Responsible and trustworthy AI
Promoting AI that is transparent, fair, robust and subject to appropriate human oversight and accountability.
Focus area
Fostering trustworthy artificial intelligence that helps address energy and climate challenges while keeping its own footprint in view.
Artificial intelligence and other emerging technologies are developing rapidly and are increasingly embedded in everyday services and critical systems. They offer real potential to support sustainable development, for example by improving forecasts, optimising energy use and accelerating research.
These technologies also raise important questions. AI systems must be reliable, fair, transparent and subject to meaningful human oversight. Training and operating them requires computing power, and therefore energy, water and hardware. And their benefits depend on people having the skills to use, question and govern them.
The Foundation seeks to encourage an approach to AI that is both ambitious and responsible: using it where it adds genuine value for people and the planet, and being clear about its limitations and costs.
Promoting AI that is transparent, fair, robust and subject to appropriate human oversight and accountability.
Supporting applications that help forecast renewable output, optimise energy use and advance climate research.
Encouraging efficient models and infrastructure, and transparent reporting of the resources AI systems consume.
Helping professionals, students and the public build the knowledge to use and assess AI critically.
Trustworthy AI is reliable, transparent about how it works and what it is used for, fair in its effects and subject to meaningful human oversight. It should also respect privacy and be accountable when things go wrong. The Foundation encourages these qualities to be built in from design through to deployment.
AI can help forecast weather-dependent renewable generation, anticipate demand, detect inefficiencies and support the design of new materials and processes. These applications can make energy systems cleaner and more efficient. Their value depends on good data, careful validation and an honest comparison with simpler alternatives.
Yes. Training and running AI models requires computing infrastructure that consumes electricity and, in many cases, water for cooling, as well as hardware with its own manufacturing impact. The Foundation encourages efficient models, sustainable infrastructure and transparent reporting so that these costs can be understood and reduced.
The Foundation welcomes collaboration on trustworthy AI and its responsible use for sustainable development.
In practice
Projects and initiatives will be published here as they are launched.
Insights
Updates, announcements and articles will appear here as they are released.
Focus areas
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