Lately, the news has been filled with stories about the good, the bad, and the ugly of artificial intelligence (AI). From ChatGPT to AI bots popping up on all our digital devices, it feels like AI and big data tools have very quickly become omnipresent in many of our spaces. And even though we have been leveraging data in our conservation spaces for a long time, there is newfound interest in seeking meaningful and impactful ways to incorporate novel data tools into our work as we seek to reduce the impacts of climate change and reverse biodiversity loss.
I recently had the immense pleasure to attend the Greater & Greener conference in Seattle this June. This convening is one of the largest gatherings of urban parks thinkers, innovators and decision-makers in North America. Among its interlinked themes, the event focused on equity, inclusivity and climate change, all themes that echo values we hold at the Salazar Center. One of the keynotes, Jaqueline Lu, of Helpful Places, gave an inspiring and passionate talk about the potential for AI to empower local residents and to build trust between communities and local government decision-makers, all while helping to green our cities. In a space where conversations were focused on trees, parks, and people, it was a head turner. What she talked about really resonated with me in a surprising way.
Jaqueline founded Helpful Places to foster building diverse coalitions to advance the adoption of what is known in the AI world as Digital Trust for Places & Routines (DTPR), which is an open-source “system-to-people” communication standard for technology. The goal of their DTPR project is to advance greater transparency and civic dialogue about the use of digital technologies in the built environment (you can see some examples of it here and here). Jaqueline told a story of how in 2015 she worked on a city-wide participatory street tree mapping project in New York City. The effort involved 2,200 volunteers from 60 community groups, who mapped over 600,000 trees. This project was the genesis of the idea that we could better leverage data to empower communities and engage more collaboratively with city decision makers. It helped drive her to think more deeply about the ways that cities struggle with engaging communities about data. Realizing that most of the public will never attend a community feedback meeting, but everyone in a city will be using public spaces, she saw an opportunity.
There were multiple ideas in this talk that resonated with me. First, I loved that the motivation for the tool was centered around community co-creation and trust building. To create the DTPR framework, people from a diversity of backgrounds and lived experiences co-designed and tested it along with technology, privacy, smart city and public realm experts.
This notion of community co-creation and trust aligns with our values at the Salazar Center. At our Symposium for Conservation Impact last year, several speakers elevated the idea that progress only moves at the speed of trust and this AI tool is an intriguing way to think about building trust. The talk also made me wonder about how AI tools such as what the speaker described can be better incorporated into climate and biodiversity protection, in cities or outside cities. In our current urban climate resilience work, we too have been thinking about ways that city decision makers can make better use of data to inform and accelerate decision-making and action. Are AI tools the best way to accelerate action so we can reach change faster on the climate and biodiversity fronts? We already use a lot of big data sets in biodiversity protection and climate resilience work and there are many examples of urban climate community science projects (see this example from one of other former Symposium speakers, Dr Jeremy Hoffman). Yet, what was intriguing about this presentation was how the Helpful Places DTPR project was not simply a data gathering exercise that could potentially be used to influence government decision-making, but that government decision-making was built into the process through collaborative engagement with communities.
AI is not going away – those horses have left the barn. It is therefore critically important that we think deeply and carefully about how it gets used, who gets to use it, and the best ways to make it work for nature and people.