Ten years ago, we couldn't have imagined how tools like machine learning, eDNA, and satellites would advance and transform conservation work. Now technology is advancing faster than ever, and as tools become smaller, lighter, and more affordable, it's vital to have a space where community members can discuss the next big thing, share ideas, compare tool options, and tell the story of their experiences - positive, negative, and anything in between - while using new technologies.
In 2021, the WILDLABS State of Conservation Tech report detailed what tools show the most promise according to community members, as well as what tools are currently seen as the most effective. And as new tools enter the field, we're excited to see how this data will change over time, and how this group grows over time as well.
Our State of Conservation Tech research also discusses something called the "Hype Cycle" - the pattern that occurs when a new technology bursts onto the scene, promises to be an exciting solution, encounters challenges as new users adopt the tool and put it into practice beyond just theory, and eventually settles into its most effective state as users acquire the right skills to use it to its actual potential. Machine learning, one of the most promising technologies, is currently in the middle of its own hype cycle, and we see community members working through their own hurdles to incorporate ML into their work effectively. Despite what you may think, this Hype Cycle can also be positive for tech development, as it means that users have big ideas for new tools, and with the right resources and skills, they can work toward bringing those ideas to life. And as our community members experiences the Hype Cycle for various tools at their own paces, we hope this group will also serve as a place to discuss that process and overcome hurdles together.
Ready to discover new possibilities? Join our Emerging Tech group now and get to know your forward-thinking conservation tech peers!
Header photo: Internet of Elephants
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