This article examines the organisation of collaborative digital methods and data projects in the context of engaged research-led teaching in the humanities. Drawing on interviews, field notes, projects and practices from across eight research groups associated with the Public Data Lab (publicdatalab.org), it provides considerations for those interested in undertaking such projects, organised around four areas: composing (1) problems and questions; (2) collectives of inquiry; (3) learning devices and infrastructures; and (4) vernacular, boundary and experimental outputs.Informed by constructivist approaches to learning and pragmatist approaches to collective inquiry, these considerations aim to support teaching and learning through digital projects which surface and reflect on the questions, problems, formats, data, methods, materials and means through which they are produced.
MULTIFILE
Growing research in sign language recognition, generation, and translation AI has been accompanied by calls for ethical development of such technologies. While these works are crucial to helping individual researchers do better, there is a notable lack of discussion of systemic biases or analysis of rhetoric that shape the research questions and methods in the field, especially as it remains dominated by hearing non-signing researchers. Therefore, we conduct a systematic review of 101 recent papers in sign language AI. Our analysis identifies significant biases in the current state of sign language AI research, including an overfocus on addressing perceived communication barriers, a lack of use of representative datasets, use of annotations lacking linguistic foundations, and development of methods that build on flawed models. We take the position that the field lacks meaningful input from Deaf stakeholders, and is instead driven by what decisions are the most convenient or perceived as important to hearing researchers. We end with a call to action: the field must make space for Deaf researchers to lead the conversation in sign language AI.
LINK
The design of cities has long ignored the flows that shape the city. Water has been the most visible one, but energy and materials were invisible and/or taken for granted. A little over 50 years ago, Abel Wolman was the first to illuminate the role of water flows in the urban fabric. It has long been a search for quantitative data while the flows were mostly seen as separated entities. The fact they invisibly formed the way the city appears has been neglected for many years. In this thematic issue the “city of flows” is seen as a design task. It aims to bring to the fore the role flows can play to be consciously used to make spatial decisions in how and where certain uses and infrastructure is located. Efficient and sustainable
DOCUMENT
