Two prototype AI systems designed to enhance access to climate data, support decision-making, and improve efficiency are illustrated here with key concerns identified around responsibility, quality, and trustworthiness of AI outputs.
Abstract
Generative AI can help scale climate services to meet growing demand. This approach is illustrated here with two prototype AI systems designed to enhance access to climate data, support decision-making, and improve efficiency. Key concerns are identified around responsibility, quality, and trustworthiness of AI outputs. Emerging best practices in system development are linked to core principles of salience, credibility, and legitimacy, to ensure alignment with user needs and societal values.
This thesis examined how AI-enabled technologies can be developed and governed to be safe, reliable, transparent and responsive to human needs and developed a framework linking technical design, organisational decision-making, governance practices and user trust across the AI ecosystem.
Calls to co-produce climate adaptation research with communities are multiplying, yet engagement often remains shallow: communities are consulted, not granted shared authority over how problems are framed, findings are interpreted, and outputs are used. This Perspective distinguishes instrumental engagement from epis...
I. Malik, James D. Ford· npj Climate Action· 0 citations
Climate change and misinformation are interconnected global crises shaped by tensions between individual, collective and vested interests. Drawing on climate psychology, we distil six insights for misinformation research to strengthen policy relevance, systems thinking and resilience to attacks.
Tobia Spampatti, Bojana Većkalov, Sandra J. Geiger et al.· Nature Human Behaviour· 0 citations
This conceptual study applies design-science research, structured synthesis and scenario-based stress testing to develop an accountability-centred governance artifact that was evaluated ex ante against lifecycle completeness, decision traceability, cross-agency usability, AI oversight, auditability and capacity for ins...
Alok Kumar Bhargava· International Journal of Adv...· 0 citations
This special commentary argues that military articificial intelligence integration must pivot from model reliability to a “cognitive fit” within human-machine teams to ensure decision advantage under uncertainty. It advances beyond traditional artificial intelliegenceintelligence metrics by focusing on dynamic operatio...
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