Artificial intelligence is evolving at a staggering pace, reshaping industries, economies, and how we interact with the world. On an individual level, it's quickly changed how I work and even become a part of some unexpected day-to-day habits. Its impact is inevitable. On some days, I am quite concerned about the future, while on other days, I envision more hopeful outcomes.

I have concerns about automation, job displacement, and ethics, which I'm sorting out in my head, often on long walks. I'm not an AI expert by any means. However, I also know that not being an expert shouldn't stop us from thinking about something or using our imagination. If we're going to steward a technology as powerful as this, we should spend time thinking about and talking about it.‍ 

Below are a few ideas that have bubbled up in my head over the past month. It’s possible many of these things are already in development or being piloted. This is meant as a personal imaginative exercise rather than a definite report on the state of AI and the environment. If you know of real examples or companies related to these ideas, share them with me. I’d love to learn more.

1. Making Spatial Data More Accessible

With satellite imagery and remote sensing, we have abundant environmental data, but interpreting it is often limited to experts with technical knowledge (Python, Spatial SQL, etc). AI has the potential to make planetary-scale data accessible to more people than ever before. I'm excited to see how it can enable us to query and visualize spatial data more naturally. Anyone could ask questions like: "How much glacial surface area was lost in Canada last year?" or "What percentage of my state is forested?" Recently, NASA launched a project called Earth CoPilot, which has many of these features. I hope we see more advances like this to enable better science, journalism, and policy, as well as a general curiosity about our planet.

2. Smarter Supply Chains & the Circular Economy

Many failures in the economy result from our inability to analyze systems holistically and make coordinated decisions. Unlike natural ecosystems, businesses often fail to reuse resources or use energy efficiently. The standard model is linear — input leads to output + waste. With some creativity and coordination, economies can operate more efficiently by coordinating with other businesses to share resources and minimize waste (i.e., industrial symbiosis). There are some successful pilot programs, like the Western Cape Industrial Symbiosis program, but most are limited by resources or the fact that all auditing and matchmaking is done by humans.

AI could be used to ingest unstructured business data—like supply chain documents and financial reports—and find synergies where waste from one company becomes a valuable input for another. This could improve regional circular economies, making them more efficient and self-sustaining. 

3. AI for Material Innovation

Building on the circular economy idea, AI could act as a research assistant for discovering new uses for waste materials. By training AI models on chemical properties, past innovations, and emerging technologies, we could accelerate the discovery of novel materials and applications. I'm excited by some of the material innovations I've seen within Maine, like converting lobster byproducts to eczema treatments. I'm hopeful that AI can assist with more of these discoveries, acting as an assistant to entrepreneurs and researchers working to make the most of our limited resources.

4. Ecosystem Observation

Historically, monitoring biodiversity required trained ecologists in the field, who manually collected data over long periods. AI, paired with low-cost cameras, trail sensors, and bioacoustics technology, can continuously observe ecosystems at an unprecedented scale. We can place virtual ecologists and biologists all over the world, which would likely lead to a better understanding of individual species and the overall web of life. I believe humans should continue to observe and study our environments directly, but I also see direct cases locally where AI could easily supplement human efforts, like the annual Alewife count in Maine.

5. Incentivizing Backyard Stewardship

On a more local level, AI could engage the general public in conservation by making biodiversity monitoring fun and interactive. I’ve seen this firsthand with the BirdBuddy birdfeeder, which monitors and classifies birds who visit your bird feeder. I’ve seen it turn tech bros turn into birders. This idea of tracking, educating, and gamifying backyard biodiversity could be extended to plants, insects, and wildlife in a user’s backyard. I can imagine a device that outputs some sort of biodiversity score for your backyard or land. This kind of hyperlocal engagement could drive a sense of greater stewardship and incentivize people to make gardening or landscaping decisions to support biodiversity.

6. Making Scientific Writing Digestible

Academic research, peer-reviewed papers, and scientific writing rarely make it beyond the walls of academia. Yet, the ideas within often have significant implications and value to others outside of academia. AI might be able to unlock a lot of that information by acting as a translation layer and turning dense scientific papers into digestible summaries, interactive graphics, and even short videos. We can look at a company like Pique Action, which condenses climate solutions into short highlight videos as successful models. Of course, it would be tricky to find a balance between nuance and brevity, but by making cutting-edge research more accessible to entrepreneurs, policymakers, and the general public, AI could help close the gap between knowledge and application.

7. Urban & Ecological Planning

AI could transform urban planning by analyzing how people naturally interact with spaces and using that data to design cities that work better for both people and nature. I know from conversations with the Maine Trails Coalition that a lack of pedestrian trail usage data limits advocacy, policy, and decision-making. Instead of relying on human monitoring or traditional traffic studies, AI could interpret video footage of foot traffic, trail usage, and green space interactions to provide baseline data and even recommendations for better use.

9. Interspecies Communication

This idea is probably the most abstract and least practical, but it also somehow feels obvious, inevitable, and powerful. While our understanding of non-human consciousness is limited, what we do know about other species largely comes from extended observation. If you spend enough time listening, watching, and observing something, you might eventually find correlations between sounds/movements and meaning (i.e., language). AI is masterful at understanding language and finding patterns. If trained on data or observations of other species, it’s possible it could identify and understand communication within other species. What might the world look like if we could understand our non-human neighbors? Would it change how we behave?

Keep Asking, Keep Imagining

The possibilities for AI and nature feel endless—but so do the tensions between its potential for harm and its capacity for good. Whether AI becomes a tool for regeneration or destruction depends on the questions we ask, the choices we make, and where we put our focus.

* I used AI to act as an interviewer and transcriber to develop this post. The ideas and most of the words are my own. Additionally, the cheesy featured image for this post was generated by AI.