Between Code and Consciousness is a series by The Beautiful Truth asking the question: What does it mean to think, create or decide in the age of AI? Nine leading voices reflect on artificial intelligence – not as an abstract force, but as a tool whose worth depends on how it honours our humanity. 

Cambridge scholar Joycelyn Longdon is reshaping how artificial intelligence engages with the natural world. Through AI-enabled “Shazam for nature” tools, she explores how remote sensors and machine learning can help us listen to and protect biodiversity in new ways. Advising organisations from the UN to Greenpeace, she also exposes the privacy risks, colonial legacies and exclusion of Indigenous voices that continue to shape global tech agendas.

Can you explain what the ‘internet of trees’ is and how it relates to AI and conservation?  

The phrase ‘internet of trees’ describes the technologies used to monitor biodiversity and analyse data in forest ecosystems – like satellites, drones, LiDAR [light detection and ranging], camera traps and eco-acoustic sensors, which I work with. Bioacoustics monitors vocalising species – birds, frogs, insects, monkeys – tracking populations and how soundscapes change over time with climate change. 

The sensors I use are cheap and can be left in the forest for months, producing vast datasets. Machine learning is essential here: it identifies species and patterns no human could ever process alone. It gives us this ‘ear to the forest floor’ we’ve never had before. 

But, alongside those capabilities, are there risks? 

Absolutely. Technology is never neutral – it arises out of hierarchies and ideologies. In conservation, this matters because much biodiversity lies in the tropics. These are lived places: cultural, spiritual, sources of sustenance. Too often, they’re framed as empty wilderness in line with colonial ideas. 

Conservation itself is reckoning with its colonial history. When you put technology into that context, you risk reinforcing injustices. In fields like social media or hiring, we already debate bias in tech. In ecology, people often assume data is automatically good. That’s not true. 

If data isn’t automatically good, and AI encodes particular values, what else have you had to unlearn in engaging with it? 

I grew up Ghanaian but also in a Western scientific paradigm where intelligence is tightly linked to sociopolitical power. That tradition separates humans from nature, science from spirituality, reason from emotion. It casts Indigenous knowledge as unintelligent. 

Take Native American communities who returned half their rice harvest to the river to feed salmon. From a capitalist view, that’s wasteful, but it’s deeply intelligent, relational and regenerative. 

Unlearning means moving closer to these other ways of knowing. I love technology, I studied astrophysics out of awe for space, but there are other types of intelligence – spiritual, cultural, ecological – that are also forward-looking and innovative.  

What would a more ‘just’ relationship with technology look like? 

It isn’t about utopia. It depends on context, history, need. A bicycle, a tractor, a living root bridge, they all emerged from particular cultures. Science was always about curiosity and creativity, and it’s crucial not to deny communities agency. Even generative AI comes from the earth – it uses the earth. The question is whether technologies interact generatively or extractively – institutions need more space to reflect on this.