Challenge Cluster 2: Digitalisation and Datafication
As digitalisation continues to reshape many aspects of daily life and work, it presents some distinct challenges within the context of international protection. Scenarios examined how digital technologies offer improvements to speed of information transfer, remote work, data processing and analysis, and other efficiencies, alongside the new challenges they present. Major challenge areas include a rapidly changing technological landscape, scarce and expensive human resources, inconsistent database quality, non-standardised interoperability, an uncertain regulatory environment and increasing cybersecurity risks. The various implementations of Artificial Intelligence, the quality of data is relies on, and different regulatory environments, are important challenges examined across all scenarios. Furthermore, defining the boundaries between automated support systems and human decision-making is a critical challenge that is partially determined by data reliability and regulatory environment.
Global differentiation of data standards, platforms, social media and the increasing fragmentation of the internet are challenge areas considered across numerous scenarios. These are accompanied by increasing use of surveillance technologies - by different types of actors and for different purposes - befitting scenario conditions. A resilient digital strategy in the area of international protection requires observation of these developments and the build-up of competences for different “digital spheres”. Additionally, an increasing digital divide among refugees, and discrimination against asylum seekers based on these differences is a challenge requiring explicit consideration by international protection agencies.
Noted Challenges
- Ensuring that the international protection institutions can develop the knowledge, skills and capacities needed to continue progress on digitalisation given limited budgets and a rapidly developing technological landscape.
- The rapidly changing technological landscape makes it difficult to identify the best technology for any given task, that is durable and adaptable so as to maintain viability over a time horizon that justifies expenditures.
- It demands continuous (often expensive) training and skills acquisition by the workforce.
- It creates competing standards that can negatively impact interoperability, database reliability and broader adoption by partners or collaborators
- Artificial Intelligence systems and technologies require highly specialised skills to program, test and validate. Given the popularity of artificial intelligence, these human resources can be difficult and expensive to retain.
- Effective automated systems require large databases of highly structured and verified data to ‘train’ on as well as databases with non-uniform structures. Incomplete or misconfigured entries can introduce various types of bias.
- Increased reliance on digital network technologies leaves essential workplaces and processes at risk of facing increased cybersecurity threats. This is a global phenomenon, with cyberattacks being both state-sponsored and criminal initiatives.