AI for Good refers to the use of artificial intelligence to address social, environmental, or humanitarian challenges, aiming to create positive and meaningful impacts on the world. It involves leveraging AI technologies responsibly to solve problems and improve lives.
Real-world examples:
- Healthcare: AI systems help detect diseases early, like using image recognition to identify cancer in medical scans or predicting outbreaks of diseases like malaria.
- Climate change: AI is used to model climate data, optimize renewable energy systems, and monitor deforestation from satellite images.
- Education: Adaptive learning platforms use AI to provide personalized education to students in underserved communities, improving access and outcomes.
- Disaster relief: AI-powered tools analyse real-time data to help prioritize and coordinate disaster response, like predicting flood zones or mapping areas affected by earthquakes.
While “AI for Good” overlaps with “Data for Good,” it specifically focuses on how intelligent systems themselves — beyond just the data — are applied to make a positive difference.