AI for Biodiversity: Overcoming Barriers to Impact
There is significant potential for artificial intelligence (AI) to contribute to our ability to monitor biodiversity at global scale in order to guide policies at global and national scales and target conservation resources where they are most needed. Challenges require innovation in both methods and the systems required to deploy them, and must be co-developed via close partnership across disciplines and geographies. This workshop will convene experts across the fields of AI and ecology with focus on both research and practice to identify key gaps and bottlenecks, prioritize goals, and build collaborations for interdisciplinary solutions.
Biodiversity and ecosystems underpin all human wellbeing and endeavors – from health and happiness to prosperity and security. Yet biodiversity is declining rapidly, with global and local extinctions, and widespread population declines. There is a critical need to track and model wildlife changes to adaptively manage ecosystems sustainably. A rapid growth in sensor technologies is revolutionizing how environments can be monitored and a tsunami of high-resolution data streams is being generated from satellite imagery, visual and audio sensor data, geospatial tracking devices, and environmental DNA. Tools for processing biodiversity data acquisition and turning these data into useful information are also growing exponentially, potentially transforming our understanding of how to manage ecosystems and meet the world’s critical global challenges.
However, while both the ecology and data science / AI communities are increasingly interested in computational approaches to biodiversity, there are significant cultural divides that impede communication between these different areas and a lack of opportunities to facilitate knowledge-sharing and interdisciplinary collaboration, resulting in siloed work where too often each field tries to reinvent what the other fields already know. Bridges must be built to realize the potential of applying new computational tools to address the critical ecological and environmental challenges of our time.
As biodiversity data grows and tools from artificial intelligence (AI) become more powerful, there are increasing opportunities for cross-disciplinary partnership in helping address the world’s urgent biodiversity crisis. This workshop will bring together experts and practitioners across many areas of AI and ecology, including specialists in computer vision, species distribution modeling, citizen science data, taxonomy and systematics, bioacoustics, conservation biology, and other areas. Many of these communities have very limited opportunities to intersect, and we aim to provide a rare platform for discourse with an equal balance of participants having primary expertise in AI and ecology, respectively, and coming from both research and deployment-focused organizations.
The structure of the workshop will aim to facilitate both in-depth learnings on the diverse topics represented by attendees, and also unstructured time to facilitate networking and collaboration-building.
Workshop Impacts / Outputs
Given the timeliness of the topic, we foresee this workshop building strong connections between world leaders in this space across borders in order to identify gaps in our current research and catalyze new collaborations.
As a key deliverable, we aim to point out and address key challenges in translating research insights and technology- and data-driven tools to conservation practice in the field and measuring progress to our global sustainability goals, through a shared discussion between diverse technology builders, technology users, and technology funders. We will develop a map of existing tools, evaluate the technological readiness level (TRL) of each, and determine for each case the key bottlenecks that are preventing TRL advancement and broader use. Some of the common bottlenecks we have already observed are software engineering education and capacity, lack of computing and data infrastructure, lack of sustained funding to support the maintenance of tools, and lack of interdisciplinary discourse and community space leading to duplication of effort. We will release a report with our findings, which will serve to explicitly outline priorities for funders, governmental agencies, and researchers, with the goal of opening up concrete paths to tech transfer and impact at the intersection of AI and Biodiversity.