Humane Intelligence launched the third set of bias bounty challenges, in partnership with the Indian Forest Service! For this competition, participants developed innovative solutions and strategies for tree planting site recommendations that were informed by biophysical data and community needs. This competition focused on ensuring fair, biophysically informed, and community-driven tree planting site recommendations—tackling bias in AI-driven environmental decision-making. This work highlights the critical role of responsible AI in environmental policy, ensuring that data-driven decisions respect both biodiversity and local livelihoods.
The Winners
Task: Conduct a literature review and write a short position piece on ensuring fair, biophysically Informed, and community-driven tree planting site recommendations.
Prizes
Task: Identify the most important features affecting tree planting feasibility using a provided dataset.
Prizes
Task: Develop a site recommendation engine that predicts site suitability for tree planting, integrating key features identified in the beginner level.
Prizes
Exploring Limits to Tree Planting as a Natural Climate Solution: Article
Global forest restoration and the importance of prioritizing local communities: Article
Predicting wasteful spending in tree planting programs in Indian Himalaya: Article
Recognizing the equity implications of restoration priority maps: Article
Plantations and pastoralists: reforestation activities make pastoralists in the Indian Himalaya vulnerable: Article