Artificial Intelligence Meets Citizen Science to Supercharge Ecological Monitoring

Abstract

The development and uptake of citizen science and artificial intelligence (AI) techniques for ecological monitoring is increasing rapidly. Citizen science and AI allow scientists to create and process larger volumes of data than possible with conventional methods. However, managers of large ecological monitoring projects have little guidance on whether citizen science, AI, or both, best suit their resource capacity and objectives. To highlight the benefits of integrating the two techniques and guide future implementation by managers, we explore the opportunities, challenges, and complementarities of using citizen science and AI for ecological monitoring. We identify project attributes to consider when implementing these techniques and suggest that financial resources, engagement, participant training, technical expertise, and subject charisma and identification are important project considerations. Ultimately, we highlight that integration can supercharge outcomes for ecological monitoring, enhancing cost-efficiency, accuracy, and multi-sector engagement.

Keywords: AI; CS; automation; big data; biological conservation; data processing; deep learning; machine learning.

Figure 1

Example Uses of Artificial Intelligence, Machine Learning, and Deep Learning in Ecological Monitoring

Figure 2

Typical Roles of Citizen Science and Artificial Intelligence in Data Collection, Processing, and Analysis Note, there is a growing movement to involve citizen scientists at all stages of the scientific workflow, including data analysis.

Figure 3

The Opportunities (Top) and Challenges (Bottom) of Citizen Science (Left) and Artificial Intelligence (Right) for Ecological Monitoring, Including Integration Opportunities (Top Center Overlap) and Challenges Common to Both Categories are efficiency (opportunities only), accuracy, discovery, engagement, resources, and ethics (challenges only) across each row of text. Superscripts refer to the following supporting references: 1,^, 2, 3,^, 4,^,, 5,^, 6,^,, 7, 8,^,, 9,^, 10, 11,^,, 12, 13, 14,^, 15, 16,^, 17, 18, 19,^, 20, 21,^,,, and 22.

Figure 4

Important Project Considerations when Implementing Citizen Science or Artificial Intelligence for Ecological Monitoring Project attributes placed toward either citizen science (CS) or artificial intelligence (AI) indicate relatively higher importance for that technique, but not a lack of importance for the other technique. Project attributes placed in the middle indicate equally high importance for both CS and AI. All project attributes would be important to consider for integrated approaches. Placement of attributes is guided by the literature and may change over time.