Conservation

Analysing complex information and enabling data-driven management are just two examples of the many benefits artificial intelligence can provide for ecologists.

The field of artificial intelligence (AI) can seem overwhelming for ecologists and conservation practitioners – we’re here to change that.

Caption of researcher setting up a camera trap

Researcher setting up a camera trap in Wellington, New Zealand.
Victor Anton / Wildlife.ai

Learning about artificial intelligence

If you want to gain an overall understanding of AI, we recommend you to take the excellent (and free!) introductory online course offered by elements of AI. No complicated math or programming are required in this 30-hour online course.

There are many educational resources to help you use machine learning algorithms in your conservation project. Join our community and stay up-to-date with the increasing number of webinars, books, online courses, and presentations.

Best practices

Before you start using ML in your conservation project, we recommend that you:

  • identify the assumptions of the algorithms, the scope of the training data and the potential risks of using it,
  • make your models and data sets explainable. Not only to reviewers or internal personnel but to stakeholders and future users,
  • review the data management security and the implications for misuse, human privacy, and safety of the models and data sets and
  • understand the data rights and fair to use before publishing any material or using publicly available material.

To find out more about best ethical practices, read towards ethical deployment of AI for conservation systems.