Recent work in Human-Computer-Interaction (HCI) and Science and Technology Studies (STS) argues that improving our relationship with nature demands designing for nature as plural and multiple. This means moving beyond approaches that impose one version of what nature is, toward sustaining its different enactments and relationships. This paper examines how such ontological multiplicity can be sustained through design. Drawing on Mol’s ontological multiplicity and Stengers’ scene-setting, we present the Toronto Water Atlas, a seven-month design project involving artists, scientists, and community members. Through workshops and coworking sessions, we experimented with various design choices that surfaced and sustained multiple enactments of water, in direct contrast with singular formulations of water prevalent in informatics used for policy and planning. Through this work, we draw attention to the infrastructural biases that restrict ontological multiplicity, and demonstrate how design can more deliberately sustain diverse water ontologies by staging conditions for partial, and relational enactments.

As the Earth's temperature continues to rise, increasing investments are being made to develop artificial intelligence (AI) technologies to address the current climate crisis.Through interviewing 19 participants-comprising climate and environmental advocates and developers of AI for sustainability in the US and Canada-we examine how advocates perceive and use these technologies, and how their perspectives converge and diverge from practitioners developing AI for sustainability.We identified three key findings: 1) while approaches differ, developers and advocates expressed care for people and the planet; 2) the developers' and advocates' values and perceptions of AI technology varied, especially around ethical issues; and 3) developers and advocates had distinct approaches to using and designing AI and digital tools.Our findings, guided by a climate justice lens, underscore the need for decision-makers to: engage with advocates from intended beneficiary communities early in the design process; prioritize the urgency of the climate crisis; and emphasize the tangible environmental and societal impact of digital systems.

This design fiction proposes a panel session in the near future having environment and climate advocates share their stories of using artificial intelligence (AI) in their work. This work explores how the development of an embodied river persona, a farming assistant app, and a community hazard mapping tool could pose challenges and aid successes to respective local communities. Our design fiction highlights issues of design and development challenges that local organizations might face in a varied AI development for the environment. We explore questions around incorporating traditional knowledge, ethical participatory design models, and challenges of implementing and sustaining tools. Our work demonstrates how design fiction might be used to imagine AI for the climate challenge that considers people, place, and community.

Trans activists play a deeply important role in caring for and advocating for the transgender community using data. Through an interview study with 16 trans activists working in trans-led and trans-serving organizations in the United States, we document how they use restorative/transformative data science processes of resolving, researching, recording, and refusing and using data. We incorporate their data practices with trans technology and trans competent interaction design approaches to propose a research agenda for trans data : materially improve trans lives, cross data boundaries, and constantly engage in power analysis. We expound on how a trans data research agenda can benefit data advocacy and CSCW research and design.

This paper analyzes the current practices of Indigenous data sovereignty in environmental research and activism in the United States, as known by the settler government. The CARE principles are a widely adopted set of guidelines for Indigenous data sovereignty with guidelines being collective benefit, authority to control, respect and ethics, yet there exists little detail on current practices of operationalization and implementation of the CARE principles. This research specifically identified opportunities to further clarify how environmental data can be managed in accordance with the CARE principles. Using current literature, we examine how sustainability and Human-Computer Interaction (HCI) research could better incorporate Indigenous data sovereignty and governance. Through three interviews with Indigenous environmental practitioners, we use inductive and deductive analysis to understand current thoughts and practices. In a forestry analysis case study with the Penobscot Nation, we examine specifically how the CARE principles could be implemented into a research project. The interviews and case study reveal design considerations such as emphasizing roles in responsibility and ethics to be taken into future HCI research involving Indigenous data sovereignty in environmental contexts.

After criminal recidivism or hiring machine learning mod-els have inflicted harm, participatory machine learning meth-ods are often used as a corrective positioning. However, lit-tle guidance exists on how to develop participatory machinelearning models throughout stages of the machine learningdevelopment life-cycle. Here we demonstrate how to co-design and partner with community groups, in the specificcase of feminicide data activism. We co-designed and piloteda machine learning model for the detection of media arti-cles about feminicide. This provides a feminist perspectiveon practicing participatory methods in a co-creation mind-set for the real-world scenario of monitoring violence againstwomen.