[HTML][HTML] Artificial intelligence for environmental security: national, international, human and ecological perspectives

M Francisco - Current Opinion in Environmental Sustainability, 2023 - Elsevier
Highlights•Environmental security perspectives can shape our understanding of artificial
intelligence.•These perspectives impact the aims, uses, actors nvolved, risks and …

AI-enabled strategies for climate change adaptation: protecting communities, infrastructure, and businesses from the impacts of climate change

H Jain, R Dhupper, A Shrivastava, D Kumar… - Computational Urban …, 2023 - Springer
Climate change is one of the most pressing global challenges we face today. The impacts of
rising temperatures, sea levels, and extreme weather events are already being felt around …

Scrutinizing environmental governance in a digital age: New ways of seeing, participating, and intervening

S Kloppenburg, A Gupta, SRL Kruk, S Makris… - One Earth, 2022 - cell.com
Digital technologies play an increasingly important role in addressing environmental
challenges, such as climate change and resource depletion. Yet, the characteristics and …

Algorithmic epistemologies and methodologies: Algorithmic harm, algorithmic care and situated algorithmic knowledges

S Maalsen - Progress in Human Geography, 2023 - journals.sagepub.com
Algorithms have been the focus of important geographical critique, particularly in relation to
their harmful and discriminatory effects. However, less attention has been paid to engaging …

Bridging adaptive management and reinforcement learning for more robust decisions

M Chapman, L Xu, M Lapeyrolerie… - … Transactions of the …, 2023 - royalsocietypublishing.org
From out-competing grandmasters in chess to informing high-stakes healthcare decisions,
emerging methods from artificial intelligence are increasingly capable of making complex …

Foresight science in conservation: Tools, barriers, and mainstreaming opportunities

G Ednie, T Kapoor, O Koppel, ML Piczak, JL Reid… - Ambio, 2023 - Springer
Foresight science is a systematic approach to generate future predictions for planning and
management by drawing upon analytical and predictive tools to understand the past and …

Clustering of disaggregated fisheries data reveals functional longline fleets across the Pacific

TH Frawley, B Muhling, H Welch, KL Seto, SK Chang… - One Earth, 2022 - cell.com
Ensuring the long-term sustainability of tuna, billfish, and other transboundary fisheries
resources begins with data on the status of stocks, as well as information concerning who …

Deep reinforcement learning for conservation decisions

M Lapeyrolerie, MS Chapman… - Methods in Ecology …, 2022 - Wiley Online Library
Can machine learning help us make better decisions about a changing planet? In this
paper, we illustrate and discuss the potential of a promising corner of machine learning …

Reflections from the Workshop on AI-Assisted Decision Making for Conservation

L Xu, E Rolf, S Beery, JR Bennett, T Berger-Wolf… - arXiv preprint arXiv …, 2023 - arxiv.org
In this white paper, we synthesize key points made during presentations and discussions
from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for …

[HTML][HTML] Exploring the Role of Artificial Intelligence in Achieving a Net Zero Carbon Economy in Emerging Economies: A Combination of PLS-SEM and fsQCA …

S Mondal, S Das, VG Vrana - Sustainability, 2024 - mdpi.com
In this paper, we examine the role of artificial intelligence (AI) in sovereignty and carbon
neutrality, emphasizing digital inclusion and climate-resilient AI strategies for emerging …