Recognizability bias in citizen science photographs

Article Multidisciplinary Sciences

Advances in automatic identification of flying insects using optical sensors and machine learning

Carsten Kirkeby et al.

Summary: Farmers around the world utilize optical sensors combined with machine learning to classify flying insects in order to optimize the application of insecticides. This technological advancement enables a precise and environmentally-sensitive use of pesticides in agriculture, leading to improved crop yield and pest control.

SCIENTIFIC REPORTS (2021)

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Article Ecology

Ensuring effective implementation of the post-2020 global biodiversity targets

Haigen Xu et al.

Summary: The majority of countries have not set effective national targets in accordance with the Aichi Targets, resulting in inadequate investments, knowledge, and accountability for biodiversity conservation to enable effective implementation.

NATURE ECOLOGY & EVOLUTION (2021)

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Review Green & Sustainable Science & Technology

The Partnership of Citizen Science and Machine Learning: Benefits, Risks, and Future Challenges for Engagement, Data Collection, and Data Quality

Maryam Lotfian et al.

Summary: The integration of AI and citizen science is primarily used in biodiversity projects, focusing on using citizen science data to train ML algorithms; it has impacts on volunteer engagement, data collection, and data validation.

SUSTAINABILITY (2021)

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Article Ecology