaining which type of data sources have been used. We are talking about various social media data, like Facebook, Twitter, and LinkedIn data. We are talking about satellite data, mobile phone data, and a combination of various data sources. So the readers can learn: where to get the data, how to download it, and how to process the basics. And then, we have some parts about visualization because it's very important that big data is also communicated in the right way. We have many case studies where we show how to analyze.

Desiree Timmermans  19:29
And do you have an example of that for one of the cases? 

Tuba Bircan  19:33
For instance, I can talk about mine. In my chapter, I'm explaining where the satellite data can be downloaded, e.g.,  in which format, can anyone process it, and what type of skills do I need. So if I can't process it: are there any pre-processed products, and how can I use the variables?

And then, I also show several cases, particularly for humanitarian aid and internal displacement, on how it has been used. To give you an example: satellite images have been used on vessel controls in the Mediterranean. So, you can see that it can be used to stop the boats from arriving on the European coast. But it has also been used by a specialist civil society to help the boats to reach the coast and the shore safely.

We also have an interesting example from financial data: how to use bank transactions to work on the remittances and transnationalism to see the links between different countries - if we call them sending country and receiving country.

I have to underline that we have a very large, important, and significant chapter on ethics. But we particularly asked every single chapter author to reflect on: what can go wrong with the big data and which areas we should be careful with both technically and ethically. So we do believe that it's very important to consider these new technologies as a huge potential, but we also have to acknowledge where we need to work further to make it better.

Desiree Timmermans  21:05
And Tuba, thank you very much for being our guests.

Tuba Bircan  21:08
It's been a pleasure. Thanks a lot for giving me the opportunity to talk about what we have been doing.

Thanks a lot.

Desiree Timmermans  21:16
Thanks for listening to the Women in Big Data Brussels Podcast. We appreciate it if you get in touch with us to provide your feedback or request to partner up and be a guest. You can contact us via datawomen@protonmail.com. You also find our contact details in the show notes. Tune in next time!

Tuba Bircan's interest in Data, Humanitarian Aid & Migration
The Social Initiative Needs Map
Book: Data Science for Migration and Mobility