User interfaces – on the web, standalone apps, or internal systems – are now central to the design and operation of the welfare state, with profound implications for access to legal entitlements and the exercise of administrative discretion. While socio-legal scholars have begun to examine how interfaces mediate state-citizen relations, research has been constrained by limited access to these systems. This paper applies a novel socio-legal methodology to analyse prototypes developed by software engineers working in the UK’s welfare administration by drawing on the Department for Work and Pensions’ (DWP) GitHub account – a platform where the DWP’s digital team stores, manages, and shares code on an almost daily basis across more than 500 repositories. By analysing this code, this paper moves beyond the handful of public-facing examples that have dominated scholarship to date to present a new account of how digital interfaces mediate access to legal entitlements. The analysis reveals three interlinking patterns: (i) ‘happy path’ processing that assumes ideal user journeys; (ii) prompting and priming mechanisms that shape decision-making; and (iii) interfaces designed specifically for official workforce management and control. This paper argues that these findings have significant implications for socio-legal analyses of public services and administrative justice in digital contexts.

We present a novel and trainable gesture-based system for next-generation intelligent interfaces. The system requires a non-contact depth sensing device such as an RGB-D (color and depth) camera for user input. The camera records the user's static hand pose and palm center dynamic motion trajectory. Both static pose and dynamic trajectory are used independently to provide commands to the interface. The sketches/symbols formed by palm center trajectory is recognized by the Support Vector Machine classifier. Sketch/symbol recognition process is based on a set of geometrical and statistical features. Static hand pose recognizer is incorporated to expand the functionalities of our system. Static hand pose recognizer is used in conjunction with sketch classification algorithm to develop a robust and effective system for natural and intuitive interaction. To evaluate the performance of the system user studies were performed on multiple participants. The efficacy of the presented system is demonstrated using multiple interfaces developed for different tasks including computer-aided design modeling.