Chris Speed

Dan Ruta, Andrew Gilbert, Pranav Aggarwal et al.

We present StyleBabel, a unique open access dataset of natural language captions and free-form tags describing the artistic style of over 135K digital artworks, collected via a novel participatory method from experts studying at specialist art and design schools. StyleBabel was collected via an iterative method, inspired by `Grounded Theory': a qualitative approach that enables annotation while co-evolving a shared language for fine-grained artistic style attribute description. We demonstrate several downstream tasks for StyleBabel, adapting the recent ALADIN architecture for fine-grained style similarity, to train cross-modal embeddings for: 1) free-form tag generation; 2) natural language description of artistic style; 3) fine-grained text search of style. To do so, we extend ALADIN with recent advances in Visual Transformer (ViT) and cross-modal representation learning, achieving a state of the art accuracy in fine-grained style retrieval.

Dave Murray-Rust, Chris Elsden, Bettina Nissen et al.

This paper presents an annotated portfolio of projects that seek to understand and communicate the social and societal implications of blockchains, distributed ledgers and smart contracts. These complex technologies rely on human and technical factors to deliver cryptocurrencies, shared computation and trustless protocols but have a secondary benefit in providing a moment to re-think many aspects of society, and imagine alternative possibilities. The projects use design and HCI methods to relate blockchains to a range of topics, including global supply chains, delivery infrastructure, smart grids, volunteering and charitable giving, through engaging publics, exploring ideas and speculating on possible futures. Based on an extensive annotated portfolio we draw out learning for the design of blockchain systems, broadening participation and surfacing questions around imaginaries, social implications and engagement with new technology. This paints a comprehensive picture of how HCI and design can shape understandings of the future of complex technologies.

Kami Vaniea, Ella Tallyn, Chris Speed

Based upon a study of how to capture data from Internet of Things (IoT) devices, this paper explores the challenges for data centric design ethnography. Often purchased to perform specific tasks, IoT devices exist in a complex ecosystem. This paper describes a study that used a variety of methods to capture the interactions an IoT device engaged in when it was first setup. The complexity of the study that is explored through the annotated documentation across video and router activity, presents the ethnographic challenges that designers face in an age of connected things.