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Collaboration across institutional boundaries is widespread and increasing today. It depends on federations sharing data that often have governance rules or external regulations restricting their use. However, the handling of data…
Sustainable global development is one of the most prevalent challenges facing the world today, hinging on the equilibrium between socioeconomic growth and environmental sustainability. We propose approaches to monitor and quantify…
In 2015, the United Nations put forward 17 Sustainable Development Goals (SDGs) to be achieved by 2030, where data has been promoted as a focus to innovating sustainable development and as a means to measuring progress towards achieving the…
To achieve the United Nations Sustainable Development Goals, coordinated action across their interlinked indicators is required. Although most of the research on the interlinkages of the SDGs is done at the goal level, policies are usually…
Designing sustainable medical devices requires balancing environmental, economic, and social demands, yet trade-offs across these pillars are difficult to identify using manual assessment alone. Current methods depend heavily on expert…
As AI/ML models, including Large Language Models, continue to scale with massive datasets, so does their consumption of undeniably limited natural resources, and impact on society. In this collaboration between AI, Sustainability, HCI and…
In 2012, the United Nations introduced 17 Sustainable Development Goals (SDGs) aimed at creating a more sustainable and improved future by 2030. However, tracking progress toward these goals is difficult because of the extensive scale and…
From 2000 to 2015, the UN's Millennium Development Goals guided global priorities. The subsequent Sustainable Development Goals (SDGs) adopted a more dynamic approach, with annual indicator updates. As 2030 nears and progress lags,…
Since the United Nations launched the Sustainable Development Goals (SDG) in 2015, numerous universities, NGOs and other organizations have attempted to develop tools for monitoring worldwide progress in achieving them. Led by advancements…
AI documentation is a rapidly-growing channel for coordinating the design of AI technologies with policies for transparency and accessibility. Calls to standardize and enact documentation of algorithmic harms and impacts are now…
Sustainable Development Goals (SDGs) bring together the diverse development community and provide a clear set of development targets for 2030. Given a large number of actors and initiatives related to these goals, there is a need to have a…
Artificial Intelligence (AI) has the potential to revolutionize various sectors, yet its adoption is often hindered by concerns about data privacy, security, and the understanding of AI capabilities. This paper synthesizes AI governance…
We discuss our insights into interpretable artificial-intelligence (AI) models, and how they are essential in the context of developing ethical AI systems, as well as data-driven solutions compliant with the Sustainable Development Goals…
AI-based decision support tools (ADS) are increasingly used to augment human decision-making in high-stakes, social contexts. As public sector agencies begin to adopt ADS, it is critical that we understand workers' experiences with these…
Drought has become a critical global threat with significant societal impact. Existing drought monitoring solutions primarily focus on assessing drought severity using quantitative measurements, overlooking the diverse societal impact of…
Language-based AI systems are diffusing into society, bringing positive and negative impacts. Mitigating negative impacts depends on accurate impact assessments, drawn from an empirical evidence base that makes causal connections between AI…
Participants in recent discussions of AI-related issues ranging from intelligence explosion to technological unemployment have made diverse claims about the nature, pace, and drivers of progress in AI. However, these theories are rarely…
Regulations govern many aspects of citizens' daily lives. Governments and businesses routinely automate these in the form of coded rules (e.g., to check a citizen's eligibility for specific benefits). However, the path to automation is long…
Evaluating generative AI (GenAI) systems is challenging because many targets of evaluation are broad, contested concepts, such as "reasoning," "fairness," or "creativity." When these concepts are left underspecified, it becomes unclear what…
Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential…