Giving Compass' Take:

• Heather Clancy explains how a partnership aims to improve disaster relief and recovery by using AI to better meet community needs. 

• How can funders support efforts to use AI to improve human services? How can bias be avoided in this type of important technology? 

• Learn how AI could help philanthropy be more data-driven. 

As global losses rack up from climate change-exacerbated natural disasters — from voracious wildfires to ferocious hurricanes — communities are scrambling to prepare (and to hedge their losses).

While information technologies such as machine learning and predictive analytics may not be able to prevent these catastrophes outright, they could help communities be better prepared to handle the aftermath. That’s the spirit behind a unique collaboration between Chicago-based technology services company Exigent and the Schulich School of Business at York University in Toronto, one that aims to create a more cost-effective and efficient marketplace for disaster relief and emergency response services.

The idea is to help state and provincial governments collectively build a more centralized inventory of relief supplies and other humanitarian items based on the data from a particular wildfire or hurricane season.

Rather than buying supplies locally based on the predictions — something many small towns in fire-prone areas can ill-afford — a community would buy "options" for these services in the marketplace being developed through this partnership. If the town ultimately doesn't need the items, it could "trade" them to another region that does have a need, either in the same state or another location. In effect, towns across a state or region or even country could arrange for protection, without having to make that investment outright.

Read the full article about AI for disaster relief and recovery by Heather Clancy at GreenBiz.