An interview with António Vitorino by Xiao-Li Meng
In May 2021, HDSR founding editor-in-chief, Xiao-Li Meng, met with International Organization for Migration (IOM) Director General António Vitorino for a virtual ‘fireside chat’ at the World Migration and Displacement Symposium: Data, Disinformation, and Human Mobility. The pair discussed IOM’s recently launched Migration Data Strategy, COVID-19’s impact on global migration, and how the United Nations and IOM are contributing to combating the increasing disinformation on migration and migrants.
Xiao-Li Meng: I would like to thank Director General Vitorino for joining us this afternoon, and we all know how busy your schedule must be, so on behalf of all the participants and Harvard Data Science Review, we truly appreciate your time and we are looking forward to your insights. So, let’s get to it right away. I understand that IOM has recently launched a data strategy, and so it will be very interesting to know if you can tell us about the strategy, as well as what IOM’s key data goals are moving forward.
António Vitorino: First of all, thank you so much for the invitation and good afternoon to all of you. It’s a pleasure to have this exchange with you, Professor Meng. Well, the IOM strategy is a threefold proposal. First of all, it deals with data that we use to inform our operations. Secondly, we identify the needs for migrants and people on the move in terms of support, so that we use the Displacement Tracking Matrix in more than 86 countries to have an assessment of how the movement occurs and what are the needs of the people in order to prepare the necessary responses. And last but not least, we intend to use our data strategy to ensure that the public discussion on migration is anchored in facts, not in fiction. And for that purpose, we are engaging with the Irish university [National University of Ireland, Galway] in creating what we call the Global Migration and Media Academy, with the purpose of providing to students of journalism—and to journalists of course—the necessary evidence for them to use in their coverage of migratory events.
It’s an ambitious strategy, to be honest with you, because in fact, it depends a lot on partnerships. And these partnerships, like the one we have with Harvard University, are fundamental for us but also with the private sector and last, but not least, with member states. Because one one side, we deal with collecting data. Secondly, we need to improve our capacity to analyze data. And thirdly—which is more daring—we try to explore new tools that might be available, and you know that much better than me. Big data, artificial intelligence, and using them not just in the perspective of looking to the figures but also trying to forecast and anticipate the drivers of movements and how to deal with those drivers. This point is particularly important because movement nowadays—mobility, migration, refugees—they move for different reasons and we need to have reliable data on the motivations of the movement to be better capable to address their needs. It might be conflict; insecurity; poverty, of course; diseases, which are at this time more important as we live in the middle of a pandemic; but also climate change, which is something recent but we see every day. You know, Professor, in the Global North we speak about climate change and reducing greenhouse gas emissions for 2030, 2040, and 2050. That’s fine. That’s all fine. But the reality is that there are already millions of people who are on the move because of climate change today, and we need to address these drivers of mobility, so we can respond better to their needs and also to the threats and vulnerabilities they are confronted with.
So, in a nutshell, we try to build partnerships with the academic world, with the private sector, with a civil society, with NGOs [non-governmental organizations], but at the same time, we try to improve the capacity of member states. And this is a critical issue because, you know, data are very differently collected worldwide and they are very uneven. We are very much engaged in the Mobility and Migration Observatory in Rabaa in the African continent, an initiative of the African Union. We work also with the National Statistics Institutes because we need to give room for national statistics to integrate more accurate data on people on the move, on migrants, on refugees. And the challenge there is to be more granular. We need to desegregate those data by gender, by age, by disability, by territory of origin, by sexual orientation and sexual identity. Those elements need to be fully incorporated into national statistics, so that afterwards we can work on that basis. And that requires capacity building, and the private sector has a key role to play in that respect. And also the academic world—and not just the academic world of the Global North. One of the missing claims in this exercise is the academic contribution from the Global South, and the data strategy also aims to develop a more networked approach to the academic world in the Global South. So, there you are. I’m sorry; it’s a long reply, but it’s a very ambitious strategy.
Xiao-Li Meng: It’s incredibly ambitious. But I also want to say it’s heartwarming to hear that you essentially cover the entire kind of data science, from data collection, data analysis, the impact, all the partnerships, all of those. I particularly want to mention that you mentioned about your interest in the national statistics, and we have another special theme being planned. This is called the future of official statistics, working with the International Statistical Institute and others trying to, you know, look into how different governments are collecting their data, and analyze the data. I think that this goes very well with what you’re doing. But with so many things going on and so many credible people working in the field and on the ground, how do you prioritize these future needs versus your day-to-day needs to protect particularly those in urgent need of protection? How do you prioritize all these?
António Vitorino: Yeah, we need to prioritize because as you can imagine, resources are limited, so we need to be very to the point. Our key priority, to be totally honest, are crises and humanitarian situations. That is our main priority. We do needs assessment and we collect data about the mobility in the humanitarian settings. Be it the Horn of Africa, the terrible situation in Yemen, the Syria crisis, the Rohingya situation in Cox’s Bazar, the displacement of Venezuelans in Latin America, or more recently, the situation in Central America in the Northern Triangle. So that is the key priority, because that is the field where the data we collect are more directly used to sustain our operations and to support the member states and the migrants in confronting very harsh and adverse situations.
But then the second priority, I would say, which is the very present one, is to shift the profile of our data collection to the pandemic. The pandemic has had a major impact on mobility. Yes, it is a health crisis, but it has become a major mobility crisis. The world has come to a stop. You have almost three million migrants stranded on their way home because of the closure of the borders, because of the lockdowns, because of the suspension of flights and other means of transportation. So, we have come to the conclusion that in 226 countries and areas in the world, there have been measures taken by the authorities to restrict mobility. Two hundred and twenty-six. And if I give you the figure of how many restrictions were adopted, they are above 110,000. One hundred and ten thousand. So, you can imagine that this is highly disruptive of travel, of tourists, of mobility in general and, of course, of trade and migration. All this comes together, and this is a very key priority for us because when we look to the world today, we need to identify what are the impacts on human lives. For instance, for food insecurity and mobility. And we have published recently a report with the World Food Program where we try to identify, based on data, what is the impact of food insecurity in making people move? Also, the data on internally displaced. I don’t know if people are fully aware, but since the beginning of the pandemic, there are almost two million people internally displaced in the Sahel countries, of which one million are in Burkina Faso, which is one of the poorest countries in the world. And these people are on the move because of food insecurity, because of climate change, but also because of nonstate actors’ aggression.
So, there is a combination of different factors, and you need to analyze those different drivers to know how better to respond to them. And that’s why I’m very happy that this section is also with the UNHCR [United Nations High Commissioner for Refugees] because we work very closely with the UNHCR. We deal together with mixed movements—this terrible jargon that we use, mixed movements—where people on the move might be entitled to international protection. They might be people running away from conflicts, but also people moving because of climate change, because of insecurity, because of poverty. So, we need to have a joint and holistic approach, and that’s why we work very much in the field together with the UNHCR. So those will be, I would say, in the short run and in practical terms, our two priorities. First, humanitarian crises. And secondly, all the impacts of the pandemic and the restrictions associated to the pandemic.
Xiao-Li Meng: Thank you very much. That’s completely understandable. And again, I really want to express our deep appreciation of how much work you and your agency are doing. It’s incredibly important. And we all complain at home, say we get a little Zoomed out. But compared to the kind of a crisis you need to deal with, you know, it’s just mind boggling to even think about that. Let me ask the question a little bit further, if you don’t mind. You know, we all want to—as you mentioned—have evidence-based information to inform policies and operations. In the priority areas, as you listed, are there any specific areas you look into particularly for data to inform policy and the operations?
António Vitorino: Yeah, absolutely. We launched in 2017 our Global Migration Data Portal, where we tried to bring together, in a logic of a one-stop shop, all the data available on migration so that all stakeholders can use them according to their priorities of research, of public debate, and of data analysis. That is, I would say, a common good in the sense that we provide the data, but the data are used by the stakeholders according to their own priorities. But of course, data analysis is for us extremely important, and we need to do better. We have the global migration report that, you know, for sure, we use our data to inform the debate around the global migration report. We provide those data also to the United Nations Migration Network, the UN hub that provides a space for debate on the data that we collect. And a little bit more daring: we try to forecast future plans. And you can only forecast—well, sometimes we just estimate, of course. That’s not a rocket science issue—but we try to forecast because if member states are not prepared to confirm in advance the trends of mobility, then the situation will become much more difficult to manage. I’ll give you one example. The fastest growing cities in the world today are in Southeast Asia and in Africa, and the mobility is clearly a movement from rural areas to cities. This has a major impact on the requirements of city planning. And usually some of the tensions and the conflicts that exist are because cities are not prepared to welcome such large numbers of people that are on the move. Sixty percent of the migrants worldwide today live in cities, but they live in slums. They live in chaotic environments, in settings that are overcrowded, that do not have the basic infrastructures. So if we leave that just to the natural movement of the people, we will have very serious problems from the public security point of view but also from the health point of view. And we have seen how, in Latin America, for instance, in the slums, in the urban slums, the [COVID-19] virus proliferated at an amazing speed.
So, we try to forecast what are the big trends of movement so that we can enable member states to be prepared to address their migratory pressure. And of course, this will require capacity building in the member states, and not all member states have the same financial capacity to deal with this; training people in social services above all, because those are the frontliners. Those are the civil officials that have to deal suddenly with an increase of the number of arrivals. And we have seen that in a number of places. Hospitals that were planned for the ‘classical population’ of a city suddenly are overwhelmed by new arrivals that are badly perceived by the residents that were there already because they say, ‘Last time I had to wait for five days, and now I have to wait for three weeks for a medical appointment.’ This is precisely because the pressure has been growing and the planning has not followed the trend. And therefore, I think that these are the kinds of concrete responses that we can give if we use data and if we forecast the major trends of evolution, not just for IOM. Let’s be very clear, the entire UN system, we share the data with all other agencies, with the UNHCR, with the UN-Habitat, with the UNDP [United Nations Development Programme] and also, of course, the private sector and the academic world.
Xiao-Li Meng: Thank you. Again, this is really mind boggling to think about all these issues that you have to deal with. You mentioned the world migration report—in your Forward for the World Migration Report, you emphasized the need for robust evidence-based information on migration in the era of increased disinformation. I recognize there are so many players involved—how is the UN and particularly IOM contributing to combating this disinformation?
António Vitorino: Well, you know, I'm going to tell you a secret. When some of my UN colleagues come to me and say, ‘Oh, these campaigns of disinformation and misinformation are terrible!’ I usually tell them, ‘Welcome to the world of misinformation!’ Because we have been living there for quite some time. And unfortunately, this is a key feature of our work, and that's why data are so important, because data are the tool that we have to dismantle and deny the misinformation campaigns that we see, especially now in social media. The initiative that I mentioned to you a few minutes ago, the National University of Ireland, Galway, and ourselves, is an initiative focused on the media—on the classical media, let’s say, because we still see that sometimes the formal media feels very much attracted by the viral waves in social media. And we need to provide to journalists the data and the information that is reliable for them to do their job with full independence, of course, but based on effective data. And I will be very frank with you. I’m very concerned, because we have seen in the pandemic an alarming raise of misinformation and disinformation concerning migration, trying to scapegoat migrants for being responsible for the crisis and for the expansion of the virus.
In spite of the fact that some of those attempts did not succeed, fortunately, we are making a very strong campaign now to make the case for migrants and refugees to be fully included in the vaccination plans. And it has been extremely helpful, the decision that President Biden took that the 11 million irregular migrants in the United States will be fully covered by the vaccination campaign. That is crucial for us. Irrespective of the legal status of the migrants, as Secretary-General [António] Guterres says, no one is safe until everybody is safe. So, the best way of fighting against the scapegoating of migrants is to provide the data. But it’s also to persuade the policymakers that they need to include migrants and refugees in the national vaccination plans. This is not just a question of human rights. It is a deep question of human rights and human dignity of migrants, but it is a question of public safety and of public health. That’s why we work with the media. We try to provide the data within social media, and we try at the same time what I usually call ‘unpack complex issues,’ because migration is very complex as different trends, different drivers, and the populists and the xenophobic and discriminatory rhetoric simplifies as much as they can to produce an emotional result. To counteract against that ‘easy way of doing things,’ we need to explain complex issues in an understandable manner to the public at large. And that’s why it’s so important to be engaged with civil society, with the migrants themselves, and with the academic world, with research: to show that those campaigns of misinformation are based on prejudgments, on prejudice. They are not sustained by evidence, and we provide the evidence.
Xiao-Li Meng: Thank you very much. You mentioned a key word I want to follow up on. You mentioned the word ‘persuasion.’ And for me a major goal for data science is really to persuade people by using the right evidence, the data. Part of my research is working on data quality issues. I am working with survey organizations, working on U.S. [United States] election data, all sorts of those things. So, I have a particular interest to ask you a specific question about all kinds of difficulties that your agency must run into for collecting data. Because I always tell people part of the reason Harvard Data Science Review really wants to reach out to the NGO space is because I realize that in terms of data collection, probably the NGO space is the hardest one because you will have the other side deliberately try to conceal the data. It’s just not a kind of, you know, ‘We don’t have enough data’ or ‘It’s a complicated problem.’ So, for the benefit of this particular audience and certainly for the general data science community, can you give some examples of the particularly challenging issues in terms of collecting good quality data?
António Vitorino: There are two different types of difficulties. One is in the field. You need to have a very efficient network so that you do not rely just on what you have been told, but you have a system to go to the field, to go to the places and be sure that you are collecting effective data and not just the data that someone wants you to see, which is sometimes biased in the origin. For that purpose, we are strengthening our regional offices’ capacity not just to collect the data and to bring the data together for a certain region, but also to improve the assessment of the quality of those data: where are the gaps and where are the data not really reliable. They can be considered as an estimation, but we need to do further fieldwork to better build our databases. So, it's a daily exercise, I must say, because we collect data daily. OK? Our DTM [Displacement Tracking Matrix] collects data every day and we publish them on a weekly basis, sometimes on a monthly basis, depends on the target. But we need to compare those data and to contrast those data with the reality in the field and with the feedback of the stakeholders, whether they are civil societies or member states.
Then we go to the second part: data can be very dangerous.
Xiao-Li Meng: I know that!
António Vitorino: I mean, they can create lots of political problems. So, we need also to take into consideration that the integrity of the data needs to be preserved because it’s also very tempting sometimes for some stakeholders to manipulate the data, to read things in the data that are not there and to simplify the use of data, losing part of the picture, and sacrificing the complexity of the data that we collect. So that’s why it’s so important for us to have our own capacity to analyze the data. We should not just be happy to provide figures. We need to provide figures with a framing, and the framing is the interpretation of the data and that interpretation needs to be also of quality. And we have set up internally an improved system of data quality control that the data that we produce will have to go through a number of criteria. I will not bother you with the enumeration of the list of criteria, but definitely it’s a crucial issue because we need timely data. That is very important. If you published data six months after the events, it's of no use. It’s historical; it might be important in the long run, but for the operational purposes that we need the data for, six months’ time delay is of no use. So, you need to have timely data and you need to have comparable data.
But, of course, then you take more risks, because if you collect data daily, the risks of missing something are bigger, higher. And then you need to put them into context. And that is a constant exercise that we do, both with our displacement tracking metrics and also our GMDAC [Global Migration Data Analysis Centre] in Berlin. And we will try to bring them together to make closer the relationship between data collection, data control, quality control, and data analysis for the purposes of spreading the data that we have collected. Well, it’s quite a challenging exercise, but I must say, very exciting.
Xiao-Li Meng: Oh, I can see that. I hope some data scientists or statisticians get excited about working in this area because this is like a whole minefield in terms of everything you need to do. If you don’t mind, I'm really interested in this, so, sorry that I’m adding more specific questions. In this incredible work you do into data collection, data analysis, do you rely on your internal team from IOM or do you work with member states? Do they have offices there? Do they work for you? And how do you work with member states who may or may not like what you are finding, such as, as you mentioned, all these political issues? How does the system work here? It’s incredibly interesting and challenging.
António Vitorino: Well, I have a few examples.
Xiao-Li Meng: Oh, OK. Great.
António Vitorino: Better disclosures were not very well received by the member states. But while we are an independent organization, we are in the UN system. So, when we had enumerated that in the settings, we don’t take parties. We do not politicize our work. And sometimes, some data that we make available to the public are unpleasant to the authorities. But we try to always engage with them in a positive and constructive way, explaining that there is no gain in hiding unpleasant realities. The problem is if you don’t do nothing with it. So, the problem is not in the reality. The problem is in responding to the reality, and the data helps people, helps institutions, helps governments to address the problems and have a strategy to solve those problems. Having said that, of course, when we publish sensitive data, we try to give advance notice of the data, not because we will change them—the data are the data—but because we do not want to be seen as taking institutions, wherever they are, by surprise. And so, it’s n ongoing conversation. But at the end of the day, data are data and they have to be fully respected in terms of the integrity of what we have collected.
We collected our data through the Displacement Tracking Matrix. But we work with a number of implementing partners in the field. And I’ll just give you an example. Very recently, we had five data enumerators in Palma, in northern Mozambique, in Cabo Delgado, and we had to set up our emergency operation to take them out of there when the attack from the fundamentalists started. So, we have people really, really on the frontline. And that is our source of collecting the data. And then we work at the country level and regional level to bring the data together and to provide the analysis that is necessary to be made. So, it's quite a demanding job and we rely also on other departments for analysis. If you see the World Migration Report—the World Migration Report is published by IOM, but to a large extent it is thanks to the partnership that we have with the private sector, with other UN agencies, and with the academic world. So, we have consultants and we develop a network of consultants also to test, and the data scientists to test our methods and our methodology and to test our data themselves.
Xiao-Li Meng: And I imagine that this whole COVID-19 pandemic probably has created particular challenges for both the data collection as well as your data analysis. You already have spoken some of the issues and challenges created by COVID-19, but I want to ask you what are these big challenges that you think will permanently affect the migration processes moving forward, because we all know COVID-19 is having lots of effects that are not temporary. They are fundamentally changing the way we live locally and globally. So, if you can speak to that, that’d be great.
António Vitorino: Yeah, absolutely. I mean, we do not know exactly how the world will look like when we get out of the pandemic, but we have already a few leads. One of them is that it’s clear that health has become a major concern and that we need to guarantee that there is health security to relaunch trade, human mobility, tourism, which is extremely important, and also migration. And so, we have been working together with the Migration Policy Institute in Washington, D.C., on how we can bring together border controls, health security, and guaranteeing nondiscrimination. These three elements will be key for the future. And I recall that after 9/11, we could not bring along some liquids because they were suspicious of being the source of possible terrorist attempts. Now it’s even more complex because you don’t bring anything with you—it’s your body that is under suspicion.
Xiao-Li Meng: Great point.
António Vitorino: The new profile is that you need to fully incorporate health controls in mobility and border management. This is quite a daring change because this will require investment in infrastructure, training and upscaling of the skills of the border guards and the migration managers, and this will require also that we do not discriminate according to the regions of origin. We might be confronted with the kind of mobility device where rich countries can adapt more quickly to the requirements of health border controls. But poor countries will have much more difficulty in finding the resources and the skills to be equally on the same level playing field, and we are working on that. We think that the solutions need to be found at the global level. It’s very demanding, very challenging, I know. But the International Health Regulations and the different regulators of air travel, maritime travel, and land border, land crossing, will have to come to a basic agreement that is nondiscriminatory, but at the same time guarantees security and safety both of those who travel and of the host communities who receive the travelers.
And my second concern is that, let’s be honest, this health crisis is generating a major social economic crisis. We see the drop in remittances to the countries of origin. We see that those who are more vulnerable in societies are losing their jobs first. We see that, of course, there is an economic recession, and we are all very much hoping for a recovery. But, in fact, we are confronted with social and economic environments that will be extremely of concern, especially for those who are more vulnerable: the migrants, the refugees, the internally displaced people. And during this year, we have seen how difficult it is to make the case that everybody should have access to universal health coverage services. And it’s not just a question of the services of the member states not being prepared. It’s also a question of persuading the migrants that they need to have the trust to attend those social services, especially health services. If you are an illegal migrant, you are always extremely afraid of getting in contact with a public authority, even if you guarantee that that’s for the good of their health. But there are obstacles, there are resistances, and there is a reluctance.
And thirdly—I’m sorry for being so long, but those are different strands—yes, there is a new window of opportunity to make better use of digital technology in all these areas that I have mentioned to you: mobility, bringing predictability to crossing the borders, and at the same time making available access to all services, even if in a remote way. And we have seen that in the crisis. For instance, visa issuance. Quite a large number of countries adopted digital platforms to issue visas. For instance, our interviews for refugees for resettlement. We have done them remotely. We have done them through the platforms online. For instance, services that can be provided, like counseling. This pandemic has had a very heavy mental health toll, especially for those who are more vulnerable. And we have set up a number of services to provide psychosocial support to the migrants in different languages, in languages that they can understand. So, I mean, digitalization is going to be a key feature for the future, which will raise a number of difficult issues like data protection, like privacy, like ethics. So, we are confronted with a very demanding agenda, but it’s inevitable that technology will have a key role to play in the future of mobility.
Xiao-Li Meng: Thank you so much. I wish we had another hour, because I really have a lot more questions about—you mentioned data privacy, data sharing, all these stuff, but unfortunately we have run out of time, and I want to respect your time. But I do have one more question if you don’t mind, particularly for both this audience, as well as for the broad data science community. Again, part of the reason that HDSR wants to engage with NGOs and with the UN is to try to bring to the journal and the data science community the kinds of problems and challenges that they can help to work on. So, my question to you is that if you have all the resources to hire all kinds of data scientists, what skills will you hire first, who would you hire, and what is your general advice for the data science committee? Say, ‘Hey, you should work on this because we have an urgent need there.’ Just whatever you can tell the data science community to motivate them and to express your wishes.
António Vitorino: Oh, well, be careful what you wish for, they say. Definitely, from my perspective, working on migration, I always underline to our interlocutors that migration is a very human process, and this human being is at the center of the process. And so, analyzing the phenomena of migration means collecting a set of data that are related to the human nature of the process itself. So, you need to bring together, connect the dots, for the drivers of mobility, for the vulnerabilities within the mobility, and for the challenges in integrating in the countries of destination. So, I think that if you just focus on one of the pieces, you can have very good data and you can get very good analysis—you do not have the full picture. You need to test your conclusions on your specialty with the conclusions of all the others in the different stages of the trajectory of migration. And so, if I have money, I will build multidisciplinary teams that will bring together specialities from all these trends. Because it’s their dialogues that can shed light on such a human phenomenon like migration. But OK, if you know someone who is willing to pay, please give them my phone number.
Xiao-Li Meng: We will work to help. And I just want to mention that your point about seeing the big picture, even if you have a good solution locally does not mean you can solve the big problem. It actually goes so well with the most recent issue of Harvard Data Science Review, where we talk about how the University now is building the School of Data Science. I invited various deans, provosts, and there’s two of them—and I think this will particularly speak to your point—both come from the engineering background. They are the systems engineers, so they emphasize that typically we have been talking about the two pillars of data science, which is computer science and statistics. But they point out that you need a third pillar, which is systems thinking. You really do need to think of everything as a system, like building an engineering system. And I think that your point is just extremely well taken. And I think I would tell these deans that they are absolutely right. We need to train our students to go beyond just thinking about this as just a qualitative-quantitative analysis, but really think about it as dealing with a whole system.
António Vitorino: Absolutely!
Xiao-Li Meng: So, thank you so much. And I think you are clearly leading to deal with the biggest system in the universe, which is the human ecosystem. That’s practically what your agency is doing, under your leadership. So, I’m truly grateful. This has been a fascinating conversation and thank you so much on behalf again of all the participants, as well as Harvard Data Science Review. And I appreciate it, and I hope also you at some point—I know you’re so busy—if you’re willing to write something for Harvard Data Science Review about the need from the data science community. And we will all work hard to help you and to help your agency.
António Vitorino: Thank you.
Xiao-Li Meng: Thank you so much.
António Vitorino: Thank you so much. It was a pleasure. Thank you. Bye-bye.
António Vitorino and Xiao-Li Meng have no financial or non-financial disclosures to share for this interview.
©2022 António Vitorino and Xiao-Li Meng. This interview is licensed under a Creative Commons Attribution (CC BY 4.0) International license, except where otherwise indicated with respect to particular material included in the interview.