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.
Artificial intelligence (AI) increasingly shapes everyday life, making responsible design and deployment essential. This thesis examined how AI-enabled technologies can be developed and governed to be safe, reliable, transparent and responsive to human needs. It developed a framework linking technical design, organisational decision-making, governance practices and user trust across the AI ecosystem. The findings show that successful AI deployment depends not only on technical performance, but also on accountability and continued alignment between technology, its operating environment and the people it serves.
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 epistemic partnership, and argues that the main barrier to meaningful co-production is institutional rather than methodological. It offers insights for participation that is rigorous, ethical, and institutionally workable, structured around three stages of shared authority.
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
Background: City economic regions are delivered through portfolios of mutually dependent infrastructure, land, service and regulatory actions. Conventional dashboards improve visibility but often fail to preserve the evidence, authority, assumptions and distributional consequences behind consequential decisions. Methods: This conceptual study applies design-science research, structured synthesis and scenario-based stress testing to develop an accountability-centred governance artifact. The proposed architecture was evaluated ex ante against lifecycle completeness, decision traceability, cross-agency usability, AI oversight, auditability and capacity for institutional learning.
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 operational adaptation, and systemic resilience. The research employs an eco-cognitive framework, synthesizing John Boyd’s evolutionary theories with modern cognitive science and risk management principles. This analysis offers policy and military practitioners a crucial blueprint for designing command structures that preserve human judgment and mitigate risk.
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.