Less than 1 month until our TNW Conference 2022 in Amsterdam – get your access pass now!

AI & futurism

This article was published on March 20, 2020

AI analyzes biology studies to find out we’re getting better at wildlife conservation

Researchers used sentiment analysis to rate thousands of conservation studies

AI analyzes biology studies to find out we’re getting better at wildlife conservation Image by: happymillerman
Thomas Macaulay
Story by

Thomas Macaulay

Writer at Neural by TNW — Thomas covers AI in all its iterations. Likes Werner Herzog films and Arsenal FC. Writer at Neural by TNW — Thomas covers AI in all its iterations. Likes Werner Herzog films and Arsenal FC.

A new AI system has revealed that we’re finally getting better at wildlife conservation.

Researchers came to this conclusion after using machine learning to analyze more than 4,000 studies on species reintroduction across four decades.

The system evaluated the outcomes of conservation programs by assessing the study abstracts with sentiment analysis, a form of AI that identifies positive and negative emotions expressed in text. The results suggested that a growing number of initiatives were working.

Greetings humanoids

Subscribe now for a weekly recap of our favorite AI stories

“Over time, there’s a lot less uncertainty in the assessment of sentiment in the studies, and we see reintroduction projects become more successful — and that’s a big takeaway,” said study author Kyle Van Houtan, the chief scientist at Monterey Bay Aquarium.

[Read: AI studies our photos to prove that nature makes us happy]

The idea for the study emerged when researchers studying conservation literature to learn how to reintroduce animals to the wild were overwhelmed by the enormous quantity of information.

They decided to see if AI could do a better job.

Building the system

The team first searched through the Web of Science database to identify 4,313 species reintroduction studies that had been published between 1987 and 2016.

They then built a model that gave each study a store with existing sentiment analysis lexicons, which had previously been used to rate things such as movie and restaurant reviews.

To ensure that the ratings were accurate, the researchers searched the results for positive words such as “success,” “protect,” and “growth,” as well as negative ones like “threaten,” “loss,” and “kill.”

They found that the repurposed tools had worked surprisingly. This is likely because many words used in conservation biology are also common in everyday language.

They now want the technique to be used applied more broadly in both conservation biology and other fields, where much of the local efforts to reintroduce wildlife go unnoticed.

Their works shows that while humanity‘s future looks bleaker by the day, at least the survival chances of other animals could be improving.

Get the Neural newsletter

Greetings Humanoids! Did you know we have a newsletter all about AI? You can subscribe to it right here.

Also tagged with