UK's sweeping asylum law changes: How will they impact refugees? Shabana Mahmood, the United Kingdom's home secretary, has said the country's asylum system is "not working" and is placing "intense strain on communities" ahead of proposals for major government reforms that would end refugees' automatic right to settle permanently in the UK. Speaking to the BBC on Sunday, Mahmood said undocumented migration is "tearing the country apart". First, they would end the automatic path to settled status for refugees after five years. And second, they would remove state benefits from those who have the right to work and can support themselves.

-- Social robots are increasingly being deployed in public spaces, where they face not only technological difficulties and unexpected user utterances, but also objections from stakeholders who may not be comfortable with introducing a robot into those spaces. We describe our difficulties with deploying a social robot in two different public settings: 1) Student services center; 2) Refugees and asylum seekers drop-in service. Although this is a failure report, in each use case we eventually managed to earn the trust of the staff and form a relationship with them, allowing us to deploy our robot and conduct our studies. We have developed a multilingual robot system (Figure 1) described in [1] for two different use cases: 1) Supporting newly arrived international students in a UK university, answering frequently asked questions; 2) Supporting refugees and asylum seekers with navigating bureaucratic processes. Like most current public-space robot deployments, our field studies involved adding a robot to an existing workplace, with stakeholders including management, visitors, as well as front-line workers who should all be consulted to develop the details of the system to be deployed.

Officials are to start using artificial intelligence to help estimate the age of asylum seekers who say they are children. Angela Eagle, the immigration minister, said on Tuesday the government would test technology that judges a person's age based on their facial features. It is the latest example of Labour ministers turning to AI to help solve problems with public services without spending significant amounts of money. The decision was announced on the same day that David Bolt, the chief inspector of borders and immigration, published a highly critical report into the haphazard way in which officials estimated the age of new arrivals. Eagle said in a written statement to parliament: "We have concluded that the most cost-effective option to pursue is likely to be facial age estimation, whereby AI technology – trained on millions of images where an individual's age is verifiable – is able to produce an age estimate with a known degree of accuracy for an individual whose age is unknown or disputed.

The claims could have been taken word-for-word from any one of numerous US far-right websites in recent months. "Reports are surfacing suggesting that [lawmakers] may have been involved in transporting large numbers of refugees and immigration applicants to polling stations to secure votes for individual candidates," the author of the article claimed. This wasn't a conspiracist asserting that Honduran migrants are being imported into the US to replace swing-state Republican voters, though; the claim came from a website called The Irish Channel. A new report published on Tuesday by researchers at the Institute for Strategic Dialogue outlines how the website has used generative AI to create articles that have been "heavily influenced by similar election denial efforts in the US." The anti-immigrant narrative, based on made-up quotes and fabricated academics, is just one of the conspiracies imported wholesale into Ireland from the US in recent months.

This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year randomized control trial in Switzerland, seeks to maximize the average predicted employment level (or any measured outcome of interest) of refugees through a minimum-discord online assignment algorithm. The performance of this algorithm is tested on real refugee resettlement data from both the US and Switzerland, where we find that it is able to achieve near-optimal expected employment compared to the hindsight-optimal solution, and is able to improve upon the status quo procedure by 40-50%. However, pure outcome maximization can result in a periodically imbalanced allocation to the localities over time, leading to implementation difficulties and an undesirable workflow for resettlement resources and agents. To address these problems, the second algorithm balances the goal of improving refugee outcomes with the desire for an even allocation over time. We find that this algorithm can achieve near-perfect balance over time with only a small loss in expected employment compared to the employment-maximizing algorithm. In addition, the allocation balancing algorithm offers a number of ancillary benefits compared to pure outcome maximization, including robustness to unknown arrival flows and greater exploration.

The way the UK government has been tagging migrants with GPS trackers is illegal, the country's privacy regulator ruled on Friday, in a rebuke to officials who have been experimenting with migrant-surveillance tech in both the UK and the US. As part of an 18-month pilot that concluded in December, the UK interior ministry, known as the Home Office, forced up to 600 people who arrived in the country without permission to wear ankle tags that continuously tracked their locations. However, that pilot broke UK data protection law because it did not properly assess the privacy intrusion of GPS tracking or give migrants clear information about the data that was being collected, the UK's Information Commissioner's Office (ICO) said today. The ruling means the Home Office has 28 days to update its policies around GPS tracking. Friday's decision also means the ICO could fine the Home Office up to 17.5 million ( 22 million) or 4 percent of its turnover--whichever is higher--if it resumes tagging people who arrive on the UK south coast in small boats from Europe.

In various real-world settings, however, we might expect shifts to arise through the superposition of many small and random changes in the population and environment. Thus, we consider a class of random distribution shift models that capture arbitrary changes in the underlying covariate space, and dense, random shocks to the relationship between the covariates and the outcomes. In this setting, we characterize the benefits and drawbacks of several alternative prediction strategies: the standard approach that directly predicts the long-term outcomes of interest, the proxy approach that directly predicts a shorter-term proxy outcome, and a hybrid approach that utilizes both the long-term policy outcome and (shorter-term) proxy outcome(s). We show that the hybrid approach is robust to the strength of the distribution shift and the proxy relationship. We apply this method to datasets in two high-impact domains: asylum-seeker resettlement and early childhood education. In both settings, we find that the proposed approach results in substantially lower mean-squared error than current approaches.

In this study, we introduce a novel two-pronged scoring system to measure individual and systemic bias in immigration courts under the U.S. Executive Office of Immigration Review (EOIR). We analyze nearly 6 million immigration court proceedings and 228 case features to build on prior research showing that U.S. asylum decisions vary dramatically based on factors that are extraneous to the merits of a case. We close a critical gap in the literature of variability metrics that can span space and time. Using predictive modeling, we explain 58.54% of the total decision variability using two metrics: partisanship and inter-judge cohort consistency. Thus, whether the EOIR grants asylum to an applicant or not depends in majority on the combined effects of the political climate and the individual variability of the presiding judge - not the individual merits of the case. Using time series analysis, we also demonstrate that partisanship increased in the early 1990s but plateaued following the turn of the century. These conclusions are striking to the extent that they diverge from the U.S. immigration system's commitments to independence and due process. Our contributions expose systemic inequities in the U.S. asylum decision-making process, and we recommend improved and standardized variability metrics to better diagnose and monitor these issues.

Tijuana, Mexico – Standing in a common area of the Casa del Migrante shelter in the Mexican border city of Tijuana, Maria taps her phone screen but can't get the app she is using to work. Maria and her family fled their native Haiti to Venezuela years ago. But recent Venezuelan economic and political instability forced them to leave that country, too, and she said they are now hoping to apply for asylum in the United States. But she and her husband and daughter have tried every day for the last month to get a US immigration appointment through the country's new CBP One app -- to no avail. And without a CBP One appointment, the family faces steep consequences should they try to cross the border irregularly, including being deported back to Haiti and barred from entering the US for up to five years.

The Home Office plans to use artificial intelligence to reduce the asylum backlog, and is launching a three-day hackathon in the search for quicker ways to process the 138,052 undecided asylum cases. The government is convening academics, tech experts, civil servants and business people to form 15 multidisciplinary teams tasked with brainstorming solutions to the backlog. Teams will be invited to compete to find the most innovative solutions, and will present their ideas to a panel of judges. The winners are expected to meet the prime minister, Rishi Sunak, in Downing Street for a prize-giving ceremony. Inspired by Silicon Valley's approach to problem-solving, the hackathon will take place in London and Peterborough in May.