Reflection on the responsibilities of data-intensive research organizations in an AI-driven world – A panel discussion
TL;DR
This moderated panel will explore how data-intensive research organizations can balance innovation with stewardship and suggest recommendations that help data-intensive organizations reimagine their responsibilities not only as the producers of knowledge but as institutions whose everyday operations shape a sustainable and ethical future.
Abstract
The exponential adoption of artificial intelligence (AI), worsening climate disruptions, and new One Health approaches to global health policy, prompt research organizations to re-examine their responsibilities. AI offers powerful capabilities from precision medicine to ecosystem monitoring. Yet its deployment raises concerns related to high energy and water demands, hardware that depends on scarce resources, data governance, ethics and equity. There is further risk that technological solutions may distract from essential ecological and social action. A One Health lens, recognizing the interconnectedness of human, animal, and environmental health, encourages organizations to examine whether their AI tools and infrastructures truly support healthy ecosystems and communities. This raises critical questions: How should organizations balance scientific urgency with the responsibility to protect people, places, and data? How can meaningful interdisciplinary collaboration be structured? How can institutions uphold accountability to land, water, Indigenous communities, and future generations when deploying AI? Operational issues are central to this conversation. This moderated panel will explore how data-intensive research organizations can balance innovation with stewardship. Discussion topics include: What constitutes climate-resilient and environmentally responsible research infrastructure? What is the purpose of calculating organizational carbon footprints, and how can institutions meaningfully measure and manage the carbon and material impacts of AI? How can research cultures encourage the use of energy-efficient models, sustainable computational practices, and responsible procurement? Input from this panel will inform recommendations that help data-intensive organizations reimagine their responsibilities not only as the producers of knowledge but as institutions whose everyday operations shape a sustainable and ethical future.