AI in Citizen Science: How Citizens and Algorithms Work Together

The results show that AI is primarily used for analyzing large amounts of data, classifying images, and transcribing historical sources. At the same time, human involvement remains central, particularly in the monitoring, validation, and training of AI models by volunteer participants.

Example projects illustrate that citizen scientists actively contribute to improving AI systems. In addition to the opportunities, challenges are also identified, including issues of data quality, data protection, copyright, and the necessary digital literacy of those involved.

Overall, AI is understood not as a replacement for human research, but as a complement to it. Its benefits arise primarily from the combination of technical capabilities with transparent communication and clear ethical guidelines.

Further information