AI for Good is a public charity and UN platform that hosts annual summits in Geneva, Switzerland to discuss the beneficial use of artificial intelligence (AI). The organization was founded in 2015 and hosts satellite operations in Boston, New York, San Francisco, London, Ljubljana
In AI for Good, interdisciplinary researchers, governments, non-profits
AI for Good summit topics
An AI for Good summit typically focuses on many subjects surrounding AI in the format of both panels and workshops. Participants in the summit identify and select some of the proposed panels and topics to decide resources and future steps needed to propel the selected panels forward as a project.
As an example of what the summit panels and workshops cover, some of the 2019 summit panels include:
- Scaling AI for Good- Which teaches about successfully scaled projects across
internet, data and AI.
- Good Health and Well Being- Which looks at existing AI initiatives in different countries, AI adoption maturity models and use cases that benefit from AI for Health.
- Science for Good, AI for Science- Which explores how AI supports scientists to find breakthroughs on pressing issues.
- AI & Agriculture- Which shares any innovations or proposals in regards to progress in the use of AI in agriculture.
- Future of Smart and Safe Mobility- Which focuses on the use of AI in self-driving cars, car security and road safety.
- Culture and Storytelling in the Age of AI Interactive- Which addresses automated storytelling based on data collection.
- Unintended Consequences of AI- Which analyzes the potential behind deploying AI at a global scale which could cause issues that were not clear on a smaller scale.
AI for Good projects
AI for Good works with multiple external organizations to help aid in relevant social issues. AI for
- Ocean life protection- Which has collected data on topics like plastic pollution coalition, plastic pollution in the world’s oceans, river plastic emissions in oceans and critical habitat biodiversity globally.
- Education- Which aims to make personal learning models for users.
- Urban development architecture- Which has collected data on refugees around the world, including refugees in the United States, population movement and densities of areas which had national disasters occur in them.
- Media bias- Which tackles media bias to ensure people have access to neutral sources of information.
- Carbon sequestration- Which collects data on issues regarding forest and reforestation data, region and biome data and data on CO2.
- Health and sleep nutrition- Which seeks to collect extensive datasets about sleep and health patterns, encouraging experts to share their findings.
- Food energy and water- Which focuses on the implementation of smart IoT systems that can sense, measure and respond to changing environments for preservation means.
- Corruption- Which focuses on the implementation of AI to create a mechanism of transparency and accountability.