A/75/590 decision-making processes and many other facets of border and immigration enforcement. 8. As a general matter, digital border technologies are reinforcing parallel border regimes that segregate the mobility and migration of different groups on the basis of national origin and class, among other things. Automated border controls are one example of these parallel border regimes in action. One submission offered the example of the introduction of “eGates” at Irish ports of entry, such as Dublin Airport, where e-passport holders from the European Union/European Economic Area and Switzerland can go through eGates on a “self-service” basis to clear immigration control. 6 The submission notes that “only certain nationalities can adopt the ‘self-service’ approach, and the nationalities included are affluent and white nations (with the exception of Japan)”. Non-nationals of the European Union/European Economic Area or Switzerland travelling from outside Ireland by air or sea must present themselves to an immigration officer upon arrival. 9. One facet of the digital border is the expansive use of biometrics or the “automated recognition of individuals based on their biological and behavioural characteristics”. 7 Biometrics can include fingerprint data, retinal scans, and facial recognition, as well as less well-known methods such as the recognition of a person’s vein and blood vessel patterns, ear shape, and gait, among others. Biometrics are used to establish, record and verify the identity of migrants and refugees. The United Nations, for example, has collected the biometric data of over 8 million people, most of them fleeing conflict or needing humanitarian assistance. 8 Researchers have documented the racialized origins of biometric technologies, 9 as well as their contemporary discriminatory operation on the basis of race, ethnicity and gender. 10 A recent report on facial recognition technology deployed in border crossing contexts, such as airports, notes that despite the fact that even the best algorithms misrecognize black women twenty times more often than white men, the use of these technologies is increasing globally. 11 As that report notes, “where facial recognition is applied as a gate-keeping technology, travellers are excluded from border control mechanisms on the basis of race, gender and other demographic characteristics (e.g. country of origin)”. The frequent results of this differential treatment include perpetuation of negative stereotypes, and even prohibited discrimination which for asylum seekers might lead to refoulement. 10. Examples below show that governmental and humanitarian biometric data collection from refugees and migrants has been linked to severe human rights violations against these groups, notwithstanding the bureaucratic and humanitarian justifications behind the collection of this data. Furthermore, it is unclear what happens to this collected biometric data and whether affected groups have access to their own data. The World Food Programme (WFP), for example, has been criticized for partnering with data mining company Palantir Technologies for a $45 million contract, raising risks around data processing, security and responsibility regarding the 92 million aid recipients’ data managed by WFP. 12 Private corporations such as __________________ 6 7 8 9 10 11 12 6/25 Submission by the Immigrant Council of Ireland. See www.biometricsinstitute.org/what-is-biometrics/. These enormous data sets are notoriously hard to track and can also include the retrofitting of old data with newly collected biometrics. See, for example, http://humanitarian-congressberlin.org/2018/. See, for example, Simone Browne, Dark Matters: On the Surveillance of Blackness (Duke University Press, 2015). See A/HRC/44/57. Tamir Israel, “Facial recognition at a crossroads: transformation at our borders and beyond” (September 2020). See www.thenewhumanitarian.org/news/2019/02/05/un-palantir-deal-data-mining-protectionconcerns-wfp. 20-14872