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Hello and welcome to another episode of the Migration Ocean Podcast.

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I'm Rob McNeil and I'm Jackie brought out. So today Jackie has been talking to two experts on the use of artificial intelligence

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and other modern forms of technology in the management of rivals in Europe.

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So, Jackie, what made you want to talk about this?

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Thanks, Rob. I feel like AI is kind of everywhere at the moment, from chatty through to, you know,

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even within the university, how it might kind of impact teaching and learning here.

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And so it felt really important to kind of hear a little bit about what's been happening within migration governance,

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both processes that been going on for a long time as ever with these things.

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You know,

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you think it's the kind of new big thing and it actually turns out that some some of the things have been happening a kind of much longer processes.

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But hearing about some of the new technologies in the way that genuinely they are impacting on decision making and migration governance.

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One of the questions for me is, I mean, is there a problem? I mean, is it wrong to use modern technology to try and understand who's arriving,

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what kind of risk they pose to people and for governments to to to try to ensure that they've got

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the most efficient mechanisms possible to assess people's claims and to deal with things quickly?

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Yeah, I mean, one of my favourite programs is Mad Men,

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and there's a line that Don Draper says in that way he he says, What if change is neither good nor bad?

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It just is. And that's something that I thought about quite a lot in this discussion,

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which is is it's the tools themselves that are the issue or this kind of systems that they're going into.

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I think one of the really interesting points in the discussion is if they are going into a system that contains inequalities, biases, discrimination,

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they have the possibility to amplify and replicate that form of discrimination,

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and particularly because they allow decisions to be made much quicker than humans might make decisions with fewer moments for reflection.

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You know, are we walking into a situation where actually we're going to see these kind of biases replaced on a much larger scale?

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But I also think it's something about the moment that we're at.

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It's true that these technologies have been around for a while, but this does feel like quite a transformative moment.

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And that means that policymakers and governments are kind of writing the rules of the game.

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And at the moment that we're writing those rules,

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it's probably a good idea for us to be having conversations about what we want these types of decisions to be,

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how much we want human judgement as part of them, you know, as opposed to kind of predictive,

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you know, how much we want to be If we were making an application for a visa or for asylum,

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how much we would want that to be done by a person looking at kind of us versus it being done on a kind of predictive algorithm.

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All of these sorts of huge questions I think is kind of grappling with are also come into play

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within migration governance and are happening both for us as citizens in deciding what's acceptable,

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what might not be acceptable, and then also within governments.

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So, I mean, there's a question here in that case about just allocation of resources and the scale of situations.

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I mean, the UK obviously at the moment, I mean,

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one of the things that we we talk about all the time is this massive backlog in the asylum and the asylum system in the UK.

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That's largely a facet of the slow processing of claims by by decision makers.

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Now I mean surely removing a degree of the kind of of human biases from decision making is is arguably a good thing sometimes, isn't it?

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I mean, it's not to say that, it's not to say that automating processes is a perfect solution,

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but if you've got a situation which is increasing consistently in scale, don't we need technologies like this Sometimes?

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There's some really interesting examples within the discussion of the kind of tools that have been used.

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One of the things that really struck me,

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particularly about asylum is that the tools that are being discussed are actually tools that then will aid human decision makers.

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So and there's a really interesting example about dialects that that that we chat about and it's, you know,

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what are the kind of skills that those decision makers have to be able to kind of deal with this new information that they're getting through.

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And it also really reminded me of some fantastic research that Lena Rose, who was formerly of this parish, now elsewhere, did,

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looking at the way that we make credibility decisions and the fact that these are such incredibly complex

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and kind of sophisticated decisions on a human level about somebody's well-founded fear of persecution,

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for example, and the extent to which we are able to understand the kind of new information that's.

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Coming in. Whether that is supportive of better decision making or in fact, you know,

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whether it's just kind of adding to what kind of pile of information and making those decision making process is actually much more difficult.

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I feel like we haven't necessarily just got to grips with the complexity of of making asylum decisions.

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And then we're adding this kind of whole extra layer on to it.

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I think your point about actually this could remove some of the biases is really interesting,

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and I think it's something that could be explored a lot further.

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I know a lot of the worry around A.I. is that it far from removing biases, it kind of amplifies those biases because of the way that it's trained.

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As a AI, to my layperson's understanding is kind of trained on the stuff that is already out there.

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And if the stuff that's already out there contains these these pre-existing biases, then it is also going to have those.

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So that's one of the ways in which it kind of becomes almost a little bit more human.

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So I think I just feel like these are incredibly interesting and important discussions

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and the fact that this is not something that we're projecting forward into the future.

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These are technologies that are being used right now. And so it's a discussion that that should be had.

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In the same way that air is trained and learns so to people.

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I mean, like air is not the only thing that learns. And so, I mean, we're constantly going to be in a situation surely,

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where there has to be a balance struck between the way that people learn how to how to either

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use the system or to manipulate a system or to play a system against the kind of the against

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the sort of the idea of the perfect decision making process that may exist either with humans

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making solid sound choices based on complete understanding of a situation which is never there,

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or machines doing something based on perfect automated system.

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There's always got to be some kind of of balance between these things.

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I'm joined by Derek Ozekhome, senior research fellow at the Refugee Study Centre at the University of Oxford, and Catarina Ridley.

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EU Policy Analyst Access now. Daria, we hear so much about how I might transform our lives.

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Can you tell us about some of the ways in which it might transform and is already transforming migration governance?

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Yes. So yeah, we started hearing more about A.I. when it started impacting our lives.

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So, for example, AI is transforming the workforce with many types of jobs now being automated.

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But it's also used in many other areas, including migration.

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And we see various practices that state authorities have started using on migrants.

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So right now from in fact, from the moment that someone thinks about even a migrant,

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the possible migrant thinks about even migrating to somewhere else.

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There are data that Google searches on the news that they're looking for are all being recorded and monitoring monitors.

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And so, for example, predictive analytics systems helps states to forecast the number of arrival of migrants on their borders.

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And then these systems can then lead to more increased border controls and push backs of people who may need protection.

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We also see a variety of other types of new technologies being used.

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For example, drones or various types of sensors in border areas for surveillance purposes, apart from those in recent years.

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Several states have started using new technologies to automate some of their casework processing.

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So these are often in the form of automated systems that take inputs from other databases.

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So, for example, in Norway, the immigration authority has automated the processing of citizenship applications.

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And the way that they can do that is they,

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by taking data from that is already available against that individual from all the databases that they have,

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and then checking whether the person fulfils all the requirements to become a citizen.

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So the process can be fully automated if they have enough data about a person, basically.

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But just the more dangerous form of automation in this field is when immigration authorities are using what is called risk assessment systems.

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And we have seen these types of systems, for example, in the UK or in Netherlands as well.

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In the UK case, thanks to huge efforts from civil society,

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it has been found that applications from certain nationalities were automatically categorised as

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high risk and that those applications were receiving a higher level of scrutiny from officers.

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The civil society organisations, particularly the Joint Council for the Welfare of Immigrants and Foxglove as well,

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They found that the system had also a feedback loop problem,

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which means that applications from a certain nationality being rejected at a

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higher rate will also influence future applications from that nationality.

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So obviously these types of systems can create discrimination on the basis of nationality and it's quite risky and important to monitor them.

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Absolutely. It's amazing how much is already happening.

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Catarina There are some big changes that are happening at EU level, but not seemingly with very much regulation.

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Can you tell us about how some of the technologies that debris are talked about are changing things in the Schengen

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zone and and why we might want to kind of regulate things to reduce some of the discrimination that we've heard about?

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Yes. Thank you. So I think that's an important starting point for orientate ourselves.

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And this discussion is to reflect on the fact that new technologies in the era of EU migration policies are not that new.

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And in fact, they were actually rolled out and developed together with the new design of migration policies in the nineties.

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So in the nineties the Schengen area was, was started with 95,

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the abolishment of internal frontiers between European Member States and the a new European common external frontier was developed.

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What civil society nowadays calls fortress Europe and digitalisation of borders and technology was since the beginning,

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since the get go crucial for the functioning of Fortress Europe, the first large scale database.

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In fact the Schengen Information System was deployed in 95 and it had the purpose of

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facilitating police cooperation among Member states as well as border management.

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And it had information on different categories of people such as missing persons or people wanted for

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arrest in the same way for an implementation of the Dublin Regulation at the beginning of the 2000 stadia.

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That database was implemented and the Europe that year.

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That database holds in source biometric information on asylum seekers,

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and it's fundamental for an implementation of the Dublin Regulation that should support Member States

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in distributing asylum seekers that arrive at the first countries at the European southern border.

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Usually this is important to say that technology was key from the beginning and is important for implementing punitive

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migration policies that are very much focussed on enforcing deportation or impeding people from entering the European Union,

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even outside of the European borders. For example, in embassies, while a request applying for a visa, as there was explained before.

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And if we look at the European policy landscape,

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there is a variety of different legislations that have allowed for the introduction of different technological solutions.

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We have European, we have we have migration policies such as policies,

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regulations that underpin migration databases such as fear that this which is a database for the information sharing on visas,

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the Schengen Information systems and others. But we also have a regulation about interoperability of all of these migration databases.

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We have the new pact on asylum and migration that allows for the introduction of new technology, but we also have regulations on other type of labour,

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such as digital policies such as the Artificial Intelligence Act that also regulates the use of technology in the migration context.

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We also have it in the context of law enforcement, such as the Europol regulation,

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that allows for more power for police forces to use air based systems and surveillance technology,

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and also legislations or initiatives about funding that allow for the money to invest on these type of technologies.

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Thanks, Katerina. Daria, I am really interested in this difference between some of the processes that Catarina has spoken about,

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which I guess are around surveillance and collecting information and some of them that are kind of predictive and about making decisions.

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And one of the areas that we know where policymakers have to make huge decisions is in the asylum process,

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deciding whether somebody has a kind of well-founded fear of persecution.

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And if you could tell us a little bit about how these technologies are affecting the asylum system,

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both for asylum seekers themselves and also for the people making the decisions.

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So in asylum decision making, we see we can see the introduction of some of the new technologies not to automate the decision,

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the whole process itself, but to automate some of the evidence that is used in decision making.

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So for example, one of them is used to determine the applicant's identity.

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The immigration authority in Germany has been using this what is called a dialect recognition tool to identify the applicant's language.

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So this technology. It's quite very much like all the types of biometric technologies.

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It can identify a person's voice data in terms of percentages.

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So it generates the report basically saying that this person speaking speaks 64%, 17 Arabic and 16% golf Arabic and so on.

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And it's really fundamentally I mean,

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this this particular technology is fundamentally changing the way language is assessed in asylum decision making, whereas in previously it was used,

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obviously it was always human linguists doing these kind of analysis, and they were recommended to make a qualitative analysis of a person's language.

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So they would say, okay, this person is very likely speaking Lebanese in Arabic and then leave it there,

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whereas this new technology is giving percentages and is changing how then the

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decision maker is perceiving the applicants because it's 60 44% levels in Arabic,

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but that not so much the rest and so on.

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And another technology that is used more widely is mobile phone data extraction.

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So a number of countries in Europe and elsewhere, such as Germany and Netherlands, for example,

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in Europe, have introduced this technology again to determine the applicant's identity,

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but also to identify their travel route and then use that as an evidence to determine whether or not the person is telling the truth.

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So it's of course, this technology is very invasive to the person's private life, extracting all the data available on their mobile phone.

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But also, research in this area shows us that mobile phones are often exchange among migrants.

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They can be sold. They can be just used by their friends and family members.

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And all types of contradictions that come out from that can potentially be

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used against the applicant's credibility during the decision making process.

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So overall, we see that these technologies really create additional grey areas for applicants to address during the interview process.

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Thanks so much, Terry.

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And Katrina, the Protect Not Surveil campaign is looking to make a human rights based argument for regulating some of these forms of new technologies,

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but it also banning some others, including some of the kind of predictive and profiling systems that we've talked about.

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Can you explain why the campaign is so worried about these forms of profiling

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and and what areas actually shouldn't be used in migration governance at all,

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in your view? Yes, The particular survey campaign fits into a progressive society effort to throw some red lines on the

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use of artificial intelligence based systems in a way that irreversibly violates fundamental rights.

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And we see that in the migration context.

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People on the move and third country nationals are usually used as the testing ground for some type of technology.

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So it's crucial that they are found some type of systems that should be banned not only relate to poor fighting type of systems,

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but also systems that amount to biometric mass surveillance.

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So there is a called for a ban on remote biometric identification systems that could identify people in in on a remote basis

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and that could be used outside detention centre or at the borders to identify people that might have their biometric data,

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really not the basis systems such as the motion recognition systems that claim

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to infer the emotional status of a person's from their facial micro gestures.

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And that reinforces this to make the suspicious suspicion against non European citizens and then profiling systems as the area was explained before,

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these systems that claim to assess the risk that a person posts are inherently biased.

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The example that Dario was making before from the UK,

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but also from the Netherlands of automated risk assessment used in the context of three ageing visa applicants.

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Well, these type of systems are assessing how much the person might pose a risk to either

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public security or at risk to overstay or their visa based on some categories

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that are predetermined by some people that by nature cannot be objective because

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they build a system of risks that is embedded in some specific assumptions.

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So when it comes to risk assessments, you have some risk indicators that are pre-decided.

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So some categories that are decided to be a factor of risks, for example, country of origin or level of education or type of employment.

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And then for each risk indicator, a screening rule is associated.

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So for each indicator, a different, the risk rate will be calculated.

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So in the case of the Netherlands, for example, in the Three Eyes system for visa application,

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applicants from Suriname were systematically received systematically a higher score when it comes to the risk based on the country of origin.

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And the same went with the case from the UK.

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Applicants coming from certain African countries were systematically receiving a higher score when it came to the risk indicator of country of origin.

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But the same could apply also for level of education.

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When people go to universities that have religious background, they might receive a higher score when their university is Muslim.

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University could give this idea that it's related to Muslim affiliation and there are many other thought of examples.

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So providing systems as well as other type of systems that protect not surveyed is calling for it,

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but are all those type of systems that would reinforce systemic oppression and forms of discrimination under the guise of technical neutrality.

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A final question for you both.

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I guess a lot of this discussion is quite scary and difficult to hear about some of the risks in particular in relation to discrimination.

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But I wonder, are there any causes for optimism in terms of the use of these new technologies in the in the right hands?

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Do you think there could be any ways in which they could solve some of the long standing issues within migration governance?

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Is there any positive note on which we can end? Derek, I'll start with you though.

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Some of the technologies that we have mentioned, such as automated processing of visa applications,

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can of course bring benefits around speeds, but those benefits are not equal for all.

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So some applicants can, of course,

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received a speedier response to their applications in one day because it's automated and it's low risk and they receive a positive response.

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But others can be under more scrutiny and probably receive a rejection.

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But overall, we can see that most of these technologies have been designed in a way to benefit

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state authorities themselves to kind of ease and lessen their workloads.

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And they are not. I mean, the only way that they can be beneficial for migrants if they are,

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can it can happen if they are first thought about and designed out of migrants or needs.

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And we haven't mentioned in this talk, but there are some technologies that are designed, for example,

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to match refugees with municipalities and areas that are best for their future employment or specific needs.

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There is, for example, the Merchant Imagine project in Germany,

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which is trying to basically match refugees needs with municipalities capacities across the country.

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So that's a really good example of what technology can achieve if they centred around migrants and refugees needs themselves.

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But apart from this, I guess, I mean, we haven't talked about at all in this talk,

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but it's worth remembering that even if it's for the best intentions,

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every technology also brings new demands on natural resources and has consequences for the environment.

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So we really need to be always asking ourselves whether we really need them and whether this is really cannot be done any other way.

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Catarina Any grounds for optimism? I think I want to be the one to bring the optimism in this conversation,

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but because I don't think the the framework where this debate is has is happening is, is the one that we bring safer solutions.

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And I always think from the abolitionist movements,

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the idea that we don't need a reform in a system that is already is created to oppress certain people.

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So I don't think the question is around the positive use of technology, but about the policies themselves.

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Of course, the technology is not a problem. It's not a problem per say.

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We see some uses of technology, the same type of technology used in different contexts, for example, drones to detect people in distress.

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If you put it in the hands of Frontex, it can lead to the facilitation of pushback through the Libyan coast guard,

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whereas also the NGO Sea-watch is using drones to detect the presence of people that are escaping from Libya towards Italy.

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And these, based on the detection of the drone, will then look locate their their vessels to start the search and rescue mission.

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But the thing is that technology is always used by someone that is always advancing their own priorities.

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So when it comes to migration management, what needs to be done is rethink the whole infrastructure, the whole objectives behind the policies.

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And if we want to address the the problem of discrimination, the problem of violence that is happening also through the use of technology,

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we should be more bold and more courageous in calling for a systems that prioritise justice,

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that prioritise the ability and the freedom of people to move.

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And that doesn't. That's not tied beyond technologies or opaque systems that in a way, the responsibilities,

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the authorities that are in fact legalising very violent policies that are closing that I thought were and within our borders.

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So not only optimism, but for for sure, I believe there is a way to to improving that.

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And I would like to close to refer to a report.

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Very interesting that actually brings some optimism, which was written by the Equinox Project.

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And it's it's about Fortress Europe. And it actually details three ways in which we can challenge and change discriminatory EU migration policies.

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That seems like as good a place as any for us to leave it. Thanks so much to you both.

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You've been listening to the Migration Oxford podcast. I'm Robert Neill.

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And I'm Jacqui Broadhead.